From f3df7f06d4419a9ed41928124702bda222a9b4f0 Mon Sep 17 00:00:00 2001 From: Kurokabe Date: Thu, 18 Dec 2025 15:48:16 +0100 Subject: [PATCH 01/11] feat: experiment finetuning compatibility with peft --- .../components/huggingface_connector.py | 12 +- darts/models/forecasting/chronos2_model.py | 150 +++++++--- darts/models/forecasting/foundation_model.py | 36 ++- .../26-Chronos-2-finetuning-examples.ipynb | 276 ++++++++++++++++++ 4 files changed, 425 insertions(+), 49 deletions(-) create mode 100644 examples/26-Chronos-2-finetuning-examples.ipynb diff --git a/darts/models/components/huggingface_connector.py b/darts/models/components/huggingface_connector.py index 41fb1d1065..4006ec6085 100644 --- a/darts/models/components/huggingface_connector.py +++ b/darts/models/components/huggingface_connector.py @@ -13,12 +13,12 @@ from safetensors.torch import load_file from darts.logging import get_logger, raise_log -from darts.models.forecasting.pl_forecasting_module import ( - PLForecastingModule, -) +from darts.models.forecasting.pl_forecasting_module import PLForecastingModule logger = get_logger(__name__) +from darts.models.forecasting.foundation_model import FoundationPLModule + class HuggingFaceConnector: def __init__( @@ -109,10 +109,10 @@ def load_model_weights( def load_model( self, - module_class: type[PLForecastingModule], + module_class: type[FoundationPLModule], pl_module_params: dict, additional_params: Optional[dict] = None, - ) -> PLForecastingModule: + ) -> FoundationPLModule: """Load the model by creating an instance of the given module class and loading the weights. Some configuration files might contain external parameters that are not part of the module class constructor like `architectures`. They are filtered @@ -140,7 +140,7 @@ def load_model( **pl_module_params, **additional_params, ) - self.load_model_weights(module) + self.load_model_weights(module.model) return module def _get_file_path( diff --git a/darts/models/forecasting/chronos2_model.py b/darts/models/forecasting/chronos2_model.py index f6267c7484..54228c1d3a 100644 --- a/darts/models/forecasting/chronos2_model.py +++ b/darts/models/forecasting/chronos2_model.py @@ -23,14 +23,10 @@ _Patch, _ResidualBlock, ) -from darts.models.components.huggingface_connector import ( - HuggingFaceConnector, -) +from darts.models.components.huggingface_connector import HuggingFaceConnector from darts.models.forecasting.foundation_model import ( FoundationModel, -) -from darts.models.forecasting.pl_forecasting_module import ( - PLForecastingModule, + FoundationPLModule, ) from darts.utils.data.torch_datasets.utils import PLModuleInput, TorchTrainingSample from darts.utils.likelihood_models.torch import QuantileRegression @@ -51,7 +47,7 @@ class _Chronos2ForecastingConfig: time_encoding_scale: int | None = None -class _Chronos2Module(PLForecastingModule): +class _Chronos2Module(nn.Module): def __init__( self, d_model: int = 512, @@ -65,11 +61,12 @@ def __init__( rope_theta: float = 10000.0, attn_implementation: Literal["eager", "sdpa"] | None = None, chronos_config: Optional[dict[str, Any]] = None, + quantiles: list[float] = None, + device: Optional[torch.device] = None, + dtype: Optional[torch.dtype] = None, **kwargs, ): - """PyTorch module implementing the Chronos-2 model, ported from - `amazon-science/chronos-forecasting `_ and - adapted for Darts :class:`PLForecastingModule` interface. + """Core Chronos-2 model containing all the modules and forward logic. Parameters ---------- @@ -95,12 +92,12 @@ def __init__( Attention implementation to use. If None, defaults to "sdpa". chronos_config Configuration parameters for Chronos-2 model. See :class:`_Chronos2ForecastingConfig` for details. + quantiles + List of quantiles for probabilistic forecasting. **kwargs - all parameters required for :class:`darts.models.forecasting.pl_forecasting_module.PLForecastingModule` - base class. + Additional keyword arguments. """ - - super().__init__(**kwargs) + super().__init__() self.d_model = d_model self.d_kv = d_kv self.d_ff = d_ff @@ -114,6 +111,8 @@ def __init__( act_info = self.feed_forward_proj.split("-") self.dense_act_fn = act_info[-1] self.is_gated_act = act_info[0] == "gated" + self.device = device or torch.device("cpu") + self.dtype = dtype or torch.float32 if self.is_gated_act: raise_log( @@ -187,19 +186,11 @@ def __init__( num_layers=self.num_layers, ) - quantiles = self.chronos_config.quantiles + quantiles = quantiles or self.chronos_config.quantiles self.num_quantiles = len(quantiles) quantiles_tensor = torch.tensor(quantiles) self.register_buffer("quantiles", quantiles_tensor, persistent=False) - # gather indices of user-specified quantiles - user_quantiles: list[float] = ( - self.likelihood.quantiles - if isinstance(self.likelihood, QuantileRegression) - else [0.5] - ) - self.user_quantile_indices = [quantiles.index(q) for q in user_quantiles] - self.output_patch_embedding = _ResidualBlock( in_dim=self.d_model, h_dim=self.d_ff, @@ -334,14 +325,14 @@ def _prepare_patched_future( return patched_future, patched_future_covariates_mask - def _forward( + def forward( self, context: torch.Tensor, group_ids: torch.Tensor, future_covariates: torch.Tensor, num_output_patches: int = 1, ) -> torch.Tensor: - """Original forward pass of the Chronos-2 model. + """Forward pass of the Chronos-2 model. Parameters ---------- @@ -454,6 +445,88 @@ def _forward( return quantile_preds + +class _Chronos2PLModule(FoundationPLModule): + def __init__( + self, + d_model: int = 512, + d_kv: int = 64, + d_ff: int = 2048, + num_layers: int = 6, + num_heads: int = 8, + dropout_rate: float = 0.1, + layer_norm_epsilon: float = 1e-6, + feed_forward_proj: str = "relu", + rope_theta: float = 10000.0, + attn_implementation: Literal["eager", "sdpa"] | None = None, + chronos_config: Optional[dict[str, Any]] = None, + **kwargs, + ): + """PyTorch Lightning module wrapper for the Chronos-2 model, adapted for + Darts :class:`PLForecastingModule` interface. + + Parameters + ---------- + d_model + Dimension of the model embeddings, also called "model size" in Transformer. + d_kv + Dimension of the key and value projections in multi-head attention. + d_ff + Dimension of the feed-forward network hidden layer. + num_layers + Number of Chronos-2 encoder layers. + num_heads + Number of attention heads in each encoder block. + dropout_rate + Dropout rate of the model. + layer_norm_epsilon + Epsilon value for layer normalization layers. + feed_forward_proj + Activation of feed-forward network. + rope_theta + Base period for Rotary Position Embeddings (RoPE). + attn_implementation + Attention implementation to use. If None, defaults to "sdpa". + chronos_config + Configuration parameters for Chronos-2 model. See :class:`_Chronos2ForecastingConfig` for details. + **kwargs + all parameters required for :class:`darts.models.forecasting.pl_forecasting_module.PLForecastingModule` + base class. + """ + + super().__init__(**kwargs) + + # Get quantiles for model initialization + chronos_config = chronos_config or {} + chronos_config_obj = _Chronos2ForecastingConfig(**chronos_config) + quantiles = chronos_config_obj.quantiles + + # gather indices of user-specified quantiles + user_quantiles: list[float] = ( + self.likelihood.quantiles + if isinstance(self.likelihood, QuantileRegression) + else [0.5] + ) + self.user_quantile_indices = [quantiles.index(q) for q in user_quantiles] + + # Create the core Chronos-2 model + self.model = _Chronos2Module( + d_model=d_model, + d_kv=d_kv, + d_ff=d_ff, + num_layers=num_layers, + num_heads=num_heads, + dropout_rate=dropout_rate, + layer_norm_epsilon=layer_norm_epsilon, + feed_forward_proj=feed_forward_proj, + rope_theta=rope_theta, + attn_implementation=attn_implementation, + chronos_config=chronos_config, + quantiles=quantiles, + device=self.device, + dtype=self.dtype, + ) + # TODO: fine-tuning support w/ normalized loss # Currently, Darts own `RINorm` is not used as Chronos-2 has its own implementation. Major differences # 1. Chronos-2 `RINorm` normalizes both target and covariates, while Darts normalizes target only. @@ -508,16 +581,16 @@ def forward(self, x_in: PLModuleInput, *args, **kwargs) -> Any: # determine minimum number of patches to cover future_length num_output_patches = math.ceil( - future_length / self.chronos_config.output_patch_size + future_length / self.model.chronos_config.output_patch_size ) - # call original Chronos-2 forward pass + # call the core model's forward pass # Unlike the original, we remove `context_mask`, `future_covariates_mask`, `future_target`, # `future_target_mask`, and `output_attentions` parameters. They are not needed for Darts' # implementation. # We also remove `einops` rearrange operation at the end so the raw output tensor is returned, # in shape of `(batch, vars * patches * quantiles * patch_size)` - quantile_preds = self._forward( + quantile_preds = self.model.forward( context=context, group_ids=group_ids, future_covariates=future_covariates, @@ -532,15 +605,15 @@ def forward(self, x_in: PLModuleInput, *args, **kwargs) -> Any: batch_size, n_variables, num_output_patches, - self.num_quantiles, - self.chronos_config.output_patch_size, + self.model.num_quantiles, + self.model.chronos_config.output_patch_size, ) # permute and reshape to (batch, time, vars, quantiles) quantile_preds = quantile_preds.permute(0, 2, 4, 1, 3).reshape( batch_size, - num_output_patches * self.chronos_config.output_patch_size, + num_output_patches * self.model.chronos_config.output_patch_size, n_variables, - self.num_quantiles, + self.model.num_quantiles, ) # truncate to output_chunk_length @@ -558,7 +631,7 @@ def forward(self, x_in: PLModuleInput, *args, **kwargs) -> Any: class Chronos2Model(FoundationModel): # Fine-tuning is turned off for now pending proper fine-tuning support # and configuration. - _allows_finetuning = False + _allows_finetuning = True def __init__( self, @@ -881,11 +954,14 @@ def encode_year(idx): ) self.hf_connector = hf_connector - super().__init__(enable_finetuning=False, **kwargs) + super().__init__(**kwargs) - def _create_model(self, train_sample: TorchTrainingSample) -> PLForecastingModule: + def _create_model(self, train_sample: TorchTrainingSample) -> FoundationPLModule: pl_module_params = self.pl_module_params or {} - return self.hf_connector.load_model( - module_class=_Chronos2Module, + model = self.hf_connector.load_model( + module_class=_Chronos2PLModule, pl_module_params=pl_module_params, ) + model.apply_peft(self.peft_config) + + return model diff --git a/darts/models/forecasting/foundation_model.py b/darts/models/forecasting/foundation_model.py index 4c92b7e992..9508fc5f3e 100644 --- a/darts/models/forecasting/foundation_model.py +++ b/darts/models/forecasting/foundation_model.py @@ -10,11 +10,14 @@ """ from abc import ABC +from typing import Optional + +from peft import PeftConfig, get_peft_model +from torch import nn from darts.logging import get_logger, raise_log -from darts.models.forecasting.torch_forecasting_model import ( - MixedCovariatesTorchModel, -) +from darts.models.forecasting.pl_forecasting_module import PLForecastingModule +from darts.models.forecasting.torch_forecasting_model import MixedCovariatesTorchModel logger = get_logger(__name__) @@ -24,7 +27,7 @@ class FoundationModel(MixedCovariatesTorchModel, ABC): def __init__( self, - enable_finetuning: bool = False, + peft_config: Optional[PeftConfig] = None, **kwargs, ): """Foundation Forecasting Model with PyTorch Lightning backend. @@ -161,6 +164,8 @@ def encode_year(idx): # initialize `TorchForecastingModel` base class super().__init__(**self._extract_torch_model_params(**self.model_params)) + enable_finetuning = peft_config is not None + # extract pytorch lightning module kwargs self.pl_module_params = self._extract_pl_module_params(**self.model_params) @@ -174,8 +179,27 @@ def encode_year(idx): logger, ) - self._enable_finetuning = enable_finetuning + self.peft_config = peft_config @property def _requires_training(self) -> bool: - return self._enable_finetuning + return self.peft_config is not None + + +class FoundationPLModule(PLForecastingModule): + def __init__(self, **kwargs): + super().__init__(**kwargs) + self.model: nn.Module + + def apply_peft(self, peft_config: PeftConfig) -> None: + """Apply PEFT to the underlying model. + + Parameters + ---------- + peft_config + The PEFT configuration to apply. + """ + if not peft_config: + return + self.model = get_peft_model(self.model, peft_config) + self.model.print_trainable_parameters() diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb new file mode 100644 index 0000000000..13aa7c467a --- /dev/null +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -0,0 +1,276 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "da55dd6c", + "metadata": {}, + "source": [ + "# Chronos-2 Foundation Model\n", + "In this notebook, we will show how to use Chronos-2 in Darts. If you are new to Darts, please check out the [Quickstart Guide](https://unit8co.github.io/darts/quickstart/00-quickstart.html) before proceeding.\n", + "\n", + "Chronos-2 is a time series foundation model for zero-shot forecasting. That means that it can be used for forecasting **without any training or fine-tuning** since it has already been pre-trained on large-scale time series data. Chronos-2 supports multivariate time series forecasting with [covariates](https://unit8co.github.io/darts/userguide/covariates.html) (exogenous variables) and can produce probabilistic forecasts.\n", + "\n", + "Check out the [Amazon Science Blog](https://www.amazon.science/blog/introducing-chronos-2-from-univariate-to-universal-forecasting) and the [original paper](https://arxiv.org/abs/2510.15821) for technical details." + ] + }, + { + "cell_type": "markdown", + "id": "9ad51937", + "metadata": {}, + "source": [ + "
\n", + " Fine-tuning Chronos-2 on your own data is not yet supported in Darts, but may be added in the future.\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "310fa52a", + "metadata": {}, + "outputs": [], + "source": [ + "# fix python path if working locally\n", + "from utils import fix_pythonpath_if_working_locally\n", + "\n", + "fix_pythonpath_if_working_locally()\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "bfa59f65", + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d510b54b", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n", + "The StatsForecast module could not be imported. To enable support for the AutoARIMA, AutoETS and Croston models, please consider installing it.\n", + "The `XGBoost` module could not be imported. To enable XGBoost support in Darts, follow the detailed instructions in the installation guide: https://github.com/unit8co/darts/blob/master/INSTALL.md\n", + "The `XGBoost` module could not be imported. To enable XGBoost support in Darts, follow the detailed instructions in the installation guide: https://github.com/unit8co/darts/blob/master/INSTALL.md\n" + ] + } + ], + "source": [ + "import warnings\n", + "\n", + "import numpy as np\n", + "\n", + "from darts.datasets import ElectricityConsumptionZurichDataset\n", + "from darts.models import Chronos2Model\n", + "\n", + "warnings.filterwarnings(\"ignore\")\n", + "import logging\n", + "\n", + "logging.disable(logging.CRITICAL)" + ] + }, + { + "cell_type": "markdown", + "id": "6b82a07a", + "metadata": {}, + "source": [ + "## Data Preparation" + ] + }, + { + "cell_type": "markdown", + "id": "70d7e392", + "metadata": {}, + "source": [ + "Here, we will use the [Electricity Consumption Zurich Dataset](https://unit8co.github.io/darts/generated_api/darts.datasets.html#darts.datasets.ElectricityConsumptionZurichDataset), which records the electricity consumption of households & SMEs (`\"Value_NE5\"` column) and business & services (`\"Value_NE7\"`) in Zurich, Switzerland, along with weather covariates such as temperature (`\"T [°C]\"`) and humidity (`\"Hr [%Hr]\"`).\n", + "Values are recorded every 15 minutes between January 2015 and August 2022.\n", + "\n", + "
\n", + "\n", + "Train-Test Split\n", + "\n", + "Even though Chronos-2 is pre-trained already, we still need to split the data into training and test sets. That is because `Chronos2Model` follows the Darts unified interface and will require calling the `fit()` method before forecasting. However, no training or fine-tuning will be performed during the `fit()` call.\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "Data Scaling\n", + "\n", + "Unlike other deep learning models in Darts, Chronos-2 does not require data scaling since it has its own internal data normalization mechanism. Therefore, we will skip the scaling step in this notebook.\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "2f87bcc5", + "metadata": {}, + "outputs": [], + "source": [ + "# convert to float32 as Chronos-2 works with float32 input\n", + "data = ElectricityConsumptionZurichDataset().load().astype(np.float32)\n", + "# extract households energy consumption\n", + "ts_energy = data[\"Value_NE5\"]\n", + "# extract temperature, solar irradiation and rain duration\n", + "ts_weather = data[[\"T [°C]\", \"StrGlo [W/m2]\", \"RainDur [min]\"]]\n", + "# split into train and validation sets by last 7 days\n", + "train_energy, val_energy = ts_energy.split_before(len(ts_energy) - 7 * 24 * 4)" + ] + }, + { + "cell_type": "markdown", + "id": "a3887f37", + "metadata": {}, + "source": [ + "Let's quickly visualize the last 7 days of the electricity consumption data." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3b43a60a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "val_energy.plot(label=\"consumption\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "147c7e36", + "metadata": {}, + "outputs": [], + "source": [ + "from peft import LoraConfig" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "60b4811d", + "metadata": {}, + "outputs": [], + "source": [ + "peft_config = LoraConfig(\n", + " r=8,\n", + " lora_alpha=32,\n", + " target_modules=[\"q\", \"v\"], # optionally indicate target modules\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "3cccd20e", + "metadata": {}, + "outputs": [], + "source": [ + "# use last 30 days of data to predict next 7 days\n", + "model = Chronos2Model(\n", + " input_chunk_length=30 * 24 * 4,\n", + " output_chunk_length=7 * 24 * 4,\n", + " peft_config=peft_config,\n", + " pl_trainer_kwargs={\"accelerator\": \"gpu\"},\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "08715193", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "trainable params: 589,824 || all params: 120,067,488 || trainable%: 0.4912\n" + ] + }, + { + "ename": "MisconfigurationException", + "evalue": "No supported gpu backend found!", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mMisconfigurationException\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[10]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2\u001b[39m \u001b[43m \u001b[49m\u001b[43mseries\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrain_energy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\utils\\torch.py:94\u001b[39m, in \u001b[36mrandom_method..decorator\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 92\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m fork_rng():\n\u001b[32m 93\u001b[39m manual_seed(random_instance.randint(\u001b[32m0\u001b[39m, high=MAX_TORCH_SEED_VALUE))\n\u001b[32m---> \u001b[39m\u001b[32m94\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdecorated\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:958\u001b[39m, in \u001b[36mTorchForecastingModel.fit\u001b[39m\u001b[34m(self, series, past_covariates, future_covariates, val_series, val_past_covariates, val_future_covariates, trainer, verbose, epochs, max_samples_per_ts, dataloader_kwargs, sample_weight, val_sample_weight, stride, load_best)\u001b[39m\n\u001b[32m 951\u001b[39m \u001b[38;5;66;03m# call super fit only if user is actually fitting the model\u001b[39;00m\n\u001b[32m 952\u001b[39m \u001b[38;5;28msuper\u001b[39m().fit(\n\u001b[32m 953\u001b[39m series=seq2series(series),\n\u001b[32m 954\u001b[39m past_covariates=seq2series(past_covariates),\n\u001b[32m 955\u001b[39m future_covariates=seq2series(future_covariates),\n\u001b[32m 956\u001b[39m verbose=verbose,\n\u001b[32m 957\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m958\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfit_from_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\utils\\torch.py:94\u001b[39m, in \u001b[36mrandom_method..decorator\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 92\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m fork_rng():\n\u001b[32m 93\u001b[39m manual_seed(random_instance.randint(\u001b[32m0\u001b[39m, high=MAX_TORCH_SEED_VALUE))\n\u001b[32m---> \u001b[39m\u001b[32m94\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdecorated\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:1150\u001b[39m, in \u001b[36mTorchForecastingModel.fit_from_dataset\u001b[39m\u001b[34m(self, train_dataset, val_dataset, trainer, verbose, epochs, dataloader_kwargs, load_best)\u001b[39m\n\u001b[32m 1091\u001b[39m \u001b[38;5;129m@random_method\u001b[39m\n\u001b[32m 1092\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mfit_from_dataset\u001b[39m(\n\u001b[32m 1093\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 1100\u001b[39m load_best: \u001b[38;5;28mbool\u001b[39m = \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[32m 1101\u001b[39m ) -> \u001b[33m\"\u001b[39m\u001b[33mTorchForecastingModel\u001b[39m\u001b[33m\"\u001b[39m:\n\u001b[32m 1102\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 1103\u001b[39m \u001b[33;03m Train the model with a specific :class:`darts.utils.data.TorchTrainingDataset` instance.\u001b[39;00m\n\u001b[32m 1104\u001b[39m \u001b[33;03m These datasets implement a PyTorch ``Dataset``, and specify how the target and covariates are sliced\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1147\u001b[39m \u001b[33;03m Fitted model.\u001b[39;00m\n\u001b[32m 1148\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m 1149\u001b[39m \u001b[38;5;28mself\u001b[39m._train(\n\u001b[32m-> \u001b[39m\u001b[32m1150\u001b[39m *\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_setup_for_train\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 1151\u001b[39m \u001b[43m \u001b[49m\u001b[43mtrain_dataset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrain_dataset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1152\u001b[39m \u001b[43m \u001b[49m\u001b[43mval_dataset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mval_dataset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1153\u001b[39m \u001b[43m \u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1154\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1155\u001b[39m \u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mepochs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1156\u001b[39m \u001b[43m \u001b[49m\u001b[43mdataloader_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdataloader_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1157\u001b[39m \u001b[43m \u001b[49m\u001b[43mload_best\u001b[49m\u001b[43m=\u001b[49m\u001b[43mload_best\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1158\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1159\u001b[39m )\n\u001b[32m 1160\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:1309\u001b[39m, in \u001b[36mTorchForecastingModel._setup_for_train\u001b[39m\u001b[34m(self, train_dataset, val_dataset, trainer, verbose, epochs, dataloader_kwargs, load_best)\u001b[39m\n\u001b[32m 1306\u001b[39m train_num_epochs = epochs \u001b[38;5;28;01mif\u001b[39;00m epochs > \u001b[32m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m.n_epochs\n\u001b[32m 1308\u001b[39m \u001b[38;5;66;03m# setup trainer\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m1309\u001b[39m trainer = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_setup_trainer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_num_epochs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1311\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m model.epochs_trained > \u001b[32m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m.load_ckpt_path:\n\u001b[32m 1312\u001b[39m logger.warning(\n\u001b[32m 1313\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAttempting to retrain/fine-tune the model without resuming from a checkpoint. This is currently \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1314\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mdiscouraged. Consider model `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m.\u001b[34m__class__\u001b[39m.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.load_weights()` to load the weights for \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1315\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mfine-tuning.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1316\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:525\u001b[39m, in \u001b[36mTorchForecastingModel._setup_trainer\u001b[39m\u001b[34m(self, trainer, model, verbose, epochs)\u001b[39m\n\u001b[32m 520\u001b[39m trainer_params[\u001b[33m\"\u001b[39m\u001b[33menable_model_summary\u001b[39m\u001b[33m\"\u001b[39m] = (\n\u001b[32m 521\u001b[39m verbose \u001b[38;5;28;01mif\u001b[39;00m model.epochs_trained == \u001b[32m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m 522\u001b[39m )\n\u001b[32m 523\u001b[39m trainer_params[\u001b[33m\"\u001b[39m\u001b[33menable_progress_bar\u001b[39m\u001b[33m\"\u001b[39m] = verbose\n\u001b[32m--> \u001b[39m\u001b[32m525\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_init_trainer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer_params\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrainer_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_epochs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mepochs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:538\u001b[39m, in \u001b[36mTorchForecastingModel._init_trainer\u001b[39m\u001b[34m(trainer_params, max_epochs)\u001b[39m\n\u001b[32m 536\u001b[39m \u001b[38;5;66;03m# prevent lightning from adding callbacks to the callbacks list in `self.trainer_params`\u001b[39;00m\n\u001b[32m 537\u001b[39m callbacks = trainer_params_copy.pop(\u001b[33m\"\u001b[39m\u001b[33mcallbacks\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m--> \u001b[39m\u001b[32m538\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpl\u001b[49m\u001b[43m.\u001b[49m\u001b[43mTrainer\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 539\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43m[\u001b[49m\u001b[43mcb\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcb\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 540\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mtrainer_params_copy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 541\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\utilities\\argparse.py:70\u001b[39m, in \u001b[36m_defaults_from_env_vars..insert_env_defaults\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 67\u001b[39m kwargs = \u001b[38;5;28mdict\u001b[39m(\u001b[38;5;28mlist\u001b[39m(env_variables.items()) + \u001b[38;5;28mlist\u001b[39m(kwargs.items()))\n\u001b[32m 69\u001b[39m \u001b[38;5;66;03m# all args were already moved to kwargs\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m70\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:404\u001b[39m, in \u001b[36mTrainer.__init__\u001b[39m\u001b[34m(self, accelerator, strategy, devices, num_nodes, precision, logger, callbacks, fast_dev_run, max_epochs, min_epochs, max_steps, min_steps, max_time, limit_train_batches, limit_val_batches, limit_test_batches, limit_predict_batches, overfit_batches, val_check_interval, check_val_every_n_epoch, num_sanity_val_steps, log_every_n_steps, enable_checkpointing, enable_progress_bar, enable_model_summary, accumulate_grad_batches, gradient_clip_val, gradient_clip_algorithm, deterministic, benchmark, inference_mode, use_distributed_sampler, profiler, detect_anomaly, barebones, plugins, sync_batchnorm, reload_dataloaders_every_n_epochs, default_root_dir, model_registry)\u001b[39m\n\u001b[32m 401\u001b[39m \u001b[38;5;66;03m# init connectors\u001b[39;00m\n\u001b[32m 402\u001b[39m \u001b[38;5;28mself\u001b[39m._data_connector = _DataConnector(\u001b[38;5;28mself\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m404\u001b[39m \u001b[38;5;28mself\u001b[39m._accelerator_connector = \u001b[43m_AcceleratorConnector\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 405\u001b[39m \u001b[43m \u001b[49m\u001b[43mdevices\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdevices\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 406\u001b[39m \u001b[43m \u001b[49m\u001b[43maccelerator\u001b[49m\u001b[43m=\u001b[49m\u001b[43maccelerator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 407\u001b[39m \u001b[43m \u001b[49m\u001b[43mstrategy\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstrategy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 408\u001b[39m \u001b[43m \u001b[49m\u001b[43mnum_nodes\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_nodes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 409\u001b[39m \u001b[43m \u001b[49m\u001b[43msync_batchnorm\u001b[49m\u001b[43m=\u001b[49m\u001b[43msync_batchnorm\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 410\u001b[39m \u001b[43m \u001b[49m\u001b[43mbenchmark\u001b[49m\u001b[43m=\u001b[49m\u001b[43mbenchmark\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 411\u001b[39m \u001b[43m \u001b[49m\u001b[43muse_distributed_sampler\u001b[49m\u001b[43m=\u001b[49m\u001b[43muse_distributed_sampler\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 412\u001b[39m \u001b[43m \u001b[49m\u001b[43mdeterministic\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdeterministic\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 413\u001b[39m \u001b[43m \u001b[49m\u001b[43mprecision\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprecision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 414\u001b[39m \u001b[43m \u001b[49m\u001b[43mplugins\u001b[49m\u001b[43m=\u001b[49m\u001b[43mplugins\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 415\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 416\u001b[39m \u001b[38;5;28mself\u001b[39m._logger_connector = _LoggerConnector(\u001b[38;5;28mself\u001b[39m)\n\u001b[32m 417\u001b[39m \u001b[38;5;28mself\u001b[39m._callback_connector = _CallbackConnector(\u001b[38;5;28mself\u001b[39m)\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\trainer\\connectors\\accelerator_connector.py:144\u001b[39m, in \u001b[36m_AcceleratorConnector.__init__\u001b[39m\u001b[34m(self, devices, num_nodes, accelerator, strategy, plugins, precision, sync_batchnorm, benchmark, use_distributed_sampler, deterministic)\u001b[39m\n\u001b[32m 142\u001b[39m \u001b[38;5;28mself\u001b[39m._accelerator_flag = \u001b[38;5;28mself\u001b[39m._choose_auto_accelerator()\n\u001b[32m 143\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._accelerator_flag == \u001b[33m\"\u001b[39m\u001b[33mgpu\u001b[39m\u001b[33m\"\u001b[39m:\n\u001b[32m--> \u001b[39m\u001b[32m144\u001b[39m \u001b[38;5;28mself\u001b[39m._accelerator_flag = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_choose_gpu_accelerator_backend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 146\u001b[39m \u001b[38;5;28mself\u001b[39m._check_device_config_and_set_final_flags(devices=devices, num_nodes=num_nodes)\n\u001b[32m 147\u001b[39m \u001b[38;5;28mself\u001b[39m._set_parallel_devices_and_init_accelerator()\n", + "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\trainer\\connectors\\accelerator_connector.py:354\u001b[39m, in \u001b[36m_AcceleratorConnector._choose_gpu_accelerator_backend\u001b[39m\u001b[34m()\u001b[39m\n\u001b[32m 352\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m CUDAAccelerator.is_available():\n\u001b[32m 353\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mcuda\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m--> \u001b[39m\u001b[32m354\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m MisconfigurationException(\u001b[33m\"\u001b[39m\u001b[33mNo supported gpu backend found!\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[31mMisconfigurationException\u001b[39m: No supported gpu backend found!" + ] + } + ], + "source": [ + "model.fit(\n", + " series=train_energy,\n", + " verbose=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e189768a", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "darts", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 76158c942817249bb8cce38f466b096d5260eb2e Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 19 Dec 2025 09:37:55 +0100 Subject: [PATCH 02/11] fix: properly set the model device and dtype --- darts/models/forecasting/chronos2_model.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/darts/models/forecasting/chronos2_model.py b/darts/models/forecasting/chronos2_model.py index 54228c1d3a..f0a9cec9cb 100644 --- a/darts/models/forecasting/chronos2_model.py +++ b/darts/models/forecasting/chronos2_model.py @@ -62,8 +62,6 @@ def __init__( attn_implementation: Literal["eager", "sdpa"] | None = None, chronos_config: Optional[dict[str, Any]] = None, quantiles: list[float] = None, - device: Optional[torch.device] = None, - dtype: Optional[torch.dtype] = None, **kwargs, ): """Core Chronos-2 model containing all the modules and forward logic. @@ -111,8 +109,6 @@ def __init__( act_info = self.feed_forward_proj.split("-") self.dense_act_fn = act_info[-1] self.is_gated_act = act_info[0] == "gated" - self.device = device or torch.device("cpu") - self.dtype = dtype or torch.float32 if self.is_gated_act: raise_log( @@ -199,6 +195,14 @@ def __init__( dropout_p=self.dropout_rate, ) + @property + def device(self) -> torch.device: + return next(self.parameters()).device + + @property + def dtype(self) -> torch.dtype: + return next(self.parameters()).dtype + def _prepare_patched_context( self, context: torch.Tensor, @@ -523,8 +527,6 @@ def __init__( attn_implementation=attn_implementation, chronos_config=chronos_config, quantiles=quantiles, - device=self.device, - dtype=self.dtype, ) # TODO: fine-tuning support w/ normalized loss From 94a71b4df570d130ce7e2356e715699b355f893d Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Thu, 15 Jan 2026 14:08:39 +0100 Subject: [PATCH 03/11] fix: remove peft as a darts dependency --- darts/models/forecasting/chronos2_model.py | 1 - darts/models/forecasting/foundation_model.py | 23 +- .../26-Chronos-2-finetuning-examples.ipynb | 7958 ++++++++++++++++- 3 files changed, 7894 insertions(+), 88 deletions(-) diff --git a/darts/models/forecasting/chronos2_model.py b/darts/models/forecasting/chronos2_model.py index f0a9cec9cb..04630f0ffe 100644 --- a/darts/models/forecasting/chronos2_model.py +++ b/darts/models/forecasting/chronos2_model.py @@ -964,6 +964,5 @@ def _create_model(self, train_sample: TorchTrainingSample) -> FoundationPLModule module_class=_Chronos2PLModule, pl_module_params=pl_module_params, ) - model.apply_peft(self.peft_config) return model diff --git a/darts/models/forecasting/foundation_model.py b/darts/models/forecasting/foundation_model.py index 9508fc5f3e..01ddc1f4de 100644 --- a/darts/models/forecasting/foundation_model.py +++ b/darts/models/forecasting/foundation_model.py @@ -10,9 +10,7 @@ """ from abc import ABC -from typing import Optional -from peft import PeftConfig, get_peft_model from torch import nn from darts.logging import get_logger, raise_log @@ -27,7 +25,7 @@ class FoundationModel(MixedCovariatesTorchModel, ABC): def __init__( self, - peft_config: Optional[PeftConfig] = None, + enable_finetuning: bool = False, **kwargs, ): """Foundation Forecasting Model with PyTorch Lightning backend. @@ -164,8 +162,6 @@ def encode_year(idx): # initialize `TorchForecastingModel` base class super().__init__(**self._extract_torch_model_params(**self.model_params)) - enable_finetuning = peft_config is not None - # extract pytorch lightning module kwargs self.pl_module_params = self._extract_pl_module_params(**self.model_params) @@ -179,27 +175,14 @@ def encode_year(idx): logger, ) - self.peft_config = peft_config + self._enable_finetuning = enable_finetuning @property def _requires_training(self) -> bool: - return self.peft_config is not None + return self._enable_finetuning class FoundationPLModule(PLForecastingModule): def __init__(self, **kwargs): super().__init__(**kwargs) self.model: nn.Module - - def apply_peft(self, peft_config: PeftConfig) -> None: - """Apply PEFT to the underlying model. - - Parameters - ---------- - peft_config - The PEFT configuration to apply. - """ - if not peft_config: - return - self.model = get_peft_model(self.model, peft_config) - self.model.print_trainable_parameters() diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index 13aa7c467a..79d0bd8481 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 23, "id": "310fa52a", "metadata": {}, "outputs": [], @@ -39,10 +39,19 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 24, "id": "bfa59f65", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The autoreload extension is already loaded. To reload it, use:\n", + " %reload_ext autoreload\n" + ] + } + ], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", @@ -54,25 +63,13 @@ "execution_count": null, "id": "d510b54b", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "c:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from .autonotebook import tqdm as notebook_tqdm\n", - "The StatsForecast module could not be imported. To enable support for the AutoARIMA, AutoETS and Croston models, please consider installing it.\n", - "The `XGBoost` module could not be imported. To enable XGBoost support in Darts, follow the detailed instructions in the installation guide: https://github.com/unit8co/darts/blob/master/INSTALL.md\n", - "The `XGBoost` module could not be imported. To enable XGBoost support in Darts, follow the detailed instructions in the installation guide: https://github.com/unit8co/darts/blob/master/INSTALL.md\n" - ] - } - ], + "outputs": [], "source": [ "import warnings\n", "\n", "import numpy as np\n", "\n", - "from darts.datasets import ElectricityConsumptionZurichDataset\n", + "from darts.datasets import AirPassengersDataset\n", "from darts.models import Chronos2Model\n", "\n", "warnings.filterwarnings(\"ignore\")\n", @@ -116,19 +113,114 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 26, "id": "2f87bcc5", "metadata": {}, "outputs": [], "source": [ "# convert to float32 as Chronos-2 works with float32 input\n", - "data = ElectricityConsumptionZurichDataset().load().astype(np.float32)\n", + "data = AirPassengersDataset().load().astype(np.float32)\n", "# extract households energy consumption\n", - "ts_energy = data[\"Value_NE5\"]\n", - "# extract temperature, solar irradiation and rain duration\n", - "ts_weather = data[[\"T [°C]\", \"StrGlo [W/m2]\", \"RainDur [min]\"]]\n", - "# split into train and validation sets by last 7 days\n", - "train_energy, val_energy = ts_energy.split_before(len(ts_energy) - 7 * 24 * 4)" + "# ts_energy = data[\"Value_NE5\"]\n", + "# # extract temperature, solar irradiation and rain duration\n", + "# ts_weather = data[[\"T [°C]\", \"StrGlo [W/m2]\", \"RainDur [min]\"]]\n", + "# # split into train and validation sets by last 7 days\n", + "train_passengers, val_passengers = data.split_before(len(data) - 2 * 12)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "a84830af", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "

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#Passengers
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shape: (24, 1, 1), freq: MS, size: 96.00 B

" + ], + "text/plain": [ + " #Passengers\n", + "Month \n", + "1959-01-01 360.0\n", + "1959-02-01 342.0\n", + "1959-03-01 406.0\n", + "1959-04-01 396.0\n", + "1959-05-01 420.0\n", + "... ...\n", + "1960-08-01 606.0\n", + "1960-09-01 508.0\n", + "1960-10-01 461.0\n", + "1960-11-01 390.0\n", + "1960-12-01 432.0\n", + "\n", + "shape: (24, 1, 1), freq: MS, size: 96.00 B" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "val_passengers" ] }, { @@ -141,13 +233,23 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 28, "id": "3b43a60a", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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r6tSpdZvBSGQwGCEiIludP39e1q1bZ63wnj59elv3B4EI1qkxjdguXLhg6/74AYMRIiKy1apVq7QVvBOmaOJO1Vy/ft0KlCh8GIwQEZGtnJQvYjBvJLIYjBARka2WL19ubVetWlWcgMFIZDEYISIiR4yMpEmTRipWrChOwGAkshiMEBGRbU6ePCmbN2/W7dtuu00DEifImTOn3HLLLbrNtvDhx2CEiIhss2LFCsfli8QdHTl16pTs3r3b7t3xNAYjRERkGycmrxqcqokcBiNERGQbBiMEDEaIiMj2YCRjxoxSunRpcRIGI5HDYISIiGxx6NAh2bNnj25XqVJFW8E7ScmSJSVdunS6vXr1art3x9MYjBARke39RZw2RQOpUqWSChUq6PbWrVvl3Llzdu+SZzEYISIi2/NFnNLsLKGpGpT2rlmzxu7d8SwGI0REZAsnJ68azBuJDAYjREQUcRhpMMFIjhw5pGjRouJEDEYig8EIERFFHJqIHTlyxJqiSZEihThRpUqVrG0GI+HDYISIiCLODVM0kDVrVilcuLBVUXP9+nW7d8mTGIwQEVHEuSUYCZyqOXv2rOzYscPu3fEkBiNERBRxbgxGgFM14cFghIiIIgpTHWaBvPz580u+fPnEyRiMhB+DESIiiqgtW7bI6dOnHd1fJBCTWMOPwQgREUWUm6ZooHjx4pIhQwbdZjASHgxGiIgootwWjKRMmVIqVqyo2zt37pRTp07ZvUuew2CEiIgiyg1t4G+UN8JF80KPwQgREUXMlStXZNWqVdb0R/bs2cUNmMQaXgxGiIgoYtatWycXL150zRSNwWAkvBiMEBFRxLgtX8QwOSPAYCT0GIwQEVHEuDUYyZQpk04rwdq1a+XatWt275KnMBgh364YOnHiRKlTp448/fTT+j0Rhd/y5cutCpXbb79d3MRM1Vy4cEF7pVDoMBgh38HaEi1btpQ2bdrIggULZODAgbJy5Uq7d4vI85ArsmbNGt0uW7asZMyYUdyEFTXhw2CEfOPSpUvyzjvvSPny5eWXX36JdZtpTU1E4fPXX3/J1atXXTdFYzCJNXxShfFnEznG7Nmz5bHHHpNNmzZZ1+GsDKtwmoMkEYWXW/NFDAYj4cOREfK0gwcPSpcuXaRhw4ZWIIK56meeeUbWr19v3Y/BCFH4uT0YKVy4sGTJkkW3GYyEFoMR8iRkug8aNEjKlCkjo0ePtq6vUaOGTsl88sknUrBgQSlatKg1/4uVRIko/MFI6tSpYy0+5xYpUqSw9nvv3r1y/Phxu3fJMxiMkCez9RF0PPHEE9YaEtmyZZOvv/5aFi1aJLfddpt1X7N97tw52bZtm237TOR1WKXXjE5iuiNt2rTiRpyqCQ8GI+QZJ0+e1ACkWrVqVvkgdO/eXQ+CvXv31imaQIGBCadqiMIHI5KmhN6NUzQGg5HwYDBCrocDHKZiMCWDqRlzwEPVzPz582XEiBGSK1eueB/LYIQoMgJPEBiMULKrafr06aPd56KiovR7NK1Bn4YpU6bIW2+9JWnSpLHuO378eMmbN6+1HsGAAQNkz549+iHRv39/yZcvX1KfniiWjRs3apXMnDlzrOsyZMggb7zxhjYzw9z0jTAYIYoMN67UG58KFSroCCtyzBiM2Fza27dvX2nevPk/rq9SpYoMHjz4H9dfvnxZXnzxRR0mb9asmQwdOlT69eunX4mCcf78eXn77bflgw8+0FVADTQy+/TTTzU5NTFwP+STnDhxgsEIUQSCkfTp02vDM7eKjo6WUqVK6YkQTrJx/LnZSQ85pM8I5grxz2rdurV+36tXLy213Ldvn+TPnz/e4AWXQPiHs9qBYOrUqTrqsXPnTuu6IkWK6AhdixYt9PukvFYwOoKRlf3792spcO7cucOy35R85v/KY4G7HDlyxHq/Vq5c2RpZcCssmodgBJ9TGzZs0NESSljcXL2QBSMff/yxXhAdPvvss1KyZEm9Hm1+EWRkz55dOnToIG3bttXrt2/fbt0H0qVLJwUKFNDr4wtGMMc/ZMiQWNe1a9dO2rdvH8zukkcgeMVU34wZM6zrEORi6hBTNThj2bVrV5J/LgIZAz/7rrvuCtk+U3hgupfcY+7cudY2PjeCeZ86SaFChaztWbNm6SJ6lDDTQiGkwchTTz0lxYoV00hn7Nix+v2ECRM02sX3yBFBM6nnn39eh78RnGBRIczjB8L3GGqPT48ePaRz586xrsNZK4bUExNhkfcgQMVrLfA1U79+ffn88881cTU5EHzg5wNGRtDYiJwJZ9MIRHgscJfdu3db2w0aNHD9e6xu3bry0UcfWZ9Nbv99nCDJwUjgcFS3bt1k8uTJOiKCvg6B9+nYsaMOfSMYwRkr+jgEwveYO4wPkmADE2HNGTAOPjwA+Q/Ooh555BFrTYs8efLogaBTp07ahCi5EEgbSEjja8z5eCxwbyVN9erVXf+/C1xtGA0T3f77OEGy/4IJ/RPwIWFKLDGSsnXr1lgrN6J7Ha4nuhkEtSYQQYIq5moxchaKQASQTGcS0JjEShRa+BwwyasYLS9evLi4HdILkI4ArKixIRg5c+aMLF26VJN2kFCK3g7oqoeRkMWLF2tFAuDDAlM2derUsapssGLqpEmT9LHDhw/XD4D48kWI4lqwYIG1jcTVrFmzhvTnYxQO5ebmtYtpRSIKXa7XoUOHrJLeUJ1E2Am/g+k3gt/N/H4UoWAEZ6doKtWoUSNp2rSpfkigjBKrn/7xxx+aYHrnnXfKq6++Kl27dtX7mIM9SjC///57nedftWqVJiISJcbChQv1K0Yv0F01HEy/EeQkoI8OEYWG2xfHSwibn9mYM4Ihtm+//Tbe21BVg0tCcOb5ww8/JH0PyddwxrF582brrAr5R+EQ2PwMBxYvHTSJ7OSVZmc3C0aaNGli6/64HbNuyNGwsJ0RzpJbdmIlCg8/jIwgiZWSh8EIuSZfJJzBSOCBhcEIUeiSV00lDdo+eClPsFy5cpIq1f8mFzhNk3wMRsgV+SJQq1atsD0PkmJN8zMcWNzcHZLIKVBFidW0zaiIF5JXjbRp01o9jtCFFUUaFDwGI+RYZ8+e1WRnQMWWKaUL91QNnhfdgYkoebw6RRN3RBXFHQhIKHgMRsixlixZIteuXdNtVGmFG/NGiELLL8EIcKomeRiMkCumaCKxXgyDEaLQ8moljcFgJHQYjJArklcjMTLCJFai0MHUhZlmxUJpOXPmFK9hMBI6DEbIkdDhF91+zQqZgatkhgsWu8qSJYtuMxghSh7kUJiFLb04KmLWycLFBCNmCRRKOgYj5EgrV6602rJHYlQEkOlvpmrQwvrIkSMReV4iL/J6vkjc0ZFjx47pCr4UHAYj5EiRzhdJqBMrEQXHb8EI8JgRPAYj5EiRzhcxmMRKFNpgBCOOWCzVqxiMhAaDEXIczLuakRGsh4ROh5HCYIQo+dDozLx/sEJ7pkyZxKsqVapkbTMYCR6DEXKcjRs36vwr1K5dW1KmjNzLFIEPVgcGBiNEwZk5c6bVI6hx48biZejCipXpgcFI8BiMkOPYlS8COKiYkRgERRcvXozo8xN5wfTp063tZs2aiZfh5MUcM7DCuEm8p6RhMEK+XRzvZlM1OLNbt25dxJ+fyO3TrL/++qtuR0dHS926dcXrTN4I1rRau3at3bvjSgxGyLEjI+nSpbMl8Y15I0TBW716tVXiWr9+fX0fex2TWJOPwQg5Cvp77NixQ7erV69uzcVGEoMRouD5aYrGYDCSfAxGyFHsKukNxLbwRMFjMMJgJBgMRshR7ExeNVBOjNbw5sCCeWAiurlTp07JokWLdLtkyZJSvHhx8YMcOXJI/vz5rWkqtoVPOgYj5MiREZTz1qxZ0/YznTNnzljTRkSU+JJev4yKxD1mICDbvXu33bvjOgxGyFGNktasWWO9sTNnzmzbvjBvhCjp/DhFY3CqJnkYjJBjLF682BretCtfxGAwQhR8SS8qaPxQ0huIwUjyMBghx3BCvojBYIQoaTCqiWo4U9KLHiN+wmAkeRiMkGM4oZLGKFKkiDVNxGCE6Ob8PEVjEnZNAMZgJOkYjJAjoO36n3/+qdvIwM+XL5+t+4OVRs3oyN69e+Xo0aO27g+R0/k9GImKipIKFSro9rZt2+Ts2bN275KrMBghR1i+fLlcvnzZEaMi8U3V8EyHKGGnT5+2SnpLlCihFz8yUzXInzHJ+JQ4DEbIEZyUL2IwGCFKfEnv1atXfTsqYjBvJHgMRsgR7F4cLz5MYiVKHL9P0RgMRoLHYIRshw6nZog3d+7cmgjmBFgWPFWqVLrNYIQofpiSMMEISnrr1asnflWpUiVrm8FI0jAYIdthyW10LTT5IkgedYK0adNqQAIbNmzQJFsiSrikF4GI30p6A2XJkkUr8UxbeC4lkXgMRsh2TirpTWiqBvPh69evt3t3iByHUzTxT9WcO3dOtm/fbvfuuAaDEbKdE5NXDeaNEN0Yg5HYOFUTHAYjZPt8sxkZyZAhQ6wPfydgMEKUuJJe9AdySr6XnZjEGhwGI2SrXbt2WfPNWKXXJIw68cDCYIQoNpb0/hODkeAwGCFbOTlfBLJnzy4FCxa0ghEmpBH9f5yi+adixYpJxowZdZvBSOIxGCFbOTlfJO5UzZkzZ2Tnzp127w6R40p6UXnm55LeQClTppSKFStaI78nT560e5dcgcEIOWJkBNMz1atXFydi3ghR/CX5gSW96dOnt3uXHDlVgxJfujkGI2QbLD6H/h1QuXJlTWB1IgYjRP/EKZqEMRhJOgYjZBuThe/UfBGDwQjRPzEYSRiTWJOOwQjZxg35IoCOipkzZ9ZtHliI/lfSa96/SNhkSW9syBkxnaR5zEgcBiPkiEqa2rVri5MT0syZzu7du+X48eN27xKRrWbNmhWrpNcpSzg4Bapp0HfF5NZcu3bN7l1yPAYjZIvz58/LihUrdLtMmTKSK1cucbLAqRqe6ZDfcYrm5swJzIULF2TLli12747jMRghW/zxxx/WmZWTp2gM5o0QxV/SW79+fbt3yZGYN5I0DEbIFk5vdhYXgxGi/1m3bp3s3btXt+vWrcuS3kQEI4sXL7Z1X9yAwQjZwi3Jq0a5cuWsVvUMRsjPOEWTODiupUmTRre///57uXz5st275GgMRijiMD2zZMkS3b7lllu0WsXp0qVLJ2XLltXt9evXy6VLl+zeJSLbg5HmzZvbui9Oli1bNmnTpo1uHzlyRH755Re7d8nRGIxQxGH+9OzZs9bZg1sy8c2wK4IpBCREfoMlEVjSm3g9e/a0tocPH27rvjgdgxGKOLflixjMGyG/Q0nvlStXdJslvTfXsGFDa6HNadOmyf79++3eJcdiMEIR57Z8EYPBCPkd80WSJioqSrp166bbWPH722+/tXuXHIvBCEW8LNCMjKCraYUKFcSN2fEMRshvWNIbnO7du8eaqsHfkUIQjPTp00dq1aqlZ7S4PPXUU9ZtI0eOlEaNGkmDBg3k008/jfVHRzlYx44dtdMmfsaBAweS+tTkAVu3bpXDhw/rNl4LOHNwi5w5c0qBAgWsYIQHFfIT5Ent2bNHt1nSm3joxIpVjWHz5s0s8w3lyEjfvn317BaXgQMHWkPv48eP14Bk3Lhx+gefNGmS3oaSphdffFGDkdmzZ+sZZr9+/YJ5anI5t+aLxJ2qwdocO3futHt3iCKGUzTBYyLrzf2vcUIIIDkHZUzmzLFLly4yZcoUad26tbb9Tp06tW5Dr169NLFn3759kj9//n/8LAQvcWuykTSFOTfy1no0bvufIpCeOnWqbq9cuVIKFy5s9y75inm9uO1147VgpGnTpvwfJAE+GzNlyqTVSDhZ/+STT3T9Gr9ImTJleIKRjz/+WC+lSpWSZ599Vsu7duzYoS9Qo0SJErJt2zbd3r59e6wSMPRsQNCC6+MLRkaMGCFDhgyJdV27du2kffv2wewuOcicOXP0K5oB5cmTR3bt2iVugr4oxvz586Vy5cq27o9fmekCigyU4psTCVSHIGfEbe9du91zzz3a/Ax/y6+++kratm0rflG0aNHQByPIEUF9OSKdsWPH6vcTJkzQhc8yZMhg3Q/bWCAI8DXwNnM7HhOfHj16SOfOnWNdh5IovAkSE2GRMx08eNA6gN1xxx0azLpN48aNrW1M03BkJLJwNo5AhMeCyMKUuynpxYeqGxoVOs2TTz6pwQhg1uC5556ze5ccJcnBSGD1A0qWJk+eLGvWrNFkpnPnzlm3YTs6Olq38TXwNnN7QglQOGs2bXQNTPPg4MMDkHsFJm4h+dmN/0sko5nhVjRvc+Pv4AU8FkTWb7/9FqvrKv/2SVejRg1dVgKJwBhlQjK/G0/IwiXZryjzosQwDP64BqZocOAGjKQE3nbx4kVdaAnXk3+4PXnVvN5NiS9GeU6cOGH3LhFFrKQXJ4ks6Q0OGsQFJrKi2IOCDEZwNrh06VJNLsWQ3ejRo7WqAKMliJZ/+uknDTKOHTumt5l1C6pUqaJreWCoD49FNjHW+YgvX4S83+wMb0qUh7tVYPMzLg1OXrdhwwbZvXu3VdIbd8qdEg+FHaadwahRo3RpCQoiGMEfbtCgQdpLBMmqONNFPxFkBeNMFwk5mLrBVwxJtWrVyoqmP/jgA50vQ1S9atUqGTBgQFKemlwOQatpFIbgFYtIuRU7sZKfsKQ3dJC0j5wbkwc5Y8YMu3fJnTkj+AC5UTtbJJ7iEp/y5cvLDz/8kPQ9JE/AiJopBXRTC/j4sBMr+QmDkdDCVI3pwYVZAq58/D/MQqKI8EK+SGBgbYZaGYyQX0p6UUFTunRpu3fJ9RDQYYQEUABy9OhRu3fJERiMUES4dXG8+KA6rEyZMrqNzPi4DfqIvAIds83rm6v0hgYqQ7t27arbJveSGIxQBOBghmkaQF8O06XXzUzeCA4mCEiIvIhTNOERmM4wbNgwrnPFYIQiAW3TUc7thVERg0ms5LeSXiyASqGBatKaNWvqNvp0rVy5UvyOwQiFnZfyRQwGI+R1GzdutDom16lThyW9IcbF82JjMEJh56V8EYMVNeR1WPzU4BRN6GGtNdOlfMyYMdbyKX7FYITCCuW8JhjJkSOHDk96Qa5cuaymfWh8xjlf8hrmi4RX5syZdQFYOHnypEycOFH8jMEIhX2o9/jx47pdu3ZtT2Xjm6kaHEhMh0oir5X0IuncVI9RaHGq5v9jMEIRyxfxyhSNwbwR8iqW9EYGcnHMGm6zZs3SlcD9isEIRSxfxCvJqwaDEfIqTtFEBoI8U+YbExOj69X4FYMRisjICBK1KleuLF7CYIS8iCW9kYX13FL838jTiBEjrGUz/IbBCIXNnj17rNLA6tWr64HNS4oVK6aLRAKDEfJiSS+mVs1rnMIDTSCbNm2q2/i7z507V/yIwQiFjRdLegOlTJnSKvHFXC8SWYncjlM0kdeTiawMRih8vNjs7Eb9RlDiS+R2DEYi795775Xs2bPr9o8//ujLExsGIxT2kRGMIJjWx17DvBHyWknv/PnzdbtQoUKe6QvkdGnTppXOnTvrNpbO+OGHH8RvGIxQWJw4cULWrl1rfWBnypRJvIjBCHnJnDlzWNJrk54+n6phMEJhsXjxYqsrqRfzRYwKFSroyA8wGCG34xSNvSc2t99+u24vW7ZMF9DzEwYjFBZ+yBcxJcumO+W6deuss0oiN5f0pk6dmiW9No+OjBgxQvyEwQiFhdcraeKbqrly5Yps2LDB7t0hCsqmTZusDqB4z3p1atXJOnXqZLVA+Pbbb311csNghEIOCVgYZoSSJUtKnjx5xMuYN0JewCka+2XPnl3atGmj20ePHpWpU6eKXzAYoZBDIGIiei9P0cQXjLC8l9yKwYgz9PTpVA2DEQo5Ly+Od7NeIxwZITc6d+6czJs3T7cLFiwo5cqVs3uXfKthw4b6P4Bp06bJ/v37xQ8YjFDIeXlxvPjkzp1bbrnlFisYMVVERG7Bkl7niIqK0vVqAOvUIHfEDxiMUEhdu3ZNFi1apNvIFSlRooT4gZmqQX8VrMlD5CaconGW7t27x+o54ocTHAYjFFKojT99+rQ1KuKXMywmsZJXSnoxTUD2Kl68uNSrV0+3N2/erH2bvI7BCIWUn0p6AzEYIbfCh92OHTusEwiW9DpDT591ZGUwQiEVuPy1H/JFDCaxkltzRVq3bm19zyka57j//vutwHDs2LG6bpCXMRihkGbkm+HeHDlyxPqA9sOwaoYMGXSbwQg53aFDh+TBBx/ULqsbN27U6zJnziwdOnSwe9fo/6RPn14eeOAB69g6fvx48TIGIxQykydPlvPnz+t227ZtJVWqVOKnDPhKlSrpNoa8/bgEOLkjwXzw4MFSunRp+e6776zrq1evrqW9WKmXnKOnj6ZqGIxQyAQue92xY0fxm8C8kdWrV9u6L0RxrVixQmrWrCmPP/64nDp1Sq/Lli2bfPXVV5ogGfj6JWeoVq2a1fMF+XjI7/EqBiMUEihpNVM06Lnhp+RVg0ms5EQIPJ588kn9YDPLNAB6WWCKpk+fPtbK0+QsKVKkkB49eljfjxw5UryKr0AKiZ9//lkXioP27dvrtIXfMBghp5XsjhkzRqdkPv/8c22gBTjTxpQMPtjQsI+c7cEHH7SOp6NGjZKrV6+KFzEYoZBP0ZikK7+pUKGCdYbJYITsXoG3cePG0rlzZ01WNQmR7733nr4269SpY/cuUiLlyZNH7rnnHt1Ga/gZM2aIFzEYoWTDwW7WrFm6XaxYMbnjjjvEj3Cwx1korFu3zhopIoqUCxcuSN++faVixYrWexJQvrthwwZ58cUXtbEZuUtPHySyMhihZJswYYI1BIzEVb90Xb3RVA3W+TAlk0SRgEXVypcvL2+//bYVCBcpUkSmTJmi06islHGvZs2a6QiJqVo8cuSIeA2DEUq277//3tdVNIGYN0KRhrWQ7rvvPmnRooXVSRWjH6+++qqO0JkhfnKv1KlTS9euXXUbgebo0aPFaxiMULLs3r3bWhgPiXHIm/AzBiMUKfhQ+vDDD6Vs2bI68mHUr19f/v77bx0hwdQheUOPgKoaLy6ex2CEkgVtigMTV/08RRM3GPnjjz9s3RfyLpwAVK5cWV544QXtzgmojEEjM+SKIEAhbylbtqz2iTELkqJvjJcwGKFk8Xujs7jwgWCSWNFIylQyEIXC0aNHNZkR6z6tXbtWr8MJwGOPPaYVNKie8fsJgV9GR0aMGCFewmCEgoZugCtXrtTtqlWrSokSJezeJUfA/D1gGHXSpEl27w55BJKisax84IdQlSpVdARu0KBBkjVrVlv3j8KvQ4cOEh0drdvIG7l06ZJ4BYMRChpHRRJebdP46aefbN0X8lbVGhJSzaJ2aGSGQMSvpfR+lDlzZmnTpo3VWddLU8EMRigoOOsPrKLhap//H+byTRkl5u+5aB6FwsCBA61tjLhhjRk/djr2uyZNmljbc+bMEa9gMEJBwUJwpo8G1qEpUKCA3bvkGJizN1M1aN08depUu3eJXO7PP/+0zoLR0Kxu3bp27xLZpH79+tY2gxHyPbZ/vzETjACnaii5PvvsM2v7qaeeYpKqjxUqVEg7XcOSJUu0664XMBihoKZoTDCCYeK2bdvavUuOU6tWLWsRsl9//dUqvyRKqoMHD1ol9NmyZZNOnTrZvUvkkNGRy5cva0DiBQxGKMkwXLxz507dbtSokeTKlcvuXXIcBGlYDwRw5vLbb7/ZvUvkUl9//bXV3r13795sZEaCqipj7ty54gUMRijJ2P496VU1P/74o637Qu6EM98vv/xSt7EiNPqJENX3YN4IgxFKkmvXrsm4ceN0O02aNNbZP8V/9mJ6PyCJ1Us9ASgyEMQeOHBAt1u1aiWFCxe2e5fIAfLnzy8lS5a0RqrPnz8vbsdghJJk3rx5OocNzZs3Z6OlG0Cw1rJlS90+ffq0zJ492+5dIpcnrhLFHR3BFJ5ZH8zNGIxQkrDRWdKwqoaCtXz5cis5EQtQspyXvDxVkzI5fSbQ+W/o0KH6/ZQpU6R69erac8JczBk0oHMgPrxq164tffr0sYYeyV3z1+gCCRkyZODS5IlsUGQSDidOnKjTXESJwXJeupHA4NQLSaxBBSPXr1+Xjz/+WJeMD4R1EhYsWGBd8ubNa32IvfjiixqMYKj61ltvlX79+oXmN6CI+f333+XEiRO6fe+992pAQjeGQKRZs2bWImcLFy60e5fIBQ4fPmyNQqKcFwvgEQXKly+flClTRreXLVsmZ8+eFTdLFcyDMNyMYcPE/vJY6jh16tRWsmOvXr2kYcOGsm/fPk3EiQvBCy6BMC+GIIjsM2bMmFjt3/n/SBy87k01Db5i1JCCY15zXn/tffXVV9YxEMfLdOnSef53puCS5NEJG52e58+fL3fffbc4ESrBQh6MYJ0NlHaOHDlSPvroo1i3rVmzRoOM7Nmz64eVaYa1fft2K/MX8MZC+3BcH18wglUphwwZEuu6du3aSfv27ZO6uxQi6JVhVqDFYk2lS5eWXbt22b1brlCpUiVNZjXTXE8//XSi3pyUsD179ohX4cQLi+ABXicYheR7jeKDQQEDx+eyZcuKExUtWjT0wcjgwYO1/XemTJn+sTgYugRiamb9+vXy/PPP6/AighN8kMUd0sf3CZUj9ejR4x/Dkvv375eCBQvyIG6T8ePHW11EEWSWKlXK7l1yFbwPpk+frrlSR44ckWrVqtm9S66E0QEEIl4+FmB6BtM0gGos5NkRJdTL6IknntDtVatWubr0O0nBCIaDEGi89NJL/7gtcIQD0RryQ5Dhi4NwdHT0P9ph4/uEOgniLBKXQJjmwcHHqwcgpzO9RQDBKP8PST9oIBgxiaw1atSwe5dczcvHgkGDBsVKXPXq70nJlzdvXilfvrwWiCAdAqkTGLl2oyS9yleuXKnDhegv0bRpU01o/Oabb6R///7/uC8yv7GGCWBRn61bt1q3Xbx4Ufbu3Wst9kPOhh4Zv/zyi27nyZMnVkkZJQ6G2s2HCvJGzHuDKBA+UBYvXqzb+JDhe41uxrxGMGqIwhG3SpnUngk///yzjB49Wi916tTRXI5//etf+gYylRYYQcGUDW43VTboPok5LcybDx8+XOe24ssXIefBmbzpHor/N9ZdoaTB+j3m/YDAHGcyRDcq533yySdZzku+6TeSpGAEiac5c+a0LmnTptUpGOSPoCUtEkzvvPNOefXVV6Vr1646egKYcvnggw808RV/OMxtDRgwIFy/E4Wx0RmmaCg4bIBGN4I8EbPuEzobd+nSxe5dIpf0G0nxf0Grm4ORFDEuGS/esWOHJudw/jSy0BsD9ewoHStUqJD+H/g/CA6mJpF4aSps/v77b7t3yXUwFI2pYi8eC95++23p27evbj/33HPy4Ycf2r1L5BK33XabHk8QlBw7dkyLR9zGW+9mCjnkNyAQAZRre+0DIJJQzo4uxaaDcWAeFfkbynlRqQj4QHn88cft3iVyWb8RwNiCW/NG+MlCN2SGjYFTNKGdqkH+FZF5LaB9gSnnTUxfBiIv5Y0wGKEEoUMuuvoB+opgKJCSp02bNtY280bIGDhwoLXN1XkpqZAc7/a8EQYjdMPeIialCKMizOxPPnQirlixom4vXbpUAz7yN7RMMEvAY72vBg0a2L1L5DLZsmWT22+/XbeRO4K8EbdhMEKJqqJBEzsK/VQNyqbJ31jOS6Geqpk3b564DYMRite2bdvkzz//1G1Mz5jVISn5WOJLBpYGMHlZWbJkkQcffNDuXSKXJ7HC3LlzxW0YjFC80LTO4KhIaGGapkSJEtYZDMqnyZ+wIKhpKIjVeeOu4UWUWFgN3FQ7ujFvhMEI3bSKBiW9FDoYhjejI9euXZPJkyfbvUtkUznvF198odss56Xkwsgaup3D2rVrddTNTRiM0D/ghYwL1KxZU4oUKWL3LnkOp2oI+UJohAf33HMP1+qikOaNuG2qhsEI3XCKhr1FwuOOO+6w1mbCgpNYjJD8m7jKcl7ye78RBiMUC0p5zRQN5h+xMB6FHv62pucIFo+cNm2a3btEEYT1uUynTCwa2rBhQ7t3iTygdu3a1kKmHBkh1y9hjkoak52dN29eu3fJszhV418s56VwyJQpk466woYNG+TgwYPiFgxGKBa2f49s9nuOHDl0GyMjFy5csHuXKAJQPTVmzBjdZjkvhVp9l+aNMBihWCuimnyR1KlTxzpzp9BLlSqVtG7dWrfPnTsnM2bMsHuXKMLlvD179pSMGTPavUvkIfUdlDdy+PBhadq0aaLuy2CELAsXLrTak+MFlD17drt3yfM4VeMvWAGbq/NSONWqVUtPJp0QjHz99deJPsliMEIWtn+PPCQuYp4X0G8EvSfIH+W8LVq0kOLFi9u9S+QxGTJkkGrVqun2li1bbFv/KrCPTmIwGCHrhTN+/Hjdjo6OllatWtm9S76QNm1a7TEBJ0+edNUcLyU/cZXIq3kjP/30k+zfvz/R92cwQmr27NlWW3J8OHIeO3I4VeMPWE11/vz5uo21nho3bmz3LpFH1XdA3sjAgQOTdH8GI6RYRWOfu+++W9KlS6fbP//8s7aIJ2+PijzxxBMs56WwqVmzpqRJk8a2YAQtIhYvXqzb5cuXT9RjGIyQXLx4UT8EIXPmzNKsWTO7d8lXMAplMs4PHTokS5YssXuXKMSOHTsmo0ePtt5jXbt2tXuXyMOio6M1IIHt27fL7t27Hd9dmMEIyfTp06125OgKas7SKXLuv/9+a5tTNd4zdOhQDfpNOa9JWiYKl3r16tmSN4JyXjPSnjVrVuncuXOiHsdghFhF4wDI00HfEROMoC0/eaecd9CgQbrNcl7yet7IkCFDdIkLeOihh7S6JzEYjPjc2bNnZcqUKbqdM2dOrpFhk2zZskmDBg10e9euXbp2CXkDSrb37Nmj282bN5cSJUrYvUvkAzVq1LBGuSMVjKAq0/TRwfpbSQm8GYz4HA6Upg1527ZtrWY5FHmsqvGmwKoClvNSJNsG1KpVyzrB2bFjR9ifE7mHppy3ZcuWUqRIkUQ/lsGIz3GKxjnQ28VUWDAY8YbVq1fLvHnzdLt06dIs5yVPT9UMDAi8E5u4ajAY8bHjx4/Lr7/+qtu33HKLLtxG9sEKyVgC3Ky4iQt5q5wXQ9dEXkxiXblypSxatMgq5w0MhBKD7wwfw5CaaT/eoUMHHigdgFU13irn/e6773Qb1TPdunWze5fIZ6pVqybp06e3RkbCmRgft7twUvvo8NPHx9jozHlQWm0wGHG3YcOGWeW8PXr0YDkvRVyaNGms0VasibRt27awPM+RI0dilfN26dIlyT+DwYhPIbvfzCFisa6qVavavUskIoULF5YqVapYw547d+60e5comeW8ZoqGyKt5I0OGDJFLly7pdq9evRJdzhuIwYhPD5QPPvigXL9+3RoVYWtqZ1bVmM645L4qNdP1Eh2NS5YsafcukU/VD3MwErg6Lz5HHnvssaB+DoMRH+rfv7+V4V+gQAF55pln7N4lCsASX3fD1MzLL78cdFUBUShhpNWMVCCJNdR5IxMnTtQpIFPOW6xYsaB+DoMRn/n999/l7bff1u2oqCgt7c2RI4fdu0UBsKJr2bJldRvZ6QcPHrR7lxwBq0ojIdTpf48BAwbIli1brMZTTZo0sXuXyMdSp05tVUoeOHBANm/eHNbE1WAxGPERNKPBOgEmMn7nnXes5CZy5ugI/lc48/C78ePHa4CGipQWLVpYjZWc5u+//5b333/f+hDAmjSsUiOvTtWsWrVKFixYoNt4fyangzffJT6BZekRiCDr2cxjP//883bvFiWAJb7/g9dr+/bt9YKREThx4oQmyTlt/R7kYmEtDnyFV199NdHLpxO5MRiJuzpvsnIPY1xi+/btMdeuXbN7N1zrtddew5FbL/nz5485cuSI3btEN3D9+vWYIkWK6P8rVapUMceOHYvxm/Hjx8fkypXLet3ikiZNGmt78ODBMU7y0UcfWftWrly5mIsXL9q9S0TqypUrMZkzZ9bXZu7cufX4klz4DEmbNq3+zCxZssScOXMmWT+PIyM+MHPmTJ3HDswTwaJ45Fw4wzBTNTjTnjp1qvhpNARN+Nq1a2eN5GXPnl3GjBkTq7oII3smN8Nu27dvl759+1r/O0zPYG0QIidIlSqVlTdy+PDhkHR3jlvOmzFjxmT9PAYjHoeEpcA8kbfeekvuvPNOu3eLEsGPVTU//vijTm2MGzcuViO49evXawn63XffLZ06ddLrz58/ryXqZlrELnhvPfzww9aCk1iptGbNmrbuE1E4p2rwnjOr8yL4TsrqvAmKcQlO0yTd1atXY+rXr28NHd999938G7oI/ld58+bV/126dOmSPQzqZBjy7dChQ6wpmezZs8eMHj061pAy/iZr166NKVGihHW/AQMG2LrvI0eOtPalYMGCMadPn7Z1f4jis2LFCut1ev/998ckdwrV/KyWLVvGhAKDEQ97/fXXY+WJHD582O5doiR65JFHrP/huHHjYrzoxx9/1HnswECkVatWMQcOHPjHfXEMwLFg0aJFMSlTprRyapYvX27Lvh88eDAmW7Zs1n5PnTrVlv0gSszJadasWfV1miNHjmR9ntapU8d6zc+YMSMmFDhN41GzZs2SN99808oTwboBuXLlsnu3KIm8XFWD6hhMveB3xDw2ZMuWTUaPHq25IVjFOCHo3/HKK6/E6ihspkki6emnn9bqHsDvgrJjIieKioqSunXrWos4rl27Nujy9fnz51vlvI0aNQrJ/jEY8SA0hQrME0HyqkleInfBwQMf0IAkVrPwmtsh2EBuCJKpjVatWmluCHJCElMi+Nprr8ntt9+u20jI+/e//y2RNGXKFBk7dqxuo3Hgp59+GtHnJ0qqevXqWdvoxprccl6suRSypURiXILTNIkfimvQoIE1hNa0aVP+3VyuW7dunpkGOHr0aMwDDzwQa0oG0xzfffddosoNzTSNeU2vW7fOKi/EZfbs2RH4LWJiTp06FVOgQAHreb/55puIPC9Rcvz111/Wa7Z169ZBvX+Rv4bHo1Q4lHlsHBnxGFTLzJ49W7dvueUW+fbbb9kB0uW8UlWD0ZBy5cpZS43DvffeK+vWrdORvGDOsPDz3n33Xet7dGg9deqUhBumiMx6HGj3HsyS6USRVrFiRWv5D6xPZhZLTSyUrJvR2Z49eya7nDeWGJfgyMjNzZo1KyZFihQatSK5b968eXbvEoXA+fPnYzJkyGAlnqGBkZvgbKpTp07/GA359ttvk9x8Ke7IiLkusGqsa9euMeG0cOFC67nSp08fs2PHjrA+H1Eo3Xfffdbrd+XKlYl+HI47qBbD4/A5s2XLlpDuF0+ZQ2zXrl2yZ88eW/JEMNcemCdSp06diO8HhV50dLQ0b97cSjwLxzLg4TJp0iTNDUHDMgMre2I0BKMJoZhvxsjfyJEjJXPmzPr9N998E7YRJDR5Qst3A4tOFilSJCzPReSkfiOTJ0+2PtuQqF2iRInQ7liMS7hhZGTZsmU6IoGosXv37jF79+6NWJ5Iw4YNrWi3SZMmjv9bUfB1/e3bt49x42gIygqRW5GcVtTxjYwYo0aNsp4LI0jxlQYnV79+/aznuOOOO/S9R+Qma9asCapHSN26da3H/fbbbyHfLwYjIfTEE0/EOvhGR0frwSvczarefPNN6znz5csXc+jQobA+H0XepUuXrHVaUqdO7ej/MfatUKFCsd4L99xzT8y+ffuS/bNvFIwgyAkcgm7RokVI1uAwVq9erT1NTG+Tv//+O2Q/myhS8J4wxxKsKZOYgBqvdfO+KlOmTEjfVwanaULo119/jfU9+h5gugTDWejjj5VzQw3DbG+88YY1XI3kwNy5c4f8echeadKkkR49euj2lStXZNSoUeJUKHHdvXu3bmfNmlX3FUO8SKgOJ0z5fPXVV5InTx79/pdfftGEu1DAe7d3795W6/mXX35ZKlWqFJKfTRRJeJ+YEl8ke69atcq+ct5AMS7h9JGRrVu3WpFjtWrVYp555hk9gw08O6xQoULM9OnTQ9r90bQLx+Wtt94K2c8m50HCmPlfox16OM5Okgsr1ZqzLowebNu2LaQ//0YjIwbKn83fCYm/eG8m16effmr9zNKlS8dcuHAh2T+TyC6DBw+2Xs/vv/9+ksp5w7XcAUdGQuS3336LtbDXJ598og2cAjtoouNds2bNpGnTprJ69epkn6khARCJq9C4cWOrIyV5E0bYGjZsqNtbt251ZCLrhAkTrJV2UZJcrFixiO8DkuswigHnzp3Tct/kjEoiKf3VV1+1vscoZ7p06UKyr0ROT2IdNmyYVc6L0dlMmTKFZ6eCjWIwh1S1atWYIUOGWNeNGDFCEylRZvff//431pkbFrfCQli1atWK6d27d8z+/fs9NTKCRKCEyqVQCli9evVYoyRIcu3Zs2fQ8+hYHIx5Iv4zduxY6/+O95PT1KxZ09q/cJSWJ2ZkBHD2VrRoUWtf3n333aCeD8cwNA40P+fRRx8Ncs+JnOP69evWqHrGjBkTbBeA603+VzjKeQMFFYzgQICukKjnN8HIggULYpo3bx6zZ88eXYETGf8///yzlXyH2/A9hnE///zzmF69enkmGMHvZPpA5MmTJ8Hkuh9++CGmSJEisYIS9CnAgnZJSXKdO3eutUgYvs6ZMyfEvxG5JZHVSYsfIggPnJIMxzRSYoMRc0wyfXfwt1q1alWSnw+dYQMXmzx58mSQe07kLB07drRe20uXLo33Pj/99JN1H3yGh1NQ0zSo4a9QoYIULVrUum7atGk6PVGgQAHJmTOnTiHgOlixYoWkTp1aWrduLWnTppVevXrpWhL79u2L9+dfvnxZzp49G+uCpD10i3PiZcGCBTocbLoxQtz7IPBr166d9ld4//33JUuWLHq/8+fPS//+/aVUqVI6/Huz3xPTMliQy3TOe/3117WfiN1/A14ic0mVKpVOOwBeK+ivYfc+mcvnn39uvYcfffRRfc2H43nie3/Fd6lVq5a88MIL1t8Ki+nh/ZbY5zl06JAuhGfg98MQtd1/Z154uR6Ci1k0D9C1O777DBw4MFbiarDPlRipJIlOnjypFRs4CH700UfW9Tt27NBciMD57W3btun29u3bpWTJktZtmG9F0ILr8+fP/4/nGDFihH4wB8IHefv27cWJxo8fb21XqVJF55hvpG3bttKgQQM9uH333XeaoX/gwAHp06eP/k0xPx3fwnb4p3bv3l3vC7Vr19ZGZzd7PvIW5B19+OGHuj148GDNSwpLdnsSICvfNDZDi2gEyOF8XSa2sSDmuFHJs3HjRs3ZeuaZZxKdW/Xss89qkzmTh3LrrbfyvUaeUapUKWt7+vTp0rFjx1i34z1jFtPDwAPuH+zrP3DgImTBCA5+ODOPm8SCM44MGTJY32PbLOmNr4G3mdvxmIQOIFirItD+/fulYMGCjlxnZcmSJfoVHwj422Bk6GYKFy6siUEoEcRl4sSJev2mTZv0zBcjLB988IGOQBnvvPOOLFy4ULexvDqCIFPGSP6B1w6CWZzN7Ny5U08EAhPS7ICEbZPkhoAZa8aEAwJyBCJJORZgZeBq1arpiCtKffEeDTwrjA8OzugeC1g1GSdHfK+RlxQqVEgHAzBDgdmLfPnyaQuBwM+bwMA8MQFFsiRlTmfDhg0xnTt3tpqkINfB5Ixg/gm5DMb69et19Vgz7/r888/H+lnIKZk/f77rc0bQZTWwpDdY+Fugo2NgPgnyQR566CFN9kUyYGCeSKRWJyVnQv6ReZ3gvWcnvC+LFy9u7Q+OE+F8rmCOBShfNPtXuHBhXXX3RsmvgU3bhg8fHoI9J3Kezp07W6/zRYsWWdcfO3ZMm3bi+kyZMoWtnDdQkoYZVq5cqcM0WCcDUzK///67rgOBnAdETSg3NDBFU7x4cd1GeV/gbTiDwoqXdpT9hbOk9+677w7652BaZunSpTrUjTNfcxaIMzlMcWEoPjBPxO4zYbIX8q/MCBxyuEw5rR1mzJhhTcmi9LhMmTLiNP/617+sqU8cwzBdk5C+fftaTdvw+2Ckh8hPJb7Dhg2zZjbCWs4bKCmRCxr9oFLGXF5++eWYgQMHatQUWE2DJik4WwuspmnWrFnMxIkTdXvQoEGeqabBCI+JLBcvXhySn4m/83vvvacNZgJHSnBB6TTXwyDAaKN5XXz44Ye27QdavZv9QPZ9OAU7MgJ4HMoYzb7ieBTXkiVLrAocnBmGomEakVNt27Yt1mcL4PMFo4fm+s2bN0dkX5LVgTVwmgYwnImpmXr16t2wz4iZenB7MIIabCyFbhYBC/XS7ijbxHo3UVFRVtlwOBb/InfatGmTdcAoVaqULR1Z8b40H95YXjzU74FQBiMwbNgw62+GEunA/jw4USpfvrx1+wcffBDCPSdynuvXr1tTkuiyijYVGEQw7wEMIkQK28EnA0ZCzD+tXbt2Yf3Q+eyzz3TUiSgQGgya16Ad/WZefPHFiC5HkNxgBAffe++919rnVq1aWUFc//79reurVKkS9sCKyAm6desWq1EhBhTM96FcvuRmnFea4tKF8ZKTL3IzKKlCjTfKoYkCoRzc+PrrryP63Mj9wtwyoI/QQw89JE6HijdUxuTKlUu/R8UM2hRg6Ya33npLr4uKitJcLfR0IfK6ev+3aB6g3QSq9AC5iqZvViQwGAlRMBLYY4UoUtBo0CSy/vjjj3L06NGIPffYsWOtPhzoA+SW0lesah3YxwiNzdCkEY3RAI3SbrvtNhv3kMieJNbAnllPPvlkRFtpMBgJEg76y5Yt0+2KFSvG27yNKNzQ0dhUe6CPxqhRoyL23IMGDbK2H3/8cXGTVq1aaZUAnDlzxlpGHWeDr732ms17RxQ5qN6M20MEjQtNp+dIYTASJJQ1I+cm3FM0RDdjVqg1UzXmdRlOCMRNMI5RhJo1a4rb/Pe//7XK6A2MmERHR9u2T0R2iNsqAoF65syZI7oPDEYcni9ClJicIjPvu3nzZpk/f37ER0XsbkcfDBxsMZJk9h35NzfrzErkh2DkiSeeiPg+MBgJApqPmWZnaGuPNWKI/JLIiilKtFiHrFmz6vpIboXgY968eZqwGhhgEfktGImKirLWvgpctyZSGIwEYfXq1bqiJ2CNEMzbE9npvvvukxw5cuj2hAkTrMTScBg+fLhcunTJGs5Nnz69uBk6s2IlcVbPkF/lz59fq8qQf/bVV1/Zsg8MRoLAKhryayLrtWvX5IsvvrC+f/TRR8PyPEQUWagoGzFihC5CaQcGI0Fgvgj5NZEVq9lipWATiKP6hIgouRiMJNHp06dl0aJFul2iRAlrMUAiu5UuXdpKwNy0aZMsWLAg5M/h5nJeInIuBiNJhO50V69e1W2OipDTPPzww2FLZMXK22ZUECWxWL2biCgUGIwkEadoyOkdWcOVyBo3V8Rk3xMRJReDkSTAHLwJRtKkSROrpz+RE6RLl87qnIiKl2+++SYkP/f8+fNaRWOSZVF9QkQUKgxGkgANpXbt2qXbderU0R4jRH5IZP3+++/l5MmTut2hQwdrPRwiolBgMJIEnKIhNyhTpoyVyLpx40ZZuHBhsn4eghkmrhJRODEYSQIGI+TGjqzJbWK0dOlSayG5qlWrSrVq1ZK9f0REgRiMJNKFCxdk7ty5Vre6cuXK2b1LRDfsyJo9e/aQJLJyVISIwo3BSCJh8bGLFy9aoyJuXBiM/JvI+u233wb1cw4fPizjx4/XbQQ3yBchIgo1BiOJxCkacvviecEksmIBObSXB1TQREdHh3QfiYiAwUgSgxH0VmjUqJHdu0OUqERWVH3Bhg0brM7BiYXmfl9++aVuYySQ69AQUbgwGEkElPOiKgFq1Kihy6YTeT2RderUqbJnzx7dRrfVokWLhnz/iIiAwUgi/Pbbb9Y2p2jITe6//34rkRW5H8ePH0/0Y5m4SkSRwmAkEZgvQn5LZMVCezNnztRtLAaJFXqJiMKFwchNXLlyxTooo+tk5cqV7d4lorB3ZB08eLC1jVyRlCl5qCCi8OER5iaWLFkiZ86c0W2cHfKgTG5TtmxZueuuu3R7/fr1N01kPXv2rIwcOdIaWenRo0dE9pOI/IufrEmYouFQNXmlzPdGRo8eLadPn9btTp06WTknREThwmAkCcFIkyZNbN0XomC1bdtWsmXLptvjxo1LMJGV69AQkR0YjNzAwYMHrTU5kCuSJ08eu3eJKCSJrN99912898OiemvWrLHK2JkjRUSRwGDkBmbMmGFts4qGvJTIip4j8SWyclSEiOzAYOQG2F+EvASLO955551WIuvixYtj3X7gwAH58ccfdTtXrlzSrl07W/aTiPyHwUgCrl27ZgUjmTNn1iFrIrd7+OGHE0xkHTJkiLaAh4ceekjSpk0b8f0jIn9iMJKAlStXWsuuYy2a1KlT271LRCHpyBqYyHrixAmrn45pF4/y9UceecTW/SQif2EwkgB2XSUvwqq7Xbt21e2LFy9aiayTJk2S/fv363bLli2lUKFCtu4nEfkLg5EEsL8I+WXxPJbzEpHdGIzEA0PXS5cutbpX8iyRvJrIum7dOhk6dKjMnTtXvy9VqpQ0bNjQ5j0kIr9hMBIPrEVz/fp13eYUDXl9dCRwJOSxxx7jkgdEFHE86sSD+SLkh46sWbNmtZJXIX369FZjNCKiSGIwEgfmz00wgmS/OnXq2L1LRGFNZDW6dOliBShERJHEYCQOzKGbqoJ69eppG20ir0/VABNXicgurglG9u3bF5Hn4RQN+UX58uXlvvvu0218rVSpkt27REQ+5Zpg5IEHHpBdu3aF/XkYjJCfjB49WpYtWyZjxoyxe1eIyMdSxMS3WpYDpUiRQooUKaIliIULFw7Lc5w9e1Zy5Mghly9flqJFi8q2bdv0eYnIGVDlhpMSHANY9UPkHa56N+/cuVPq168fthESBDoIREyjMwYiRERE4eeaYAQjFbBjx46wBSScoiEiIoo81wQjmNNGd8jAgGT37t1hCUZSpUolDRo0COnPJiIiIpcHI3ny5JFZs2bFCkhQehuqgGTr1q2aIwJolZ0pU6aQ/FwiIiLySDACt9xyi8yZM0dKliwZ8oDkt99+s7Y5RUNERBQ5rgpGTECCRNPAgCQUUzbMFyEiIrKH64KR+AKS7du3a0CyZ8+eoH7epUuXZPbs2bqdN29eNn8iIiKKIFcGI/FN2SAgwZRNMAHJwoUL5fz589aoCEt6iYiIHByMvP3229qDo27dutKhQweZP3++Xj9lyhSpXr263HXXXdbl4MGDsdZ86dixo9SuXVvXxDhw4ECydz5//vwhCUg4RUNEROSiDqxoPIZRiTRp0miA8dhjj8mkSZNkwYIFMn36dBk8ePA/HoNGYm3atJHevXtLs2bNZOjQobJq1Sr9mljIDUmo6yLWrcE0zZYtW/T7YsWK6TROwYIFE/WzK1asKGvXrtURkSNHjmgXViJyHnZgJfKmVEl9AFqyG/jwvnr1qn6A38iKFSskderU0rp1a/2+V69e0rBhQw0iMLoRX/BiOqEaV65c0QNRfPLly6dlv+gNghJdk0OC624WkOzdu1cDEahWrZpky5YtwechInuZ9ybfo0TukZgThyQHI/Cf//xHp2WQ+IlplxIlSsjGjRtlzZo1GmRkz55dp3Datm2r90dwYKZSIF26dFKgQAG9Pr5gZMSIETJkyJBY17Vr107at29/w/365ptvrAX10DMEU0loloZgJSFjx461tjHNFInF+IgoeYJNVici+zqohzwYefnll+WFF17QEQ+zmFzlypX1gx3VKOvXr5fnn39eRxkQnFy4cEEyZMgQ62fge5M0GlePHj2kc+fOsa7bv3+/jnLcKMLC0C1yWPCcGCFBYNG1a1etlEHwEx/8DgYCqHAtwkdEyYcREQQiNzsWEJG7BBWMQFRUlE5rfP/993pgQNdSo0KFCpqsiuRSBAbR0dFy7ty5WI/H9+nTp4/3ZyMfBZdAmObBwedmB6BChQrp82KaxnRVxfQNckjiBiSYYpo5c6ZuI3DCyAgPcETOl5hjARG5R7LfzdeuXdO8i7gwWmJyY5FQisDAuHjxoj4G14cDgg4EJMWLF9fvEZAgOIm7n3/++aecPHlSt5s0aaIBFhERETk4GDl79qyWwWJ6xYwqLF++XG6//XZZvHixnDhxQu+H/BFM2dSpU0e/r1KliuaXoOoGianDhw+XsmXLxpsvEsqABKMhJiBBMISABEmzBkt6iYiIXFbai2Dkueeek02bNumoB6ZnevbsqdMgn3zyiUybNk3zQ3Lnzq3JppiqMVAGPGDAAJ3vLVeunLz55ps3TCxNSmnvjWA0BL1HzCJ4SLZFkIJACNNMy5Yts3JSkrI/RBR5LO0l8qYk9xmxS7DBCCAAwqhIYEAyYcIEHdHBr3/rrbfKX3/9FYa9JqJQYjBC5E2+eDdjBCcwhwRTNrVq1bJyWtBRloiIiOzhi2AkMCAxSbOBZcXMFyEiIrKPb4IRE5AgXySwigf9TtC4jYiIiOzhq2AkMCAxUzZoiha3pwkRERG5oOmZ2wMSrEeDpFV0jiUiIiL7+DIYMevj1KhRw+7dICIi8j3fTdMQERGRszAYISIiIlsxGCEiIiJbMRghIiIiWzEYISIiIlsxGCEiIiJbMRghIiIiWzEYISIiIlsxGCEiIiJbMRghIiIiWzEYISIiIlsxGCEiIiJbMRghIiIiWzEYISIiIluliImJibF3F4iIiMjPODJCREREtmIwQkRERLZiMEJERES2YjBCREREtmIwQkRERLZiMEJERES2YjBCREREtmIwQq61f/9+qV69ut27QUQ24nHAGxiMOMx9990nnTt3Fr9r2bKl/PXXX+I348ePl/vvv19q166tf4MhQ4bItWvXbviYKVOmyGOPPRaxfaTw43HA38cBPx4LUtm9A/T/rV27Vo4ePSqXL1+WHTt2SNGiRZP0eDTTxSVlSsaYbjRixAg9AL311ltSqVIl2b59u/Tt21eOHDkir776qt27RxHC4wCN8OGxwDGvVj9HwMb06dOlbt26OuQ4bdo06/qqVavKDz/8IC1atJCmTZvKN998Y932xhtvyHvvvSePPPKI3HnnnbJ3717xEvx+Q4cO9UTkfyNnz57V3/Oll16SypUrS6pUqaRUqVIyYMAAmThxouzatUtOnDgh//73v6Vx48bSsGFD+eyzz/T//e6778qKFSvkrrvukvbt24vb+f1YwOOAf48Dfj4WcGTEIa5evSq///67Rr9nzpyRL7/8Ut9sKVKk0NsXLlwoY8eO1TOmhx9+WMqUKSPVqlXT22bMmCGff/65lCxZ0ubfgoK1evVqfQ3ggyRQ6dKlJW/evLJ8+XKZPXu2buOAFBUVJZs3b5YCBQrIK6+8oh9ggwcPtm3/KTR4HKDVPj0WpHLiEOX777+v0V+mTJmkS5cu0rFjR73tq6++kj179siVK1dkyZIlOnz5zjvvSP78+cXtli5dqr9XzZo1dXgWv9eqVas0Mobu3btLxowZ9dKqVSs9YJmDUIMGDaRs2bI2/waUHCdPnpSsWbPqgSWu7Nmz6+0445kzZ45ER0fr9Ri+9TI/Hgt4HKCTPj0WOGaaxsCQFObE8IfGgeiLL76QjRs3Wrfj+nbt2mlkWLhwYfn666/FCxDN1qtXT1KnTi0ZMmSQWrVq6XUGomAjT548emYU+D25W5YsWfQgE1+C2vHjx/XAhAOROfj4gR+PBTwOUBafHgscF4xg2BEXJF+VK1dOM4n//vtv63acBWDuFAeqJk2ayJYtW8Ttzp8/L/PmzdODKuaCcfnjjz9k1qxZenYEBw8etO5/6NAhyZkzp/gB3nCXLl2yvj927Jh4Ec5s8JrGMHygTZs2yYEDB6RixYo6T3zx4sV/PNYM4XuN344FPA4kzC/HAT8fCxwXjGzbtk3nSBs1aqRJXDj7OXXqlHU7IkIjXbp0+gZ2Oxx8MmfOLD/++KOMHj1aLxMmTNAI2LwgkayGxKadO3fK5MmT9e/jB5j/XrRokf7uSNDC7+5FmIbo0aOHJiGuXLlS54zx4dqvXz+59957pUqVKjpU/9FHH+lrHgeiNWvW6GOzZcumH0x4jJf47VjA40DC/HIc8POxwHE5IxiOvf322+Xjjz/WAwyGaVGm5mUYhsX8b9yzHLzwzBAthms7dOig88mdOnXyTZOf5s2ba04AKgiKFCmiZ4uBZ8de8tBDD+mBCOV8OAPGhy0qS3r16qW343q8P3AdzoDatGmjZ0l33HGH3HLLLZpZj6F6VFx4gd+OBTwOJMxPxwG/HgscF4wg0kNyVtq0aTVxC9Ew5oO9bNCgQfFe/+STT+pXDEXXr1/fSt6LW/LmRXgdIIkLH0IffPBBvPfBmw7D2F6CDxpc4oOzHpTuxZUmTRot7fMavx0LeBz4J78eB/x4LHDcNA3eeGj2gmHZMWPGSJ06dezeJYowlK7hDDhfvnx27wrZiMcCf+NxwF9SOS0CxhDcpEmT4r0P6uoD4UwBddbkHW+//baWN2JIHmfE5D88FhCPA/6TIsYBk7CIgF988UWdF+ULj8i/eCwg8ifbR0YYARMR8FhA5F+OGBkhIiIi/3JcAisRERH5C4MRIiIi8lcwgo6CnTt31mY9WOzKwGwRvkdTG6zNgKYuaOxj9OnTRxv+YGlkXJ566inrNrQJRgMYNMLBcsoJ1esTkXMEeyyAUaNG6e0o90Xzr3Pnzlm3jRw5UjuTYuG4Tz/91NON0oi8IuLBCLoLIrDAgSLQlClTdA2GESNGyC+//KJrDwwZMiTWfbCs9oIFC/QycODAWAefrVu3ak8CXNAAh2V+RM4W7LFg3Lhx2o1z2LBhupZL//79dWE5QNt0HANwTMD9Fi9enGB5MBH5OBjBmQ6aGKHVbSAcRO677z7JnTu3rlbZrVs3mTp1aqJ+Jh6LMyys64C2uQ888IA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"text/plain": [ "
" ] @@ -157,7 +259,7579 @@ } ], "source": [ - "val_energy.plot(label=\"consumption\");" + "val_passengers.plot(label=\"passengers\")" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "3cccd20e", + "metadata": {}, + "outputs": [], + "source": [ + "# use last 30 days of data to predict next 7 days\n", + "model = Chronos2Model(\n", + " input_chunk_length=12,\n", + " output_chunk_length=6,\n", + " n_epochs=10,\n", + " pl_trainer_kwargs={\"accelerator\": \"mps\"},\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "08715193", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=12, output_chunk_length=6, n_epochs=10, pl_trainer_kwargs={'accelerator': 'mps'})" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.fit(\n", + " series=train_passengers,\n", + " verbose=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "f9c8b482", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "0be2b2c066ac4d7f958b8a4b10778d4c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pred = model.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + ")\n", + "val_passengers.plot(label=\"actual\")\n", + "pred.plot(label=\"forecast\");" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "c54a89eb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "OrderedDict([('shared.weight',\n", + " tensor([[-1.4855e-06, 6.6741e-07, -2.3774e-07, ..., 2.5759e-07,\n", + " 1.6342e-06, 2.2832e-06],\n", + " [-2.4927e-03, 3.1087e-03, 1.2331e-03, ..., -1.2153e-02,\n", + " -7.9643e-04, -9.8041e-03]])),\n", + " ('input_patch_embedding.hidden_layer.weight',\n", + " tensor([[-1.6344e-03, -1.7315e-03, -1.7230e-03, ..., -6.8476e-03,\n", + " -1.5899e-03, -7.6784e-03],\n", + " [ 1.5054e-04, 1.0679e-04, 2.0166e-04, ..., 3.2022e-03,\n", + " 3.9019e-03, 3.4222e-03],\n", + " [-8.2940e-04, -8.7882e-04, -8.5499e-04, ..., -3.6055e-03,\n", + " 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+ }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.model.model.state_dict()" ] }, { @@ -167,86 +7841,236 @@ "metadata": {}, "outputs": [], "source": [ - "from peft import LoraConfig" + "from peft import LoraConfig, PeftModel, get_peft_model" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 35, "id": "60b4811d", "metadata": {}, "outputs": [], "source": [ "peft_config = LoraConfig(\n", - " r=8,\n", + " r=32,\n", " lora_alpha=32,\n", - " target_modules=[\"q\", \"v\"], # optionally indicate target modules\n", + " target_modules=[\"v\"], # optionally indicate target modules\n", ")" ] }, { "cell_type": "code", - "execution_count": 9, - "id": "3cccd20e", + "execution_count": 36, + "id": "61beeeae", "metadata": {}, "outputs": [], "source": [ - "# use last 30 days of data to predict next 7 days\n", - "model = Chronos2Model(\n", - " input_chunk_length=30 * 24 * 4,\n", - " output_chunk_length=7 * 24 * 4,\n", - " peft_config=peft_config,\n", - " pl_trainer_kwargs={\"accelerator\": \"gpu\"},\n", + "model.model.model = get_peft_model(model.model.model, peft_config)\n", + "model._enable_finetuning = True" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "5f1a55b0", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "64afd717f77145f08f46ae765ae9cd00", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Training: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pred = model.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + ")\n", + "val_passengers.plot(label=\"actual\")\n", + "pred.plot(label=\"forecast\");" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "cc169bfa", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "trainable params: 589,824 || all params: 120,067,488 || trainable%: 0.4912\n" + "trainable params: 1,179,648 || all params: 120,657,312 || trainable%: 0.9777\n" ] - }, + } + ], + "source": [ + "model.model.model.print_trainable_parameters()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "f44f6966", + "metadata": {}, + "outputs": [], + "source": [ + "model.model.model.save_pretrained(\"chronos2-lora-passengers\")" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "a6a4328e", + "metadata": {}, + "outputs": [], + "source": [ + "# use last 30 days of data to predict next 7 days\n", + "model_loaded = Chronos2Model(\n", + " input_chunk_length=12,\n", + " output_chunk_length=6,\n", + " n_epochs=10,\n", + " pl_trainer_kwargs={\"accelerator\": \"mps\"},\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "7e7adc07", + "metadata": {}, + "outputs": [ { - "ename": "MisconfigurationException", - "evalue": "No supported gpu backend found!", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mMisconfigurationException\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[10]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2\u001b[39m \u001b[43m \u001b[49m\u001b[43mseries\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrain_energy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\utils\\torch.py:94\u001b[39m, in \u001b[36mrandom_method..decorator\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 92\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m fork_rng():\n\u001b[32m 93\u001b[39m manual_seed(random_instance.randint(\u001b[32m0\u001b[39m, high=MAX_TORCH_SEED_VALUE))\n\u001b[32m---> \u001b[39m\u001b[32m94\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdecorated\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:958\u001b[39m, in \u001b[36mTorchForecastingModel.fit\u001b[39m\u001b[34m(self, series, past_covariates, future_covariates, val_series, val_past_covariates, val_future_covariates, trainer, verbose, epochs, max_samples_per_ts, dataloader_kwargs, sample_weight, val_sample_weight, stride, load_best)\u001b[39m\n\u001b[32m 951\u001b[39m \u001b[38;5;66;03m# call super fit only if user is actually fitting the model\u001b[39;00m\n\u001b[32m 952\u001b[39m \u001b[38;5;28msuper\u001b[39m().fit(\n\u001b[32m 953\u001b[39m series=seq2series(series),\n\u001b[32m 954\u001b[39m past_covariates=seq2series(past_covariates),\n\u001b[32m 955\u001b[39m future_covariates=seq2series(future_covariates),\n\u001b[32m 956\u001b[39m verbose=verbose,\n\u001b[32m 957\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m958\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfit_from_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\utils\\torch.py:94\u001b[39m, in \u001b[36mrandom_method..decorator\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 92\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m fork_rng():\n\u001b[32m 93\u001b[39m manual_seed(random_instance.randint(\u001b[32m0\u001b[39m, high=MAX_TORCH_SEED_VALUE))\n\u001b[32m---> \u001b[39m\u001b[32m94\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdecorated\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:1150\u001b[39m, in \u001b[36mTorchForecastingModel.fit_from_dataset\u001b[39m\u001b[34m(self, train_dataset, val_dataset, trainer, verbose, epochs, dataloader_kwargs, load_best)\u001b[39m\n\u001b[32m 1091\u001b[39m \u001b[38;5;129m@random_method\u001b[39m\n\u001b[32m 1092\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mfit_from_dataset\u001b[39m(\n\u001b[32m 1093\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 1100\u001b[39m load_best: \u001b[38;5;28mbool\u001b[39m = \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[32m 1101\u001b[39m ) -> \u001b[33m\"\u001b[39m\u001b[33mTorchForecastingModel\u001b[39m\u001b[33m\"\u001b[39m:\n\u001b[32m 1102\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m 1103\u001b[39m \u001b[33;03m Train the model with a specific :class:`darts.utils.data.TorchTrainingDataset` instance.\u001b[39;00m\n\u001b[32m 1104\u001b[39m \u001b[33;03m These datasets implement a PyTorch ``Dataset``, and specify how the target and covariates are sliced\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 1147\u001b[39m \u001b[33;03m Fitted model.\u001b[39;00m\n\u001b[32m 1148\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m 1149\u001b[39m \u001b[38;5;28mself\u001b[39m._train(\n\u001b[32m-> \u001b[39m\u001b[32m1150\u001b[39m *\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_setup_for_train\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 1151\u001b[39m \u001b[43m \u001b[49m\u001b[43mtrain_dataset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrain_dataset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1152\u001b[39m \u001b[43m \u001b[49m\u001b[43mval_dataset\u001b[49m\u001b[43m=\u001b[49m\u001b[43mval_dataset\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1153\u001b[39m \u001b[43m \u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1154\u001b[39m \u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1155\u001b[39m \u001b[43m \u001b[49m\u001b[43mepochs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mepochs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1156\u001b[39m \u001b[43m \u001b[49m\u001b[43mdataloader_kwargs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdataloader_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1157\u001b[39m \u001b[43m \u001b[49m\u001b[43mload_best\u001b[49m\u001b[43m=\u001b[49m\u001b[43mload_best\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 1158\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1159\u001b[39m )\n\u001b[32m 1160\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:1309\u001b[39m, in \u001b[36mTorchForecastingModel._setup_for_train\u001b[39m\u001b[34m(self, train_dataset, val_dataset, trainer, verbose, epochs, dataloader_kwargs, load_best)\u001b[39m\n\u001b[32m 1306\u001b[39m train_num_epochs = epochs \u001b[38;5;28;01mif\u001b[39;00m epochs > \u001b[32m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m.n_epochs\n\u001b[32m 1308\u001b[39m \u001b[38;5;66;03m# setup trainer\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m1309\u001b[39m trainer = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_setup_trainer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverbose\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrain_num_epochs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1311\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m model.epochs_trained > \u001b[32m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m.load_ckpt_path:\n\u001b[32m 1312\u001b[39m logger.warning(\n\u001b[32m 1313\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mAttempting to retrain/fine-tune the model without resuming from a checkpoint. This is currently \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1314\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mdiscouraged. Consider model `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m.\u001b[34m__class__\u001b[39m.\u001b[34m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.load_weights()` to load the weights for \u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1315\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mfine-tuning.\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 1316\u001b[39m )\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:525\u001b[39m, in \u001b[36mTorchForecastingModel._setup_trainer\u001b[39m\u001b[34m(self, trainer, model, verbose, epochs)\u001b[39m\n\u001b[32m 520\u001b[39m trainer_params[\u001b[33m\"\u001b[39m\u001b[33menable_model_summary\u001b[39m\u001b[33m\"\u001b[39m] = (\n\u001b[32m 521\u001b[39m verbose \u001b[38;5;28;01mif\u001b[39;00m model.epochs_trained == \u001b[32m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m 522\u001b[39m )\n\u001b[32m 523\u001b[39m trainer_params[\u001b[33m\"\u001b[39m\u001b[33menable_progress_bar\u001b[39m\u001b[33m\"\u001b[39m] = verbose\n\u001b[32m--> \u001b[39m\u001b[32m525\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_init_trainer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrainer_params\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtrainer_params\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_epochs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mepochs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32md:\\Projects\\darts\\darts\\models\\forecasting\\torch_forecasting_model.py:538\u001b[39m, in \u001b[36mTorchForecastingModel._init_trainer\u001b[39m\u001b[34m(trainer_params, max_epochs)\u001b[39m\n\u001b[32m 536\u001b[39m \u001b[38;5;66;03m# prevent lightning from adding callbacks to the callbacks list in `self.trainer_params`\u001b[39;00m\n\u001b[32m 537\u001b[39m callbacks = trainer_params_copy.pop(\u001b[33m\"\u001b[39m\u001b[33mcallbacks\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m--> \u001b[39m\u001b[32m538\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpl\u001b[49m\u001b[43m.\u001b[49m\u001b[43mTrainer\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 539\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43m[\u001b[49m\u001b[43mcb\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcb\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 540\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mtrainer_params_copy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 541\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\utilities\\argparse.py:70\u001b[39m, in \u001b[36m_defaults_from_env_vars..insert_env_defaults\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m 67\u001b[39m kwargs = \u001b[38;5;28mdict\u001b[39m(\u001b[38;5;28mlist\u001b[39m(env_variables.items()) + \u001b[38;5;28mlist\u001b[39m(kwargs.items()))\n\u001b[32m 69\u001b[39m \u001b[38;5;66;03m# all args were already moved to kwargs\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m70\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\trainer\\trainer.py:404\u001b[39m, in \u001b[36mTrainer.__init__\u001b[39m\u001b[34m(self, accelerator, strategy, devices, num_nodes, precision, logger, callbacks, fast_dev_run, max_epochs, min_epochs, max_steps, min_steps, max_time, limit_train_batches, limit_val_batches, limit_test_batches, limit_predict_batches, overfit_batches, val_check_interval, check_val_every_n_epoch, num_sanity_val_steps, log_every_n_steps, enable_checkpointing, enable_progress_bar, enable_model_summary, accumulate_grad_batches, gradient_clip_val, gradient_clip_algorithm, deterministic, benchmark, inference_mode, use_distributed_sampler, profiler, detect_anomaly, barebones, plugins, sync_batchnorm, reload_dataloaders_every_n_epochs, default_root_dir, model_registry)\u001b[39m\n\u001b[32m 401\u001b[39m \u001b[38;5;66;03m# init connectors\u001b[39;00m\n\u001b[32m 402\u001b[39m \u001b[38;5;28mself\u001b[39m._data_connector = _DataConnector(\u001b[38;5;28mself\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m404\u001b[39m \u001b[38;5;28mself\u001b[39m._accelerator_connector = \u001b[43m_AcceleratorConnector\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 405\u001b[39m \u001b[43m \u001b[49m\u001b[43mdevices\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdevices\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 406\u001b[39m \u001b[43m \u001b[49m\u001b[43maccelerator\u001b[49m\u001b[43m=\u001b[49m\u001b[43maccelerator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 407\u001b[39m \u001b[43m \u001b[49m\u001b[43mstrategy\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstrategy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 408\u001b[39m \u001b[43m \u001b[49m\u001b[43mnum_nodes\u001b[49m\u001b[43m=\u001b[49m\u001b[43mnum_nodes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 409\u001b[39m \u001b[43m \u001b[49m\u001b[43msync_batchnorm\u001b[49m\u001b[43m=\u001b[49m\u001b[43msync_batchnorm\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 410\u001b[39m \u001b[43m \u001b[49m\u001b[43mbenchmark\u001b[49m\u001b[43m=\u001b[49m\u001b[43mbenchmark\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 411\u001b[39m \u001b[43m \u001b[49m\u001b[43muse_distributed_sampler\u001b[49m\u001b[43m=\u001b[49m\u001b[43muse_distributed_sampler\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 412\u001b[39m \u001b[43m \u001b[49m\u001b[43mdeterministic\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdeterministic\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 413\u001b[39m \u001b[43m \u001b[49m\u001b[43mprecision\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprecision\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 414\u001b[39m \u001b[43m \u001b[49m\u001b[43mplugins\u001b[49m\u001b[43m=\u001b[49m\u001b[43mplugins\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 415\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 416\u001b[39m \u001b[38;5;28mself\u001b[39m._logger_connector = _LoggerConnector(\u001b[38;5;28mself\u001b[39m)\n\u001b[32m 417\u001b[39m \u001b[38;5;28mself\u001b[39m._callback_connector = _CallbackConnector(\u001b[38;5;28mself\u001b[39m)\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\trainer\\connectors\\accelerator_connector.py:144\u001b[39m, in \u001b[36m_AcceleratorConnector.__init__\u001b[39m\u001b[34m(self, devices, num_nodes, accelerator, strategy, plugins, precision, sync_batchnorm, benchmark, use_distributed_sampler, deterministic)\u001b[39m\n\u001b[32m 142\u001b[39m \u001b[38;5;28mself\u001b[39m._accelerator_flag = \u001b[38;5;28mself\u001b[39m._choose_auto_accelerator()\n\u001b[32m 143\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._accelerator_flag == \u001b[33m\"\u001b[39m\u001b[33mgpu\u001b[39m\u001b[33m\"\u001b[39m:\n\u001b[32m--> \u001b[39m\u001b[32m144\u001b[39m \u001b[38;5;28mself\u001b[39m._accelerator_flag = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_choose_gpu_accelerator_backend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 146\u001b[39m \u001b[38;5;28mself\u001b[39m._check_device_config_and_set_final_flags(devices=devices, num_nodes=num_nodes)\n\u001b[32m 147\u001b[39m \u001b[38;5;28mself\u001b[39m._set_parallel_devices_and_init_accelerator()\n", - "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Kurokabe\\miniconda3\\envs\\darts\\Lib\\site-packages\\pytorch_lightning\\trainer\\connectors\\accelerator_connector.py:354\u001b[39m, in \u001b[36m_AcceleratorConnector._choose_gpu_accelerator_backend\u001b[39m\u001b[34m()\u001b[39m\n\u001b[32m 352\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m CUDAAccelerator.is_available():\n\u001b[32m 353\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mcuda\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m--> \u001b[39m\u001b[32m354\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m MisconfigurationException(\u001b[33m\"\u001b[39m\u001b[33mNo supported gpu backend found!\u001b[39m\u001b[33m\"\u001b[39m)\n", - "\u001b[31mMisconfigurationException\u001b[39m: No supported gpu backend found!" - ] + "data": { + "text/plain": [ + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=12, output_chunk_length=6, n_epochs=10, pl_trainer_kwargs={'accelerator': 'mps'})" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "model.fit(\n", - " series=train_energy,\n", + "model_loaded.fit(\n", + " series=train_passengers,\n", " verbose=True,\n", ")" ] }, + { + "cell_type": "code", + "execution_count": 43, + "id": "6bc9e736", + "metadata": {}, + "outputs": [], + "source": [ + "model_loaded.model.model = PeftModel.from_pretrained(\n", + " model_loaded.model.model, \"chronos2-lora-passengers\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "3306a586", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "7ea0d32c134f48ae9984a2179f2c138d", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pred = model.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + ")\n", + "val_passengers.plot(label=\"actual\")\n", + "pred.plot(label=\"forecast\");" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "e189768a", + "id": "41eeeb2e", "metadata": {}, "outputs": [], "source": [] @@ -268,7 +8092,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.12" + "version": "3.13.7" } }, "nbformat": 4, From 9057acbba7885f1cbda25311107455139d978f03 Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 16 Jan 2026 09:54:19 +0100 Subject: [PATCH 04/11] wip: add transform callback for foundation model fine-tuning --- darts/models/forecasting/foundation_model.py | 146 + .../26-Chronos-2-finetuning-examples.ipynb | 7857 +---------------- 2 files changed, 279 insertions(+), 7724 deletions(-) diff --git a/darts/models/forecasting/foundation_model.py b/darts/models/forecasting/foundation_model.py index 01ddc1f4de..1d87b53d4a 100644 --- a/darts/models/forecasting/foundation_model.py +++ b/darts/models/forecasting/foundation_model.py @@ -10,7 +10,11 @@ """ from abc import ABC +from functools import partial +from typing import Any, Callable +import pytorch_lightning as pl +from pytorch_lightning.callbacks import Callback from torch import nn from darts.logging import get_logger, raise_log @@ -186,3 +190,145 @@ class FoundationPLModule(PLForecastingModule): def __init__(self, **kwargs): super().__init__(**kwargs) self.model: nn.Module + + +class ModelTransformCallback(Callback): + def __init__( + self, + transform_fn: Callable[[nn.Module], nn.Module], + model_attribute: str = "model", + ): + super().__init__() + self.transform_fn = transform_fn + self.model_attribute = model_attribute + self._transformed = False + + def _get_inner_model(self, pl_module: pl.LightningModule) -> nn.Module: + """Get the inner model from the Lightning module.""" + return getattr(pl_module, self.model_attribute) + + def _set_inner_model(self, pl_module: pl.LightningModule, model: nn.Module): + """Set the inner model on the Lightning module.""" + setattr(pl_module, self.model_attribute, model) + + def on_fit_start(self, trainer: pl.Trainer, pl_module: pl.LightningModule): + """Apply transformation before training begins.""" + if not self._transformed: + inner_model = self._get_inner_model(pl_module) + transformed_model = self.transform_fn(inner_model) + self._set_inner_model(pl_module, transformed_model) + self._transformed = True + + # Log trainable parameters + trainable = sum( + p.numel() for p in pl_module.parameters() if p.requires_grad + ) + total = sum(p.numel() for p in pl_module.parameters()) + print( + f"Model transformed. Trainable: {trainable:,}/{total:,} ({100 * trainable / total:.2f}%)" + ) + + def on_save_checkpoint( + self, + trainer: pl.Trainer, + pl_module: pl.LightningModule, + checkpoint: dict[str, Any], + ): + """ + Handle checkpoint saving for transformed models. + + For PEFT models, we could optionally save just the adapter weights + or mark the checkpoint as requiring transformation on load. + """ + # Mark that this checkpoint was saved with a transformed model + checkpoint["model_transform_applied"] = True + + # TODO maybe replace in checkpoint["state_dict"] with pl_module.model.get_base_model().state_dict() + # and adapt the keys names accordingly + + def on_load_checkpoint( + self, + trainer: pl.Trainer, + pl_module: pl.LightningModule, + checkpoint: dict[str, Any], + ): + """ + Apply transformation before loading checkpoint weights. + + This ensures the model structure matches the saved weights. + """ + if checkpoint.get("model_transform_applied", False) and not self._transformed: + inner_model = self._get_inner_model(pl_module) + transformed_model = self.transform_fn(inner_model) + self._set_inner_model(pl_module, transformed_model) + self._transformed = True + + +class LayerFreezeCallback(ModelTransformCallback): + @classmethod + def _freeze_layers( + cls, model: nn.Module, freeze_patterns: list[str], unfreeze_patterns: list[str] + ) -> nn.Module: + for name, param in model.named_parameters(): + if any(name.startswith(layer) for layer in freeze_patterns): + param.requires_grad = False + if any(name.startswith(layer) for layer in unfreeze_patterns): + param.requires_grad = True + return model + + def __init__( + self, + freeze_patterns: list[str], + unfreeze_patterns: list[str] = None, + model_attribute: str = "model", + ): + unfreeze_patterns = unfreeze_patterns or [] + + super().__init__( + transform_fn=partial( + self._freeze_layers, + freeze_patterns=freeze_patterns, + unfreeze_patterns=unfreeze_patterns, + ), + model_attribute=model_attribute, + ) + + +class PeftCallback(ModelTransformCallback): + @classmethod + def _apply_peft(cls, model: nn.Module, peft_config) -> nn.Module: + try: + from peft import get_peft_model + except ImportError: + raise ImportError( + "Please install the `peft` package to use PeftCallback: `pip install peft`." + ) + peft_model = get_peft_model(model, peft_config) + return peft_model + + def __init__( + self, + peft_config=None, + model_attribute: str = "model", + ): + super().__init__( + transform_fn=partial(self._apply_peft, peft_config=peft_config), + model_attribute=model_attribute, + ) + self.peft_config = peft_config + + def on_save_checkpoint(self, trainer, pl_module, checkpoint): + checkpoint["peft_applied"] = True + # Optionally store config for reference + if self.peft_config is not None: + checkpoint["peft_config"] = self.peft_config.to_dict() + + def on_load_checkpoint( + self, + trainer: pl.Trainer, + pl_module: pl.LightningModule, + checkpoint: dict[str, Any], + ): + """Apply PEFT structure before loading weights.""" + if checkpoint.get("peft_applied", False): + self._apply_peft(pl_module, peft_config=self.peft_config) diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index 79d0bd8481..4cc65edb8e 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -25,7 +25,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 1, "id": "310fa52a", "metadata": {}, "outputs": [], @@ -39,19 +39,10 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 2, "id": "bfa59f65", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2\n", @@ -60,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "d510b54b", "metadata": {}, "outputs": [], @@ -113,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 4, "id": "2f87bcc5", "metadata": {}, "outputs": [], @@ -130,7 +121,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 5, "id": "a84830af", "metadata": {}, "outputs": [ @@ -214,7 +205,7 @@ "shape: (24, 1, 1), freq: MS, size: 96.00 B" ] }, - "execution_count": 27, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -233,7 +224,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 6, "id": "3b43a60a", "metadata": {}, "outputs": [ @@ -243,7 +234,7 @@ "" ] }, - "execution_count": 28, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, @@ -263,70 +254,28 @@ ] }, { - "cell_type": "code", - "execution_count": 29, - "id": "3cccd20e", + "cell_type": "markdown", + "id": "1313019f", "metadata": {}, - "outputs": [], "source": [ - "# use last 30 days of data to predict next 7 days\n", - "model = Chronos2Model(\n", - " input_chunk_length=12,\n", - " output_chunk_length=6,\n", - " n_epochs=10,\n", - " pl_trainer_kwargs={\"accelerator\": \"mps\"},\n", - ")" + "# Full fine-tuning" ] }, { "cell_type": "code", - "execution_count": 31, - "id": "08715193", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=12, output_chunk_length=6, n_epochs=10, pl_trainer_kwargs={'accelerator': 'mps'})" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.fit(\n", - " series=train_passengers,\n", - " verbose=True,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "f9c8b482", + "execution_count": 10, + "id": "72832dff", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0be2b2c066ac4d7f958b8a4b10778d4c", + "model_id": "fd9f95a0195d448cbc9d961c5cb274d8", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "Predicting: | | 0/? [00:00" + "Training: | | 0/? [00:00" + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=12, output_chunk_length=6, enable_finetuning=True, n_epochs=10, pl_trainer_kwargs={'callbacks': []})" ] }, + "execution_count": 6, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "pred = model.predict(\n", - " n=len(val_passengers),\n", - " series=train_passengers,\n", + "from peft import LoraConfig\n", + "\n", + "from darts.models.forecasting.foundation_model import PeftCallback\n", + "\n", + "lora_config = LoraConfig(\n", + " r=16,\n", + " lora_alpha=32,\n", + " target_modules=[\"q\", \"v\"],\n", + " lora_dropout=0.1,\n", ")\n", - "val_passengers.plot(label=\"actual\")\n", - "pred.plot(label=\"forecast\");" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "cc169bfa", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "trainable params: 1,179,648 || all params: 120,657,312 || trainable%: 0.9777\n" - ] - } - ], - "source": [ - "model.model.model.print_trainable_parameters()" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "f44f6966", - "metadata": {}, - "outputs": [], - "source": [ - "model.model.model.save_pretrained(\"chronos2-lora-passengers\")" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "a6a4328e", - "metadata": {}, - "outputs": [], - "source": [ - "# use last 30 days of data to predict next 7 days\n", - "model_loaded = Chronos2Model(\n", + "peft_callback = PeftCallback(peft_config=lora_config)\n", + "\n", + "model = Chronos2Model(\n", " input_chunk_length=12,\n", " output_chunk_length=6,\n", + " enable_finetuning=True,\n", " n_epochs=10,\n", - " pl_trainer_kwargs={\"accelerator\": \"mps\"},\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "7e7adc07", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=12, output_chunk_length=6, n_epochs=10, pl_trainer_kwargs={'accelerator': 'mps'})" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model_loaded.fit(\n", - " series=train_passengers,\n", - " verbose=True,\n", - ")" + " pl_trainer_kwargs={\"callbacks\": [peft_callback]},\n", + ")\n", + "model.fit(train_passengers, verbose=True)\n", + "\n", + "# model.save(\"chronos2_lora_finetuned.pt\")\n", + "# # Save adapters using PEFT's native method\n", + "# model.model.model.save_pretrained(\"chronos2_lora_adapters/\")\n", + "\n", + "# # === Loading ===\n", + "# # Use callback with adapter_path to load\n", + "# load_callback = PeftCallback(adapter_path=\"chronos2_lora_adapters/\")\n", + "\n", + "# loaded = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")\n", + "# loaded.fit(train_passengers[:1]) # Initialize model structure\n", + "# loaded.predict(n=12, series=train_passengers) # Adapters applied via on_predict_start" ] }, { "cell_type": "code", - "execution_count": 43, - "id": "6bc9e736", + "execution_count": 7, + "id": "2716abc4", "metadata": {}, "outputs": [], "source": [ - "model_loaded.model.model = PeftModel.from_pretrained(\n", - " model_loaded.model.model, \"chronos2-lora-passengers\"\n", - ")" + "model.save(\"chronos2_lora_finetuned.pt\")" ] }, { "cell_type": "code", - "execution_count": 44, - "id": "3306a586", + "execution_count": 14, + "id": "8122447b", "metadata": {}, "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "7ea0d32c134f48ae9984a2179f2c138d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Predicting: | | 0/? [00:00" - ] - }, - "metadata": {}, - "output_type": "display_data" + "ename": "RuntimeError", + "evalue": "Error(s) in loading state_dict for _Chronos2PLModule:\n\tMissing key(s) in state_dict: \"model.shared.weight\", \"model.input_patch_embedding.hidden_layer.weight\", \"model.input_patch_embedding.hidden_layer.bias\", \"model.input_patch_embedding.output_layer.weight\", \"model.input_patch_embedding.output_layer.bias\", \"model.input_patch_embedding.residual_layer.weight\", \"model.input_patch_embedding.residual_layer.bias\", \"model.encoder.block.0.layer.0.self_attention.q.weight\", \"model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.encoder.block.0.layer.0.self_attention.v.weight\", \"model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.encoder.block.0.layer.0.layer_norm.weight\", \"model.encoder.block.0.layer.1.self_attention.q.weight\", \"model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.encoder.block.0.layer.1.self_attention.v.weight\", \"model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.encoder.block.0.layer.1.layer_norm.weight\", \"model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.encoder.block.0.layer.2.layer_norm.weight\", \"model.encoder.block.1.layer.0.self_attention.q.weight\", \"model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.encoder.block.1.layer.0.self_attention.v.weight\", \"model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.encoder.block.1.layer.0.layer_norm.weight\", \"model.encoder.block.1.layer.1.self_attention.q.weight\", \"model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.encoder.block.1.layer.1.self_attention.v.weight\", \"model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.encoder.block.1.layer.1.layer_norm.weight\", \"model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.encoder.block.1.layer.2.layer_norm.weight\", \"model.encoder.block.2.layer.0.self_attention.q.weight\", \"model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.encoder.block.2.layer.0.self_attention.v.weight\", \"model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.encoder.block.2.layer.0.layer_norm.weight\", \"model.encoder.block.2.layer.1.self_attention.q.weight\", \"model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.encoder.block.2.layer.1.self_attention.v.weight\", \"model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.encoder.block.2.layer.1.layer_norm.weight\", \"model.encoder.block.2.layer.2.mlp.wi.weight\", \"model.encoder.block.2.layer.2.mlp.wo.weight\", \"model.encoder.block.2.layer.2.layer_norm.weight\", \"model.encoder.block.3.layer.0.self_attention.q.weight\", \"model.encoder.block.3.layer.0.self_attention.k.weight\", \"model.encoder.block.3.layer.0.self_attention.v.weight\", \"model.encoder.block.3.layer.0.self_attention.o.weight\", \"model.encoder.block.3.layer.0.layer_norm.weight\", \"model.encoder.block.3.layer.1.self_attention.q.weight\", \"model.encoder.block.3.layer.1.self_attention.k.weight\", \"model.encoder.block.3.layer.1.self_attention.v.weight\", \"model.encoder.block.3.layer.1.self_attention.o.weight\", \"model.encoder.block.3.layer.1.layer_norm.weight\", \"model.encoder.block.3.layer.2.mlp.wi.weight\", \"model.encoder.block.3.layer.2.mlp.wo.weight\", \"model.encoder.block.3.layer.2.layer_norm.weight\", \"model.encoder.block.4.layer.0.self_attention.q.weight\", \"model.encoder.block.4.layer.0.self_attention.k.weight\", \"model.encoder.block.4.layer.0.self_attention.v.weight\", \"model.encoder.block.4.layer.0.self_attention.o.weight\", \"model.encoder.block.4.layer.0.layer_norm.weight\", \"model.encoder.block.4.layer.1.self_attention.q.weight\", \"model.encoder.block.4.layer.1.self_attention.k.weight\", \"model.encoder.block.4.layer.1.self_attention.v.weight\", \"model.encoder.block.4.layer.1.self_attention.o.weight\", \"model.encoder.block.4.layer.1.layer_norm.weight\", \"model.encoder.block.4.layer.2.mlp.wi.weight\", \"model.encoder.block.4.layer.2.mlp.wo.weight\", \"model.encoder.block.4.layer.2.layer_norm.weight\", \"model.encoder.block.5.layer.0.self_attention.q.weight\", \"model.encoder.block.5.layer.0.self_attention.k.weight\", \"model.encoder.block.5.layer.0.self_attention.v.weight\", \"model.encoder.block.5.layer.0.self_attention.o.weight\", \"model.encoder.block.5.layer.0.layer_norm.weight\", \"model.encoder.block.5.layer.1.self_attention.q.weight\", \"model.encoder.block.5.layer.1.self_attention.k.weight\", \"model.encoder.block.5.layer.1.self_attention.v.weight\", \"model.encoder.block.5.layer.1.self_attention.o.weight\", \"model.encoder.block.5.layer.1.layer_norm.weight\", \"model.encoder.block.5.layer.2.mlp.wi.weight\", \"model.encoder.block.5.layer.2.mlp.wo.weight\", \"model.encoder.block.5.layer.2.layer_norm.weight\", \"model.encoder.block.6.layer.0.self_attention.q.weight\", \"model.encoder.block.6.layer.0.self_attention.k.weight\", \"model.encoder.block.6.layer.0.self_attention.v.weight\", \"model.encoder.block.6.layer.0.self_attention.o.weight\", \"model.encoder.block.6.layer.0.layer_norm.weight\", \"model.encoder.block.6.layer.1.self_attention.q.weight\", \"model.encoder.block.6.layer.1.self_attention.k.weight\", \"model.encoder.block.6.layer.1.self_attention.v.weight\", \"model.encoder.block.6.layer.1.self_attention.o.weight\", \"model.encoder.block.6.layer.1.layer_norm.weight\", \"model.encoder.block.6.layer.2.mlp.wi.weight\", \"model.encoder.block.6.layer.2.mlp.wo.weight\", \"model.encoder.block.6.layer.2.layer_norm.weight\", \"model.encoder.block.7.layer.0.self_attention.q.weight\", \"model.encoder.block.7.layer.0.self_attention.k.weight\", \"model.encoder.block.7.layer.0.self_attention.v.weight\", \"model.encoder.block.7.layer.0.self_attention.o.weight\", \"model.encoder.block.7.layer.0.layer_norm.weight\", \"model.encoder.block.7.layer.1.self_attention.q.weight\", \"model.encoder.block.7.layer.1.self_attention.k.weight\", \"model.encoder.block.7.layer.1.self_attention.v.weight\", \"model.encoder.block.7.layer.1.self_attention.o.weight\", \"model.encoder.block.7.layer.1.layer_norm.weight\", \"model.encoder.block.7.layer.2.mlp.wi.weight\", \"model.encoder.block.7.layer.2.mlp.wo.weight\", \"model.encoder.block.7.layer.2.layer_norm.weight\", \"model.encoder.block.8.layer.0.self_attention.q.weight\", \"model.encoder.block.8.layer.0.self_attention.k.weight\", \"model.encoder.block.8.layer.0.self_attention.v.weight\", \"model.encoder.block.8.layer.0.self_attention.o.weight\", \"model.encoder.block.8.layer.0.layer_norm.weight\", \"model.encoder.block.8.layer.1.self_attention.q.weight\", \"model.encoder.block.8.layer.1.self_attention.k.weight\", \"model.encoder.block.8.layer.1.self_attention.v.weight\", \"model.encoder.block.8.layer.1.self_attention.o.weight\", \"model.encoder.block.8.layer.1.layer_norm.weight\", \"model.encoder.block.8.layer.2.mlp.wi.weight\", \"model.encoder.block.8.layer.2.mlp.wo.weight\", \"model.encoder.block.8.layer.2.layer_norm.weight\", \"model.encoder.block.9.layer.0.self_attention.q.weight\", \"model.encoder.block.9.layer.0.self_attention.k.weight\", \"model.encoder.block.9.layer.0.self_attention.v.weight\", \"model.encoder.block.9.layer.0.self_attention.o.weight\", \"model.encoder.block.9.layer.0.layer_norm.weight\", \"model.encoder.block.9.layer.1.self_attention.q.weight\", \"model.encoder.block.9.layer.1.self_attention.k.weight\", \"model.encoder.block.9.layer.1.self_attention.v.weight\", \"model.encoder.block.9.layer.1.self_attention.o.weight\", \"model.encoder.block.9.layer.1.layer_norm.weight\", \"model.encoder.block.9.layer.2.mlp.wi.weight\", \"model.encoder.block.9.layer.2.mlp.wo.weight\", \"model.encoder.block.9.layer.2.layer_norm.weight\", \"model.encoder.block.10.layer.0.self_attention.q.weight\", \"model.encoder.block.10.layer.0.self_attention.k.weight\", \"model.encoder.block.10.layer.0.self_attention.v.weight\", \"model.encoder.block.10.layer.0.self_attention.o.weight\", \"model.encoder.block.10.layer.0.layer_norm.weight\", \"model.encoder.block.10.layer.1.self_attention.q.weight\", \"model.encoder.block.10.layer.1.self_attention.k.weight\", \"model.encoder.block.10.layer.1.self_attention.v.weight\", \"model.encoder.block.10.layer.1.self_attention.o.weight\", \"model.encoder.block.10.layer.1.layer_norm.weight\", \"model.encoder.block.10.layer.2.mlp.wi.weight\", \"model.encoder.block.10.layer.2.mlp.wo.weight\", \"model.encoder.block.10.layer.2.layer_norm.weight\", \"model.encoder.block.11.layer.0.self_attention.q.weight\", \"model.encoder.block.11.layer.0.self_attention.k.weight\", \"model.encoder.block.11.layer.0.self_attention.v.weight\", \"model.encoder.block.11.layer.0.self_attention.o.weight\", \"model.encoder.block.11.layer.0.layer_norm.weight\", \"model.encoder.block.11.layer.1.self_attention.q.weight\", \"model.encoder.block.11.layer.1.self_attention.k.weight\", \"model.encoder.block.11.layer.1.self_attention.v.weight\", \"model.encoder.block.11.layer.1.self_attention.o.weight\", \"model.encoder.block.11.layer.1.layer_norm.weight\", \"model.encoder.block.11.layer.2.mlp.wi.weight\", \"model.encoder.block.11.layer.2.mlp.wo.weight\", \"model.encoder.block.11.layer.2.layer_norm.weight\", \"model.encoder.final_layer_norm.weight\", \"model.output_patch_embedding.hidden_layer.weight\", \"model.output_patch_embedding.hidden_layer.bias\", \"model.output_patch_embedding.output_layer.weight\", \"model.output_patch_embedding.output_layer.bias\", \"model.output_patch_embedding.residual_layer.weight\", \"model.output_patch_embedding.residual_layer.bias\". \n\tUnexpected key(s) in state_dict: \"model.base_model.model.shared.weight\", 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\"model.base_model.model.encoder.block.11.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.final_layer_norm.weight\", \"model.base_model.model.output_patch_embedding.hidden_layer.weight\", \"model.base_model.model.output_patch_embedding.hidden_layer.bias\", \"model.base_model.model.output_patch_embedding.output_layer.weight\", \"model.base_model.model.output_patch_embedding.output_layer.bias\", \"model.base_model.model.output_patch_embedding.residual_layer.weight\", \"model.base_model.model.output_patch_embedding.residual_layer.bias\". ", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m loaded \u001b[38;5;241m=\u001b[39m \u001b[43mChronos2Model\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mchronos2_lora_finetuned.pt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpl_trainer_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcallbacks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mpeft_callback\u001b[49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/Projects/Darts/darts/darts/models/forecasting/torch_forecasting_model.py:2072\u001b[0m, in \u001b[0;36mTorchForecastingModel.load\u001b[0;34m(path, pl_trainer_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 2070\u001b[0m path_ptl_ckpt \u001b[38;5;241m=\u001b[39m path \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.ckpt\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2071\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mexists(path_ptl_ckpt):\n\u001b[0;32m-> 2072\u001b[0m model\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_load_from_checkpoint\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath_ptl_ckpt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2073\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 2074\u001b[0m model\u001b[38;5;241m.\u001b[39m_fit_called \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n", + "File \u001b[0;32m~/Projects/Darts/darts/darts/models/forecasting/torch_forecasting_model.py:2204\u001b[0m, in \u001b[0;36mTorchForecastingModel._load_from_checkpoint\u001b[0;34m(self, file_path, **kwargs)\u001b[0m\n\u001b[1;32m 2198\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Loads a checkpoint for the underlying :class:`PLForecastingModule` (PLM) model.\u001b[39;00m\n\u001b[1;32m 2199\u001b[0m \u001b[38;5;124;03mThe PLM object is not stored when saving a :class:`TorchForecastingModel` (TFM) to avoid saving\u001b[39;00m\n\u001b[1;32m 2200\u001b[0m \u001b[38;5;124;03mthe model twice. Instead, we recover the module class with the module path and class name stored\u001b[39;00m\n\u001b[1;32m 2201\u001b[0m \u001b[38;5;124;03min the TFM object. With the recovered module class, we can load the checkpoint.\u001b[39;00m\n\u001b[1;32m 2202\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 2203\u001b[0m pl_module_cls \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(sys\u001b[38;5;241m.\u001b[39mmodules[\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_module_path], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_module_name)\n\u001b[0;32m-> 2204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpl_module_cls\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_from_checkpoint\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfile_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/utilities/model_helpers.py:125\u001b[0m, in \u001b[0;36m_restricted_classmethod_impl.__get__..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m instance \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_scripting:\n\u001b[1;32m 121\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 122\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe classmethod `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmethod\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` cannot be called on an instance.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 123\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m Please call it on the class type and make sure the return value is used.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 124\u001b[0m )\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/core/module.py:1611\u001b[0m, in \u001b[0;36mLightningModule.load_from_checkpoint\u001b[0;34m(cls, checkpoint_path, map_location, hparams_file, strict, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;129m@_restricted_classmethod\u001b[39m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mload_from_checkpoint\u001b[39m(\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 1530\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Self:\n\u001b[1;32m 1531\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Primary way of loading a model from a checkpoint. When Lightning saves a checkpoint it stores the arguments\u001b[39;00m\n\u001b[1;32m 1532\u001b[0m \u001b[38;5;124;03m passed to ``__init__`` in the checkpoint under ``\"hyper_parameters\"``.\u001b[39;00m\n\u001b[1;32m 1533\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1609\u001b[0m \n\u001b[1;32m 1610\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1611\u001b[0m loaded \u001b[38;5;241m=\u001b[39m \u001b[43m_load_from_checkpoint\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1612\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1613\u001b[0m \u001b[43m \u001b[49m\u001b[43mcheckpoint_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1614\u001b[0m \u001b[43m \u001b[49m\u001b[43mmap_location\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1615\u001b[0m \u001b[43m \u001b[49m\u001b[43mhparams_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1616\u001b[0m \u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1617\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1618\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1619\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cast(Self, loaded)\n", + "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/core/saving.py:91\u001b[0m, in \u001b[0;36m_load_from_checkpoint\u001b[0;34m(cls, checkpoint_path, map_location, hparams_file, strict, **kwargs)\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _load_state(\u001b[38;5;28mcls\u001b[39m, checkpoint, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28missubclass\u001b[39m(\u001b[38;5;28mcls\u001b[39m, pl\u001b[38;5;241m.\u001b[39mLightningModule):\n\u001b[0;32m---> 91\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43m_load_state\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheckpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstrict\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 92\u001b[0m state_dict \u001b[38;5;241m=\u001b[39m checkpoint[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstate_dict\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m state_dict:\n", + "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/core/saving.py:187\u001b[0m, in \u001b[0;36m_load_state\u001b[0;34m(cls, checkpoint, strict, **cls_kwargs_new)\u001b[0m\n\u001b[1;32m 184\u001b[0m obj\u001b[38;5;241m.\u001b[39mon_load_checkpoint(checkpoint)\n\u001b[1;32m 186\u001b[0m \u001b[38;5;66;03m# load the state_dict on the model automatically\u001b[39;00m\n\u001b[0;32m--> 187\u001b[0m keys \u001b[38;5;241m=\u001b[39m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_state_dict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcheckpoint\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstate_dict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstrict\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore[arg-type]\u001b[39;00m\n\u001b[1;32m 189\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m strict:\n\u001b[1;32m 190\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m keys\u001b[38;5;241m.\u001b[39mmissing_keys:\n", + "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/torch/nn/modules/module.py:2624\u001b[0m, in \u001b[0;36mModule.load_state_dict\u001b[0;34m(self, state_dict, strict, assign)\u001b[0m\n\u001b[1;32m 2616\u001b[0m error_msgs\u001b[38;5;241m.\u001b[39minsert(\n\u001b[1;32m 2617\u001b[0m \u001b[38;5;241m0\u001b[39m,\n\u001b[1;32m 2618\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMissing key(s) in state_dict: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 2619\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mk\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m missing_keys)\n\u001b[1;32m 2620\u001b[0m ),\n\u001b[1;32m 2621\u001b[0m )\n\u001b[1;32m 2623\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(error_msgs) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 2624\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 2625\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError(s) in loading state_dict for \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 2626\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(error_msgs)\n\u001b[1;32m 2627\u001b[0m )\n\u001b[1;32m 2628\u001b[0m )\n\u001b[1;32m 2629\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _IncompatibleKeys(missing_keys, unexpected_keys)\n", + "\u001b[0;31mRuntimeError\u001b[0m: Error(s) in loading state_dict for _Chronos2PLModule:\n\tMissing key(s) in state_dict: \"model.shared.weight\", \"model.input_patch_embedding.hidden_layer.weight\", \"model.input_patch_embedding.hidden_layer.bias\", \"model.input_patch_embedding.output_layer.weight\", \"model.input_patch_embedding.output_layer.bias\", \"model.input_patch_embedding.residual_layer.weight\", \"model.input_patch_embedding.residual_layer.bias\", \"model.encoder.block.0.layer.0.self_attention.q.weight\", \"model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.encoder.block.0.layer.0.self_attention.v.weight\", \"model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.encoder.block.0.layer.0.layer_norm.weight\", \"model.encoder.block.0.layer.1.self_attention.q.weight\", \"model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.encoder.block.0.layer.1.self_attention.v.weight\", \"model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.encoder.block.0.layer.1.layer_norm.weight\", \"model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.encoder.block.0.layer.2.layer_norm.weight\", \"model.encoder.block.1.layer.0.self_attention.q.weight\", \"model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.encoder.block.1.layer.0.self_attention.v.weight\", \"model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.encoder.block.1.layer.0.layer_norm.weight\", \"model.encoder.block.1.layer.1.self_attention.q.weight\", \"model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.encoder.block.1.layer.1.self_attention.v.weight\", \"model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.encoder.block.1.layer.1.layer_norm.weight\", \"model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.encoder.block.1.layer.2.layer_norm.weight\", \"model.encoder.block.2.layer.0.self_attention.q.weight\", \"model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.encoder.block.2.layer.0.self_attention.v.weight\", \"model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.encoder.block.2.layer.0.layer_norm.weight\", \"model.encoder.block.2.layer.1.self_attention.q.weight\", \"model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.encoder.block.2.layer.1.self_attention.v.weight\", \"model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.encoder.block.2.layer.1.layer_norm.weight\", \"model.encoder.block.2.layer.2.mlp.wi.weight\", \"model.encoder.block.2.layer.2.mlp.wo.weight\", \"model.encoder.block.2.layer.2.layer_norm.weight\", \"model.encoder.block.3.layer.0.self_attention.q.weight\", \"model.encoder.block.3.layer.0.self_attention.k.weight\", \"model.encoder.block.3.layer.0.self_attention.v.weight\", \"model.encoder.block.3.layer.0.self_attention.o.weight\", \"model.encoder.block.3.layer.0.layer_norm.weight\", \"model.encoder.block.3.layer.1.self_attention.q.weight\", \"model.encoder.block.3.layer.1.self_attention.k.weight\", \"model.encoder.block.3.layer.1.self_attention.v.weight\", \"model.encoder.block.3.layer.1.self_attention.o.weight\", \"model.encoder.block.3.layer.1.layer_norm.weight\", \"model.encoder.block.3.layer.2.mlp.wi.weight\", \"model.encoder.block.3.layer.2.mlp.wo.weight\", \"model.encoder.block.3.layer.2.layer_norm.weight\", \"model.encoder.block.4.layer.0.self_attention.q.weight\", \"model.encoder.block.4.layer.0.self_attention.k.weight\", \"model.encoder.block.4.layer.0.self_attention.v.weight\", \"model.encoder.block.4.layer.0.self_attention.o.weight\", \"model.encoder.block.4.layer.0.layer_norm.weight\", \"model.encoder.block.4.layer.1.self_attention.q.weight\", \"model.encoder.block.4.layer.1.self_attention.k.weight\", \"model.encoder.block.4.layer.1.self_attention.v.weight\", \"model.encoder.block.4.layer.1.self_attention.o.weight\", \"model.encoder.block.4.layer.1.layer_norm.weight\", \"model.encoder.block.4.layer.2.mlp.wi.weight\", \"model.encoder.block.4.layer.2.mlp.wo.weight\", \"model.encoder.block.4.layer.2.layer_norm.weight\", \"model.encoder.block.5.layer.0.self_attention.q.weight\", \"model.encoder.block.5.layer.0.self_attention.k.weight\", \"model.encoder.block.5.layer.0.self_attention.v.weight\", \"model.encoder.block.5.layer.0.self_attention.o.weight\", \"model.encoder.block.5.layer.0.layer_norm.weight\", \"model.encoder.block.5.layer.1.self_attention.q.weight\", \"model.encoder.block.5.layer.1.self_attention.k.weight\", \"model.encoder.block.5.layer.1.self_attention.v.weight\", \"model.encoder.block.5.layer.1.self_attention.o.weight\", \"model.encoder.block.5.layer.1.layer_norm.weight\", \"model.encoder.block.5.layer.2.mlp.wi.weight\", \"model.encoder.block.5.layer.2.mlp.wo.weight\", \"model.encoder.block.5.layer.2.layer_norm.weight\", \"model.encoder.block.6.layer.0.self_attention.q.weight\", \"model.encoder.block.6.layer.0.self_attention.k.weight\", \"model.encoder.block.6.layer.0.self_attention.v.weight\", \"model.encoder.block.6.layer.0.self_attention.o.weight\", \"model.encoder.block.6.layer.0.layer_norm.weight\", \"model.encoder.block.6.layer.1.self_attention.q.weight\", \"model.encoder.block.6.layer.1.self_attention.k.weight\", \"model.encoder.block.6.layer.1.self_attention.v.weight\", \"model.encoder.block.6.layer.1.self_attention.o.weight\", \"model.encoder.block.6.layer.1.layer_norm.weight\", \"model.encoder.block.6.layer.2.mlp.wi.weight\", \"model.encoder.block.6.layer.2.mlp.wo.weight\", \"model.encoder.block.6.layer.2.layer_norm.weight\", \"model.encoder.block.7.layer.0.self_attention.q.weight\", \"model.encoder.block.7.layer.0.self_attention.k.weight\", \"model.encoder.block.7.layer.0.self_attention.v.weight\", \"model.encoder.block.7.layer.0.self_attention.o.weight\", \"model.encoder.block.7.layer.0.layer_norm.weight\", \"model.encoder.block.7.layer.1.self_attention.q.weight\", \"model.encoder.block.7.layer.1.self_attention.k.weight\", \"model.encoder.block.7.layer.1.self_attention.v.weight\", \"model.encoder.block.7.layer.1.self_attention.o.weight\", \"model.encoder.block.7.layer.1.layer_norm.weight\", \"model.encoder.block.7.layer.2.mlp.wi.weight\", \"model.encoder.block.7.layer.2.mlp.wo.weight\", \"model.encoder.block.7.layer.2.layer_norm.weight\", \"model.encoder.block.8.layer.0.self_attention.q.weight\", \"model.encoder.block.8.layer.0.self_attention.k.weight\", \"model.encoder.block.8.layer.0.self_attention.v.weight\", \"model.encoder.block.8.layer.0.self_attention.o.weight\", \"model.encoder.block.8.layer.0.layer_norm.weight\", \"model.encoder.block.8.layer.1.self_attention.q.weight\", \"model.encoder.block.8.layer.1.self_attention.k.weight\", \"model.encoder.block.8.layer.1.self_attention.v.weight\", \"model.encoder.block.8.layer.1.self_attention.o.weight\", \"model.encoder.block.8.layer.1.layer_norm.weight\", \"model.encoder.block.8.layer.2.mlp.wi.weight\", \"model.encoder.block.8.layer.2.mlp.wo.weight\", \"model.encoder.block.8.layer.2.layer_norm.weight\", \"model.encoder.block.9.layer.0.self_attention.q.weight\", \"model.encoder.block.9.layer.0.self_attention.k.weight\", \"model.encoder.block.9.layer.0.self_attention.v.weight\", \"model.encoder.block.9.layer.0.self_attention.o.weight\", \"model.encoder.block.9.layer.0.layer_norm.weight\", \"model.encoder.block.9.layer.1.self_attention.q.weight\", \"model.encoder.block.9.layer.1.self_attention.k.weight\", \"model.encoder.block.9.layer.1.self_attention.v.weight\", \"model.encoder.block.9.layer.1.self_attention.o.weight\", \"model.encoder.block.9.layer.1.layer_norm.weight\", \"model.encoder.block.9.layer.2.mlp.wi.weight\", \"model.encoder.block.9.layer.2.mlp.wo.weight\", \"model.encoder.block.9.layer.2.layer_norm.weight\", \"model.encoder.block.10.layer.0.self_attention.q.weight\", \"model.encoder.block.10.layer.0.self_attention.k.weight\", \"model.encoder.block.10.layer.0.self_attention.v.weight\", \"model.encoder.block.10.layer.0.self_attention.o.weight\", \"model.encoder.block.10.layer.0.layer_norm.weight\", \"model.encoder.block.10.layer.1.self_attention.q.weight\", \"model.encoder.block.10.layer.1.self_attention.k.weight\", \"model.encoder.block.10.layer.1.self_attention.v.weight\", \"model.encoder.block.10.layer.1.self_attention.o.weight\", \"model.encoder.block.10.layer.1.layer_norm.weight\", \"model.encoder.block.10.layer.2.mlp.wi.weight\", \"model.encoder.block.10.layer.2.mlp.wo.weight\", \"model.encoder.block.10.layer.2.layer_norm.weight\", \"model.encoder.block.11.layer.0.self_attention.q.weight\", \"model.encoder.block.11.layer.0.self_attention.k.weight\", \"model.encoder.block.11.layer.0.self_attention.v.weight\", \"model.encoder.block.11.layer.0.self_attention.o.weight\", \"model.encoder.block.11.layer.0.layer_norm.weight\", \"model.encoder.block.11.layer.1.self_attention.q.weight\", \"model.encoder.block.11.layer.1.self_attention.k.weight\", \"model.encoder.block.11.layer.1.self_attention.v.weight\", \"model.encoder.block.11.layer.1.self_attention.o.weight\", \"model.encoder.block.11.layer.1.layer_norm.weight\", \"model.encoder.block.11.layer.2.mlp.wi.weight\", \"model.encoder.block.11.layer.2.mlp.wo.weight\", \"model.encoder.block.11.layer.2.layer_norm.weight\", \"model.encoder.final_layer_norm.weight\", \"model.output_patch_embedding.hidden_layer.weight\", \"model.output_patch_embedding.hidden_layer.bias\", \"model.output_patch_embedding.output_layer.weight\", \"model.output_patch_embedding.output_layer.bias\", \"model.output_patch_embedding.residual_layer.weight\", \"model.output_patch_embedding.residual_layer.bias\". \n\tUnexpected key(s) in state_dict: \"model.base_model.model.shared.weight\", \"model.base_model.model.input_patch_embedding.hidden_layer.weight\", \"model.base_model.model.input_patch_embedding.hidden_layer.bias\", \"model.base_model.model.input_patch_embedding.output_layer.weight\", \"model.base_model.model.input_patch_embedding.output_layer.bias\", \"model.base_model.model.input_patch_embedding.residual_layer.weight\", \"model.base_model.model.input_patch_embedding.residual_layer.bias\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.0.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.0.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.0.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.1.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.1.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.1.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.2.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.2.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.2.mlp.wi.weight\", 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" + ] } ], "source": [ - "pred = model.predict(\n", - " n=len(val_passengers),\n", - " series=train_passengers,\n", - ")\n", - "val_passengers.plot(label=\"actual\")\n", - "pred.plot(label=\"forecast\");" + "loaded = Chronos2Model.load(\n", + " \"chronos2_lora_finetuned.pt\", pl_trainer_kwargs={\"callbacks\": [peft_callback]}\n", + ")" ] }, { "cell_type": "code", "execution_count": null, - "id": "41eeeb2e", + "id": "a7a64516", "metadata": {}, "outputs": [], "source": [] From 34b08c1bcf922c7a9dee9df9a28fd1ac66b1ba6a Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 16 Jan 2026 17:45:39 +0100 Subject: [PATCH 05/11] fix: make lora finetuning work --- darts/models/forecasting/foundation_model.py | 63 +- .../26-Chronos-2-finetuning-examples.ipynb | 617 +++++++++++------- 2 files changed, 448 insertions(+), 232 deletions(-) diff --git a/darts/models/forecasting/foundation_model.py b/darts/models/forecasting/foundation_model.py index 1d87b53d4a..b526b4aee0 100644 --- a/darts/models/forecasting/foundation_model.py +++ b/darts/models/forecasting/foundation_model.py @@ -10,6 +10,7 @@ """ from abc import ABC +from copy import deepcopy from functools import partial from typing import Any, Callable @@ -185,6 +186,19 @@ def encode_year(idx): def _requires_training(self) -> bool: return self._enable_finetuning + @property + def internal_model(self) -> Any: + """ + Returns the underlying PyTorch model (nn.Module). + This gives access to the actual internal mechanics of the model, which can be useful + for advanced usage like accessing PEFT adapters, inspecting weights or custom saving/loading. + + If the model has not been initialized yet, returns None. + """ + if hasattr(self, "model") and hasattr(self.model, "model"): + return self.model.model + return None + class FoundationPLModule(PLForecastingModule): def __init__(self, **kwargs): @@ -211,8 +225,8 @@ def _set_inner_model(self, pl_module: pl.LightningModule, model: nn.Module): """Set the inner model on the Lightning module.""" setattr(pl_module, self.model_attribute, model) - def on_fit_start(self, trainer: pl.Trainer, pl_module: pl.LightningModule): - """Apply transformation before training begins.""" + def setup(self, trainer: pl.Trainer, pl_module: pl.LightningModule, stage: str): + """Apply transformation before training begins (before optimizer setup).""" if not self._transformed: inner_model = self._get_inner_model(pl_module) transformed_model = self.transform_fn(inner_model) @@ -243,9 +257,6 @@ def on_save_checkpoint( # Mark that this checkpoint was saved with a transformed model checkpoint["model_transform_applied"] = True - # TODO maybe replace in checkpoint["state_dict"] with pl_module.model.get_base_model().state_dict() - # and adapt the keys names accordingly - def on_load_checkpoint( self, trainer: pl.Trainer, @@ -318,10 +329,44 @@ def __init__( self.peft_config = peft_config def on_save_checkpoint(self, trainer, pl_module, checkpoint): - checkpoint["peft_applied"] = True - # Optionally store config for reference - if self.peft_config is not None: - checkpoint["peft_config"] = self.peft_config.to_dict() + # We replace the state_dict in the checkpoint with the one from the base model + # (with adapters merged), so that the model can be loaded as a regular model. + peft_model = getattr(pl_module, self.model_attribute, None) + try: + from peft import PeftModel + except ImportError: + return + + if isinstance(peft_model, PeftModel): + # Merge adapters into the base model weights + model_copy = deepcopy(peft_model) + setattr(pl_module, self.model_attribute, peft_model.merge_and_unload()) + try: + # Get the state dict of the base model + # This returns the weights including the merged adapters + # base_state_dict = peft_model.get_base_model().state_dict() + + # We need to prepend the model attribute name to the keys + # because the PL module expects keys to start with `model.` (or `model_attribute.`) + prefix = self.model_attribute + "." + new_state_dict = { + prefix + k: v + for k, v in getattr(pl_module, self.model_attribute) + .state_dict() + .items() + } + + # # Update the checkpoint + checkpoint["state_dict"] = new_state_dict + + # Remove "peft_applied" so that on_load_checkpoint() does not try to re-wrap the model + # This allows loading the model as a regular (non-PEFT) model + checkpoint.pop("peft_applied", None) + checkpoint.pop("peft_config", None) + + finally: + # Unmerge adapters to keep the current model in PEFT mode + setattr(pl_module, self.model_attribute, model_copy) def on_load_checkpoint( self, diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index 4cc65edb8e..50fc3d1e3b 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -5,27 +5,23 @@ "id": "da55dd6c", "metadata": {}, "source": [ - "# Chronos-2 Foundation Model\n", - "In this notebook, we will show how to use Chronos-2 in Darts. If you are new to Darts, please check out the [Quickstart Guide](https://unit8co.github.io/darts/quickstart/00-quickstart.html) before proceeding.\n", - "\n", - "Chronos-2 is a time series foundation model for zero-shot forecasting. That means that it can be used for forecasting **without any training or fine-tuning** since it has already been pre-trained on large-scale time series data. Chronos-2 supports multivariate time series forecasting with [covariates](https://unit8co.github.io/darts/userguide/covariates.html) (exogenous variables) and can produce probabilistic forecasts.\n", - "\n", - "Check out the [Amazon Science Blog](https://www.amazon.science/blog/introducing-chronos-2-from-univariate-to-universal-forecasting) and the [original paper](https://arxiv.org/abs/2510.15821) for technical details." + "# Chronos-2 Foundation Model Fine-Tuning" ] }, { - "cell_type": "markdown", - "id": "9ad51937", + "cell_type": "code", + "execution_count": 1, + "id": "bfa59f65", "metadata": {}, + "outputs": [], "source": [ - "
\n", - " Fine-tuning Chronos-2 on your own data is not yet supported in Darts, but may be added in the future.\n", - "
" + "%load_ext autoreload\n", + "%autoreload 2" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "310fa52a", "metadata": {}, "outputs": [], @@ -37,18 +33,6 @@ "%matplotlib inline" ] }, - { - "cell_type": "code", - "execution_count": 2, - "id": "bfa59f65", - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2\n", - "%matplotlib inline" - ] - }, { "cell_type": "code", "execution_count": 3, @@ -77,31 +61,6 @@ "## Data Preparation" ] }, - { - "cell_type": "markdown", - "id": "70d7e392", - "metadata": {}, - "source": [ - "Here, we will use the [Electricity Consumption Zurich Dataset](https://unit8co.github.io/darts/generated_api/darts.datasets.html#darts.datasets.ElectricityConsumptionZurichDataset), which records the electricity consumption of households & SMEs (`\"Value_NE5\"` column) and business & services (`\"Value_NE7\"`) in Zurich, Switzerland, along with weather covariates such as temperature (`\"T [°C]\"`) and humidity (`\"Hr [%Hr]\"`).\n", - "Values are recorded every 15 minutes between January 2015 and August 2022.\n", - "\n", - "
\n", - "\n", - "Train-Test Split\n", - "\n", - "Even though Chronos-2 is pre-trained already, we still need to split the data into training and test sets. That is because `Chronos2Model` follows the Darts unified interface and will require calling the `fit()` method before forecasting. However, no training or fine-tuning will be performed during the `fit()` call.\n", - "\n", - "
\n", - "\n", - "
\n", - "\n", - "Data Scaling\n", - "\n", - "Unlike other deep learning models in Darts, Chronos-2 does not require data scaling since it has its own internal data normalization mechanism. Therefore, we will skip the scaling step in this notebook.\n", - "\n", - "
" - ] - }, { "cell_type": "code", "execution_count": 4, @@ -111,136 +70,56 @@ "source": [ "# convert to float32 as Chronos-2 works with float32 input\n", "data = AirPassengersDataset().load().astype(np.float32)\n", - "# extract households energy consumption\n", - "# ts_energy = data[\"Value_NE5\"]\n", - "# # extract temperature, solar irradiation and rain duration\n", - "# ts_weather = data[[\"T [°C]\", \"StrGlo [W/m2]\", \"RainDur [min]\"]]\n", - "# # split into train and validation sets by last 7 days\n", - "train_passengers, val_passengers = data.split_before(len(data) - 2 * 12)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "a84830af", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "

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#Passengers
Month
1959-01-01360.0
1959-02-01342.0
1959-03-01406.0
1959-04-01396.0
1959-05-01420.0
......
1960-08-01606.0
1960-09-01508.0
1960-10-01461.0
1960-11-01390.0
1960-12-01432.0

shape: (24, 1, 1), freq: MS, size: 96.00 B

" - ], - "text/plain": [ - " #Passengers\n", - "Month \n", - "1959-01-01 360.0\n", - "1959-02-01 342.0\n", - "1959-03-01 406.0\n", - "1959-04-01 396.0\n", - "1959-05-01 420.0\n", - "... ...\n", - "1960-08-01 606.0\n", - "1960-09-01 508.0\n", - "1960-10-01 461.0\n", - "1960-11-01 390.0\n", - "1960-12-01 432.0\n", - "\n", - "shape: (24, 1, 1), freq: MS, size: 96.00 B" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "val_passengers" + "train_passengers, val_passengers = data.split_before(\n", + " len(data) - 2 * 12\n", + ") # last 2 years for validation" ] }, { "cell_type": "markdown", - "id": "a3887f37", + "id": "b9251561", "metadata": {}, "source": [ - "Let's quickly visualize the last 7 days of the electricity consumption data." + "# Model prediction out-of-the-box\n", + "Let's see how the model behaves on the validation data without any fine-tuning. For that we:\n", + "- Create the model\n", + "- Call fit to load the model internally (no training is done)\n", + "- Predict on the validation set" ] }, { "cell_type": "code", - "execution_count": 6, - "id": "3b43a60a", + "execution_count": 13, + "id": "ea8456ae", "metadata": {}, "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a08b5ab19e164a3086e0a3bf59c7f2c3", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" ] }, - "execution_count": 6, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -250,7 +129,18 @@ } ], "source": [ - "val_passengers.plot(label=\"passengers\")" + "model = Chronos2Model(\n", + " input_chunk_length=24,\n", + " output_chunk_length=6,\n", + ")\n", + "model.fit(train_passengers, verbose=True)\n", + "\n", + "prediction = model.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + ")\n", + "val_passengers.plot(label=\"Ground truth\")\n", + "prediction.plot(label=\"Forecast\")" ] }, { @@ -258,19 +148,23 @@ "id": "1313019f", "metadata": {}, "source": [ - "# Full fine-tuning" + "# Full fine-tuning\n", + "\n", + "In this method, all the model weights are retrained. This is done with `enable_finetuning=True` in the model constructor.\n", + "\n", + "The model is saved then loaded to show that Darts model saving and restoration continue to work with the different fine-tuning methods" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "id": "72832dff", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fd9f95a0195d448cbc9d961c5cb274d8", + "model_id": "c73e0b0c4ed942a0b8c1c3915d6de446", "version_major": 2, "version_minor": 0 }, @@ -284,10 +178,11 @@ ], "source": [ "model = Chronos2Model(\n", - " input_chunk_length=12,\n", + " input_chunk_length=24,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=10,\n", + " n_epochs=100,\n", + " pl_trainer_kwargs={\"accelerator\": \"gpu\"},\n", ")\n", "model.fit(train_passengers, verbose=True)\n", "model.save(\"full_finetuned.pt\")\n", @@ -296,6 +191,104 @@ "loaded = Chronos2Model.load(\"full_finetuned.pt\")" ] }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9bbd219e", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "607d823d5a9f436289c2a9d8789c21a0", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pred_trained = model.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + ")\n", + "pred_loaded = loaded.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + ")\n", + "val_passengers.plot(label=\"Ground truth\")\n", + "pred_trained.plot(label=\"Forecast of the trained model\")\n", + "pred_loaded.plot(label=\"Forecast of the loaded model\")" + ] + }, + { + "cell_type": "markdown", + "id": "d3dc22f4", + "metadata": {}, + "source": [ + "We can also verify that the prediction of the trained model is identical to the prediction of the loaded model" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "599402d3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pred_trained == pred_loaded" + ] + }, { "cell_type": "markdown", "id": "3cabab8a", @@ -306,7 +299,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 29, "id": "33fa7fc4", "metadata": {}, "outputs": [ @@ -320,7 +313,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "76747d3e90b64bf1a861dffa31b5b87c", + "model_id": "970d4406f6974c1085b70f9585de66c4", "version_major": 2, "version_minor": 0 }, @@ -344,8 +337,8 @@ " input_chunk_length=12,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=10,\n", - " pl_trainer_kwargs={\"callbacks\": [freeze_callback]},\n", + " n_epochs=100,\n", + " pl_trainer_kwargs={\"accelerator\": \"gpu\", \"callbacks\": [freeze_callback]},\n", ")\n", "model.fit(train_passengers, verbose=True)\n", "model.save(\"partial_finetuned.pt\")\n", @@ -354,6 +347,106 @@ "loaded = Chronos2Model.load(\"partial_finetuned.pt\")" ] }, + { + "cell_type": "code", + "execution_count": 30, + "id": "50830283", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "fbb261b4924248879c6f3224ae0b331a", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pred_trained = model.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + " random_state=42,\n", + ")\n", + "pred_loaded = loaded.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + " random_state=42,\n", + ")\n", + "val_passengers.plot(label=\"Ground truth\")\n", + "pred_trained.plot(label=\"Forecast of the trained model\")\n", + "pred_loaded.plot(label=\"Forecast of the loaded model\")" + ] + }, + { + "cell_type": "markdown", + "id": "3c01daaa", + "metadata": {}, + "source": [ + "Again, we verify that the prediction of the fine-tuned model is the same as the loaded model to make sure that saving/load works correctly" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "01717b70", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pred_trained == pred_loaded" + ] + }, { "cell_type": "markdown", "id": "b0d126dc", @@ -364,7 +457,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "6981052c", "metadata": {}, "outputs": [ @@ -372,13 +465,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model transformed. Trainable: 1,179,648/120,657,312 (0.98%)\n" + "Model transformed. Trainable: 1,206,912/120,684,576 (1.00%)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "253112b961e349e4abb07e1b22606f15", + "model_id": "6e469e8f90df46a0b3673668261f603b", "version_major": 2, "version_minor": 0 }, @@ -388,16 +481,6 @@ }, "metadata": {}, "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=12, output_chunk_length=6, enable_finetuning=True, n_epochs=10, pl_trainer_kwargs={'callbacks': []})" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" } ], "source": [ @@ -406,80 +489,168 @@ "from darts.models.forecasting.foundation_model import PeftCallback\n", "\n", "lora_config = LoraConfig(\n", - " r=16,\n", - " lora_alpha=32,\n", - " target_modules=[\"q\", \"v\"],\n", - " lora_dropout=0.1,\n", + " r=8,\n", + " lora_alpha=16,\n", + " target_modules=[\n", + " \"q\",\n", + " \"v\",\n", + " \"k\",\n", + " \"o\",\n", + " \"output_patch_embedding.output_layer\",\n", + " ],\n", + " # lora_dropout=0.1,\n", ")\n", "peft_callback = PeftCallback(peft_config=lora_config)\n", "\n", - "model = Chronos2Model(\n", - " input_chunk_length=12,\n", + "model_lora = Chronos2Model(\n", + " input_chunk_length=24,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=10,\n", - " pl_trainer_kwargs={\"callbacks\": [peft_callback]},\n", + " n_epochs=100,\n", + " pl_trainer_kwargs={\"accelerator\": \"gpu\", \"callbacks\": [peft_callback]},\n", + " log_tensorboard=True,\n", ")\n", - "model.fit(train_passengers, verbose=True)\n", + "model_lora.fit(train_passengers, verbose=True)\n", + "\n", + "# Fully save the model including adapters\n", + "model_lora.save(\"chronos2_lora_finetuned.pt\")\n", + "loaded = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")\n", + "# loaded_full = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")\n", "\n", - "# model.save(\"chronos2_lora_finetuned.pt\")\n", "# # Save adapters using PEFT's native method\n", "# model.model.model.save_pretrained(\"chronos2_lora_adapters/\")\n", "\n", - "# # === Loading ===\n", - "# # Use callback with adapter_path to load\n", - "# load_callback = PeftCallback(adapter_path=\"chronos2_lora_adapters/\")\n", - "\n", - "# loaded = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")\n", - "# loaded.fit(train_passengers[:1]) # Initialize model structure\n", - "# loaded.predict(n=12, series=train_passengers) # Adapters applied via on_predict_start" + "# # # === Loading ===\n", + "# model = Chronos2Model(\n", + "# input_chunk_length=12,\n", + "# output_chunk_length=6,\n", + "# enable_finetuning=True,\n", + "# n_epochs=10,\n", + "# pl_trainer_kwargs={\"callbacks\": [peft_callback]},\n", + "# )\n", + "# model.fit(train_passengers, verbose=True)\n", + "# model.model.model.load_adapter(\"chronos2_lora_adapters/\")" ] }, { "cell_type": "code", - "execution_count": 7, - "id": "2716abc4", + "execution_count": 6, + "id": "41e8a82f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "56b8b427e22348b19709bde1107f6367", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "model.save(\"chronos2_lora_finetuned.pt\")" + "pred_trained = model_lora.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + " random_state=42,\n", + ")\n", + "pred_loaded = loaded.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + " random_state=42,\n", + ")\n", + "val_passengers.plot(label=\"Ground truth\")\n", + "pred_trained.plot(label=\"Forecast of the trained model\")\n", + "pred_loaded.plot(label=\"Forecast of the loaded model\")" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "8122447b", + "execution_count": 8, + "id": "9a96ca55", "metadata": {}, "outputs": [ { - "ename": "RuntimeError", - "evalue": "Error(s) in loading state_dict for _Chronos2PLModule:\n\tMissing key(s) in state_dict: \"model.shared.weight\", \"model.input_patch_embedding.hidden_layer.weight\", \"model.input_patch_embedding.hidden_layer.bias\", \"model.input_patch_embedding.output_layer.weight\", \"model.input_patch_embedding.output_layer.bias\", \"model.input_patch_embedding.residual_layer.weight\", \"model.input_patch_embedding.residual_layer.bias\", \"model.encoder.block.0.layer.0.self_attention.q.weight\", \"model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.encoder.block.0.layer.0.self_attention.v.weight\", \"model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.encoder.block.0.layer.0.layer_norm.weight\", \"model.encoder.block.0.layer.1.self_attention.q.weight\", \"model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.encoder.block.0.layer.1.self_attention.v.weight\", \"model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.encoder.block.0.layer.1.layer_norm.weight\", \"model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.encoder.block.0.layer.2.layer_norm.weight\", \"model.encoder.block.1.layer.0.self_attention.q.weight\", \"model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.encoder.block.1.layer.0.self_attention.v.weight\", \"model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.encoder.block.1.layer.0.layer_norm.weight\", \"model.encoder.block.1.layer.1.self_attention.q.weight\", \"model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.encoder.block.1.layer.1.self_attention.v.weight\", \"model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.encoder.block.1.layer.1.layer_norm.weight\", \"model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.encoder.block.1.layer.2.layer_norm.weight\", \"model.encoder.block.2.layer.0.self_attention.q.weight\", \"model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.encoder.block.2.layer.0.self_attention.v.weight\", \"model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.encoder.block.2.layer.0.layer_norm.weight\", \"model.encoder.block.2.layer.1.self_attention.q.weight\", \"model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.encoder.block.2.layer.1.self_attention.v.weight\", \"model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.encoder.block.2.layer.1.layer_norm.weight\", \"model.encoder.block.2.layer.2.mlp.wi.weight\", \"model.encoder.block.2.layer.2.mlp.wo.weight\", \"model.encoder.block.2.layer.2.layer_norm.weight\", \"model.encoder.block.3.layer.0.self_attention.q.weight\", \"model.encoder.block.3.layer.0.self_attention.k.weight\", \"model.encoder.block.3.layer.0.self_attention.v.weight\", \"model.encoder.block.3.layer.0.self_attention.o.weight\", \"model.encoder.block.3.layer.0.layer_norm.weight\", \"model.encoder.block.3.layer.1.self_attention.q.weight\", \"model.encoder.block.3.layer.1.self_attention.k.weight\", \"model.encoder.block.3.layer.1.self_attention.v.weight\", \"model.encoder.block.3.layer.1.self_attention.o.weight\", \"model.encoder.block.3.layer.1.layer_norm.weight\", \"model.encoder.block.3.layer.2.mlp.wi.weight\", \"model.encoder.block.3.layer.2.mlp.wo.weight\", \"model.encoder.block.3.layer.2.layer_norm.weight\", \"model.encoder.block.4.layer.0.self_attention.q.weight\", \"model.encoder.block.4.layer.0.self_attention.k.weight\", \"model.encoder.block.4.layer.0.self_attention.v.weight\", \"model.encoder.block.4.layer.0.self_attention.o.weight\", \"model.encoder.block.4.layer.0.layer_norm.weight\", \"model.encoder.block.4.layer.1.self_attention.q.weight\", \"model.encoder.block.4.layer.1.self_attention.k.weight\", \"model.encoder.block.4.layer.1.self_attention.v.weight\", \"model.encoder.block.4.layer.1.self_attention.o.weight\", \"model.encoder.block.4.layer.1.layer_norm.weight\", \"model.encoder.block.4.layer.2.mlp.wi.weight\", \"model.encoder.block.4.layer.2.mlp.wo.weight\", \"model.encoder.block.4.layer.2.layer_norm.weight\", \"model.encoder.block.5.layer.0.self_attention.q.weight\", \"model.encoder.block.5.layer.0.self_attention.k.weight\", \"model.encoder.block.5.layer.0.self_attention.v.weight\", \"model.encoder.block.5.layer.0.self_attention.o.weight\", \"model.encoder.block.5.layer.0.layer_norm.weight\", \"model.encoder.block.5.layer.1.self_attention.q.weight\", \"model.encoder.block.5.layer.1.self_attention.k.weight\", \"model.encoder.block.5.layer.1.self_attention.v.weight\", \"model.encoder.block.5.layer.1.self_attention.o.weight\", \"model.encoder.block.5.layer.1.layer_norm.weight\", \"model.encoder.block.5.layer.2.mlp.wi.weight\", \"model.encoder.block.5.layer.2.mlp.wo.weight\", \"model.encoder.block.5.layer.2.layer_norm.weight\", \"model.encoder.block.6.layer.0.self_attention.q.weight\", \"model.encoder.block.6.layer.0.self_attention.k.weight\", \"model.encoder.block.6.layer.0.self_attention.v.weight\", \"model.encoder.block.6.layer.0.self_attention.o.weight\", \"model.encoder.block.6.layer.0.layer_norm.weight\", \"model.encoder.block.6.layer.1.self_attention.q.weight\", \"model.encoder.block.6.layer.1.self_attention.k.weight\", \"model.encoder.block.6.layer.1.self_attention.v.weight\", \"model.encoder.block.6.layer.1.self_attention.o.weight\", \"model.encoder.block.6.layer.1.layer_norm.weight\", \"model.encoder.block.6.layer.2.mlp.wi.weight\", \"model.encoder.block.6.layer.2.mlp.wo.weight\", \"model.encoder.block.6.layer.2.layer_norm.weight\", \"model.encoder.block.7.layer.0.self_attention.q.weight\", \"model.encoder.block.7.layer.0.self_attention.k.weight\", \"model.encoder.block.7.layer.0.self_attention.v.weight\", \"model.encoder.block.7.layer.0.self_attention.o.weight\", \"model.encoder.block.7.layer.0.layer_norm.weight\", \"model.encoder.block.7.layer.1.self_attention.q.weight\", \"model.encoder.block.7.layer.1.self_attention.k.weight\", \"model.encoder.block.7.layer.1.self_attention.v.weight\", \"model.encoder.block.7.layer.1.self_attention.o.weight\", \"model.encoder.block.7.layer.1.layer_norm.weight\", \"model.encoder.block.7.layer.2.mlp.wi.weight\", \"model.encoder.block.7.layer.2.mlp.wo.weight\", \"model.encoder.block.7.layer.2.layer_norm.weight\", \"model.encoder.block.8.layer.0.self_attention.q.weight\", \"model.encoder.block.8.layer.0.self_attention.k.weight\", \"model.encoder.block.8.layer.0.self_attention.v.weight\", \"model.encoder.block.8.layer.0.self_attention.o.weight\", \"model.encoder.block.8.layer.0.layer_norm.weight\", \"model.encoder.block.8.layer.1.self_attention.q.weight\", \"model.encoder.block.8.layer.1.self_attention.k.weight\", \"model.encoder.block.8.layer.1.self_attention.v.weight\", \"model.encoder.block.8.layer.1.self_attention.o.weight\", \"model.encoder.block.8.layer.1.layer_norm.weight\", \"model.encoder.block.8.layer.2.mlp.wi.weight\", \"model.encoder.block.8.layer.2.mlp.wo.weight\", \"model.encoder.block.8.layer.2.layer_norm.weight\", \"model.encoder.block.9.layer.0.self_attention.q.weight\", \"model.encoder.block.9.layer.0.self_attention.k.weight\", \"model.encoder.block.9.layer.0.self_attention.v.weight\", \"model.encoder.block.9.layer.0.self_attention.o.weight\", \"model.encoder.block.9.layer.0.layer_norm.weight\", \"model.encoder.block.9.layer.1.self_attention.q.weight\", \"model.encoder.block.9.layer.1.self_attention.k.weight\", \"model.encoder.block.9.layer.1.self_attention.v.weight\", \"model.encoder.block.9.layer.1.self_attention.o.weight\", \"model.encoder.block.9.layer.1.layer_norm.weight\", \"model.encoder.block.9.layer.2.mlp.wi.weight\", \"model.encoder.block.9.layer.2.mlp.wo.weight\", \"model.encoder.block.9.layer.2.layer_norm.weight\", \"model.encoder.block.10.layer.0.self_attention.q.weight\", \"model.encoder.block.10.layer.0.self_attention.k.weight\", \"model.encoder.block.10.layer.0.self_attention.v.weight\", \"model.encoder.block.10.layer.0.self_attention.o.weight\", \"model.encoder.block.10.layer.0.layer_norm.weight\", \"model.encoder.block.10.layer.1.self_attention.q.weight\", \"model.encoder.block.10.layer.1.self_attention.k.weight\", \"model.encoder.block.10.layer.1.self_attention.v.weight\", \"model.encoder.block.10.layer.1.self_attention.o.weight\", \"model.encoder.block.10.layer.1.layer_norm.weight\", \"model.encoder.block.10.layer.2.mlp.wi.weight\", \"model.encoder.block.10.layer.2.mlp.wo.weight\", \"model.encoder.block.10.layer.2.layer_norm.weight\", \"model.encoder.block.11.layer.0.self_attention.q.weight\", \"model.encoder.block.11.layer.0.self_attention.k.weight\", \"model.encoder.block.11.layer.0.self_attention.v.weight\", \"model.encoder.block.11.layer.0.self_attention.o.weight\", \"model.encoder.block.11.layer.0.layer_norm.weight\", \"model.encoder.block.11.layer.1.self_attention.q.weight\", \"model.encoder.block.11.layer.1.self_attention.k.weight\", \"model.encoder.block.11.layer.1.self_attention.v.weight\", \"model.encoder.block.11.layer.1.self_attention.o.weight\", \"model.encoder.block.11.layer.1.layer_norm.weight\", \"model.encoder.block.11.layer.2.mlp.wi.weight\", \"model.encoder.block.11.layer.2.mlp.wo.weight\", \"model.encoder.block.11.layer.2.layer_norm.weight\", \"model.encoder.final_layer_norm.weight\", \"model.output_patch_embedding.hidden_layer.weight\", \"model.output_patch_embedding.hidden_layer.bias\", \"model.output_patch_embedding.output_layer.weight\", \"model.output_patch_embedding.output_layer.bias\", \"model.output_patch_embedding.residual_layer.weight\", \"model.output_patch_embedding.residual_layer.bias\". \n\tUnexpected key(s) in state_dict: \"model.base_model.model.shared.weight\", \"model.base_model.model.input_patch_embedding.hidden_layer.weight\", \"model.base_model.model.input_patch_embedding.hidden_layer.bias\", \"model.base_model.model.input_patch_embedding.output_layer.weight\", \"model.base_model.model.input_patch_embedding.output_layer.bias\", \"model.base_model.model.input_patch_embedding.residual_layer.weight\", \"model.base_model.model.input_patch_embedding.residual_layer.bias\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.0.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.0.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.0.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.1.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.1.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.1.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.2.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.2.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.2.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.2.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.3.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.3.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.3.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.3.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.3.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.v.lora_B.default.weight\", 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", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m loaded \u001b[38;5;241m=\u001b[39m \u001b[43mChronos2Model\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mchronos2_lora_finetuned.pt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpl_trainer_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcallbacks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mpeft_callback\u001b[49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/Projects/Darts/darts/darts/models/forecasting/torch_forecasting_model.py:2072\u001b[0m, in \u001b[0;36mTorchForecastingModel.load\u001b[0;34m(path, pl_trainer_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 2070\u001b[0m path_ptl_ckpt \u001b[38;5;241m=\u001b[39m path \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.ckpt\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 2071\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mexists(path_ptl_ckpt):\n\u001b[0;32m-> 2072\u001b[0m model\u001b[38;5;241m.\u001b[39mmodel \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_load_from_checkpoint\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath_ptl_ckpt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2073\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 2074\u001b[0m model\u001b[38;5;241m.\u001b[39m_fit_called \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n", - "File \u001b[0;32m~/Projects/Darts/darts/darts/models/forecasting/torch_forecasting_model.py:2204\u001b[0m, in \u001b[0;36mTorchForecastingModel._load_from_checkpoint\u001b[0;34m(self, file_path, **kwargs)\u001b[0m\n\u001b[1;32m 2198\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Loads a checkpoint for the underlying :class:`PLForecastingModule` (PLM) model.\u001b[39;00m\n\u001b[1;32m 2199\u001b[0m \u001b[38;5;124;03mThe PLM object is not stored when saving a :class:`TorchForecastingModel` (TFM) to avoid saving\u001b[39;00m\n\u001b[1;32m 2200\u001b[0m \u001b[38;5;124;03mthe model twice. Instead, we recover the module class with the module path and class name stored\u001b[39;00m\n\u001b[1;32m 2201\u001b[0m \u001b[38;5;124;03min the TFM object. With the recovered module class, we can load the checkpoint.\u001b[39;00m\n\u001b[1;32m 2202\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 2203\u001b[0m pl_module_cls \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(sys\u001b[38;5;241m.\u001b[39mmodules[\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_module_path], \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_module_name)\n\u001b[0;32m-> 2204\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mpl_module_cls\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_from_checkpoint\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfile_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/utilities/model_helpers.py:125\u001b[0m, in \u001b[0;36m_restricted_classmethod_impl.__get__..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m instance \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_scripting:\n\u001b[1;32m 121\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m 122\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe classmethod `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmethod\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` cannot be called on an instance.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 123\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m Please call it on the class type and make sure the return value is used.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 124\u001b[0m )\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmethod\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/core/module.py:1611\u001b[0m, in \u001b[0;36mLightningModule.load_from_checkpoint\u001b[0;34m(cls, checkpoint_path, map_location, hparams_file, strict, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[38;5;129m@_restricted_classmethod\u001b[39m\n\u001b[1;32m 1523\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mload_from_checkpoint\u001b[39m(\n\u001b[1;32m 1524\u001b[0m \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1529\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 1530\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Self:\n\u001b[1;32m 1531\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124;03m\"\"\"Primary way of loading a model from a checkpoint. When Lightning saves a checkpoint it stores the arguments\u001b[39;00m\n\u001b[1;32m 1532\u001b[0m \u001b[38;5;124;03m passed to ``__init__`` in the checkpoint under ``\"hyper_parameters\"``.\u001b[39;00m\n\u001b[1;32m 1533\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1609\u001b[0m \n\u001b[1;32m 1610\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m-> 1611\u001b[0m loaded \u001b[38;5;241m=\u001b[39m \u001b[43m_load_from_checkpoint\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1612\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1613\u001b[0m \u001b[43m \u001b[49m\u001b[43mcheckpoint_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1614\u001b[0m \u001b[43m \u001b[49m\u001b[43mmap_location\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1615\u001b[0m \u001b[43m \u001b[49m\u001b[43mhparams_file\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1616\u001b[0m \u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1617\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1618\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1619\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cast(Self, loaded)\n", - "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/core/saving.py:91\u001b[0m, in \u001b[0;36m_load_from_checkpoint\u001b[0;34m(cls, checkpoint_path, map_location, hparams_file, strict, **kwargs)\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _load_state(\u001b[38;5;28mcls\u001b[39m, checkpoint, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28missubclass\u001b[39m(\u001b[38;5;28mcls\u001b[39m, pl\u001b[38;5;241m.\u001b[39mLightningModule):\n\u001b[0;32m---> 91\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43m_load_state\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcheckpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstrict\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 92\u001b[0m state_dict \u001b[38;5;241m=\u001b[39m checkpoint[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstate_dict\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 93\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m state_dict:\n", - "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/pytorch_lightning/core/saving.py:187\u001b[0m, in \u001b[0;36m_load_state\u001b[0;34m(cls, checkpoint, strict, **cls_kwargs_new)\u001b[0m\n\u001b[1;32m 184\u001b[0m obj\u001b[38;5;241m.\u001b[39mon_load_checkpoint(checkpoint)\n\u001b[1;32m 186\u001b[0m \u001b[38;5;66;03m# load the state_dict on the model automatically\u001b[39;00m\n\u001b[0;32m--> 187\u001b[0m keys \u001b[38;5;241m=\u001b[39m \u001b[43mobj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_state_dict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcheckpoint\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstate_dict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstrict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstrict\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore[arg-type]\u001b[39;00m\n\u001b[1;32m 189\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m strict:\n\u001b[1;32m 190\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m keys\u001b[38;5;241m.\u001b[39mmissing_keys:\n", - "File \u001b[0;32m~/anaconda3/envs/darts/lib/python3.13/site-packages/torch/nn/modules/module.py:2624\u001b[0m, in \u001b[0;36mModule.load_state_dict\u001b[0;34m(self, state_dict, strict, assign)\u001b[0m\n\u001b[1;32m 2616\u001b[0m error_msgs\u001b[38;5;241m.\u001b[39minsert(\n\u001b[1;32m 2617\u001b[0m \u001b[38;5;241m0\u001b[39m,\n\u001b[1;32m 2618\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMissing key(s) in state_dict: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 2619\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mk\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m missing_keys)\n\u001b[1;32m 2620\u001b[0m ),\n\u001b[1;32m 2621\u001b[0m )\n\u001b[1;32m 2623\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(error_msgs) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 2624\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 2625\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError(s) in loading state_dict for \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m 2626\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\t\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(error_msgs)\n\u001b[1;32m 2627\u001b[0m )\n\u001b[1;32m 2628\u001b[0m )\n\u001b[1;32m 2629\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _IncompatibleKeys(missing_keys, unexpected_keys)\n", - "\u001b[0;31mRuntimeError\u001b[0m: Error(s) in loading state_dict for _Chronos2PLModule:\n\tMissing key(s) in state_dict: \"model.shared.weight\", \"model.input_patch_embedding.hidden_layer.weight\", \"model.input_patch_embedding.hidden_layer.bias\", \"model.input_patch_embedding.output_layer.weight\", \"model.input_patch_embedding.output_layer.bias\", \"model.input_patch_embedding.residual_layer.weight\", \"model.input_patch_embedding.residual_layer.bias\", \"model.encoder.block.0.layer.0.self_attention.q.weight\", \"model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.encoder.block.0.layer.0.self_attention.v.weight\", \"model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.encoder.block.0.layer.0.layer_norm.weight\", \"model.encoder.block.0.layer.1.self_attention.q.weight\", \"model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.encoder.block.0.layer.1.self_attention.v.weight\", \"model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.encoder.block.0.layer.1.layer_norm.weight\", \"model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.encoder.block.0.layer.2.layer_norm.weight\", \"model.encoder.block.1.layer.0.self_attention.q.weight\", \"model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.encoder.block.1.layer.0.self_attention.v.weight\", \"model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.encoder.block.1.layer.0.layer_norm.weight\", \"model.encoder.block.1.layer.1.self_attention.q.weight\", \"model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.encoder.block.1.layer.1.self_attention.v.weight\", \"model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.encoder.block.1.layer.1.layer_norm.weight\", \"model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.encoder.block.1.layer.2.layer_norm.weight\", \"model.encoder.block.2.layer.0.self_attention.q.weight\", \"model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.encoder.block.2.layer.0.self_attention.v.weight\", \"model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.encoder.block.2.layer.0.layer_norm.weight\", \"model.encoder.block.2.layer.1.self_attention.q.weight\", \"model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.encoder.block.2.layer.1.self_attention.v.weight\", \"model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.encoder.block.2.layer.1.layer_norm.weight\", \"model.encoder.block.2.layer.2.mlp.wi.weight\", \"model.encoder.block.2.layer.2.mlp.wo.weight\", \"model.encoder.block.2.layer.2.layer_norm.weight\", \"model.encoder.block.3.layer.0.self_attention.q.weight\", \"model.encoder.block.3.layer.0.self_attention.k.weight\", \"model.encoder.block.3.layer.0.self_attention.v.weight\", \"model.encoder.block.3.layer.0.self_attention.o.weight\", \"model.encoder.block.3.layer.0.layer_norm.weight\", \"model.encoder.block.3.layer.1.self_attention.q.weight\", \"model.encoder.block.3.layer.1.self_attention.k.weight\", \"model.encoder.block.3.layer.1.self_attention.v.weight\", \"model.encoder.block.3.layer.1.self_attention.o.weight\", \"model.encoder.block.3.layer.1.layer_norm.weight\", \"model.encoder.block.3.layer.2.mlp.wi.weight\", \"model.encoder.block.3.layer.2.mlp.wo.weight\", \"model.encoder.block.3.layer.2.layer_norm.weight\", \"model.encoder.block.4.layer.0.self_attention.q.weight\", \"model.encoder.block.4.layer.0.self_attention.k.weight\", \"model.encoder.block.4.layer.0.self_attention.v.weight\", \"model.encoder.block.4.layer.0.self_attention.o.weight\", \"model.encoder.block.4.layer.0.layer_norm.weight\", \"model.encoder.block.4.layer.1.self_attention.q.weight\", \"model.encoder.block.4.layer.1.self_attention.k.weight\", \"model.encoder.block.4.layer.1.self_attention.v.weight\", \"model.encoder.block.4.layer.1.self_attention.o.weight\", \"model.encoder.block.4.layer.1.layer_norm.weight\", \"model.encoder.block.4.layer.2.mlp.wi.weight\", \"model.encoder.block.4.layer.2.mlp.wo.weight\", \"model.encoder.block.4.layer.2.layer_norm.weight\", \"model.encoder.block.5.layer.0.self_attention.q.weight\", \"model.encoder.block.5.layer.0.self_attention.k.weight\", \"model.encoder.block.5.layer.0.self_attention.v.weight\", \"model.encoder.block.5.layer.0.self_attention.o.weight\", \"model.encoder.block.5.layer.0.layer_norm.weight\", \"model.encoder.block.5.layer.1.self_attention.q.weight\", \"model.encoder.block.5.layer.1.self_attention.k.weight\", \"model.encoder.block.5.layer.1.self_attention.v.weight\", \"model.encoder.block.5.layer.1.self_attention.o.weight\", \"model.encoder.block.5.layer.1.layer_norm.weight\", \"model.encoder.block.5.layer.2.mlp.wi.weight\", \"model.encoder.block.5.layer.2.mlp.wo.weight\", \"model.encoder.block.5.layer.2.layer_norm.weight\", \"model.encoder.block.6.layer.0.self_attention.q.weight\", \"model.encoder.block.6.layer.0.self_attention.k.weight\", \"model.encoder.block.6.layer.0.self_attention.v.weight\", \"model.encoder.block.6.layer.0.self_attention.o.weight\", \"model.encoder.block.6.layer.0.layer_norm.weight\", \"model.encoder.block.6.layer.1.self_attention.q.weight\", \"model.encoder.block.6.layer.1.self_attention.k.weight\", \"model.encoder.block.6.layer.1.self_attention.v.weight\", \"model.encoder.block.6.layer.1.self_attention.o.weight\", \"model.encoder.block.6.layer.1.layer_norm.weight\", \"model.encoder.block.6.layer.2.mlp.wi.weight\", \"model.encoder.block.6.layer.2.mlp.wo.weight\", \"model.encoder.block.6.layer.2.layer_norm.weight\", \"model.encoder.block.7.layer.0.self_attention.q.weight\", \"model.encoder.block.7.layer.0.self_attention.k.weight\", \"model.encoder.block.7.layer.0.self_attention.v.weight\", \"model.encoder.block.7.layer.0.self_attention.o.weight\", \"model.encoder.block.7.layer.0.layer_norm.weight\", \"model.encoder.block.7.layer.1.self_attention.q.weight\", \"model.encoder.block.7.layer.1.self_attention.k.weight\", \"model.encoder.block.7.layer.1.self_attention.v.weight\", \"model.encoder.block.7.layer.1.self_attention.o.weight\", \"model.encoder.block.7.layer.1.layer_norm.weight\", \"model.encoder.block.7.layer.2.mlp.wi.weight\", \"model.encoder.block.7.layer.2.mlp.wo.weight\", \"model.encoder.block.7.layer.2.layer_norm.weight\", \"model.encoder.block.8.layer.0.self_attention.q.weight\", \"model.encoder.block.8.layer.0.self_attention.k.weight\", \"model.encoder.block.8.layer.0.self_attention.v.weight\", \"model.encoder.block.8.layer.0.self_attention.o.weight\", \"model.encoder.block.8.layer.0.layer_norm.weight\", \"model.encoder.block.8.layer.1.self_attention.q.weight\", \"model.encoder.block.8.layer.1.self_attention.k.weight\", \"model.encoder.block.8.layer.1.self_attention.v.weight\", \"model.encoder.block.8.layer.1.self_attention.o.weight\", \"model.encoder.block.8.layer.1.layer_norm.weight\", \"model.encoder.block.8.layer.2.mlp.wi.weight\", \"model.encoder.block.8.layer.2.mlp.wo.weight\", \"model.encoder.block.8.layer.2.layer_norm.weight\", \"model.encoder.block.9.layer.0.self_attention.q.weight\", \"model.encoder.block.9.layer.0.self_attention.k.weight\", \"model.encoder.block.9.layer.0.self_attention.v.weight\", \"model.encoder.block.9.layer.0.self_attention.o.weight\", \"model.encoder.block.9.layer.0.layer_norm.weight\", \"model.encoder.block.9.layer.1.self_attention.q.weight\", \"model.encoder.block.9.layer.1.self_attention.k.weight\", \"model.encoder.block.9.layer.1.self_attention.v.weight\", \"model.encoder.block.9.layer.1.self_attention.o.weight\", \"model.encoder.block.9.layer.1.layer_norm.weight\", \"model.encoder.block.9.layer.2.mlp.wi.weight\", \"model.encoder.block.9.layer.2.mlp.wo.weight\", \"model.encoder.block.9.layer.2.layer_norm.weight\", \"model.encoder.block.10.layer.0.self_attention.q.weight\", \"model.encoder.block.10.layer.0.self_attention.k.weight\", \"model.encoder.block.10.layer.0.self_attention.v.weight\", \"model.encoder.block.10.layer.0.self_attention.o.weight\", \"model.encoder.block.10.layer.0.layer_norm.weight\", \"model.encoder.block.10.layer.1.self_attention.q.weight\", \"model.encoder.block.10.layer.1.self_attention.k.weight\", \"model.encoder.block.10.layer.1.self_attention.v.weight\", \"model.encoder.block.10.layer.1.self_attention.o.weight\", \"model.encoder.block.10.layer.1.layer_norm.weight\", \"model.encoder.block.10.layer.2.mlp.wi.weight\", \"model.encoder.block.10.layer.2.mlp.wo.weight\", \"model.encoder.block.10.layer.2.layer_norm.weight\", \"model.encoder.block.11.layer.0.self_attention.q.weight\", \"model.encoder.block.11.layer.0.self_attention.k.weight\", \"model.encoder.block.11.layer.0.self_attention.v.weight\", \"model.encoder.block.11.layer.0.self_attention.o.weight\", \"model.encoder.block.11.layer.0.layer_norm.weight\", \"model.encoder.block.11.layer.1.self_attention.q.weight\", \"model.encoder.block.11.layer.1.self_attention.k.weight\", \"model.encoder.block.11.layer.1.self_attention.v.weight\", \"model.encoder.block.11.layer.1.self_attention.o.weight\", \"model.encoder.block.11.layer.1.layer_norm.weight\", \"model.encoder.block.11.layer.2.mlp.wi.weight\", \"model.encoder.block.11.layer.2.mlp.wo.weight\", \"model.encoder.block.11.layer.2.layer_norm.weight\", \"model.encoder.final_layer_norm.weight\", \"model.output_patch_embedding.hidden_layer.weight\", \"model.output_patch_embedding.hidden_layer.bias\", \"model.output_patch_embedding.output_layer.weight\", \"model.output_patch_embedding.output_layer.bias\", \"model.output_patch_embedding.residual_layer.weight\", \"model.output_patch_embedding.residual_layer.bias\". \n\tUnexpected key(s) in state_dict: \"model.base_model.model.shared.weight\", \"model.base_model.model.input_patch_embedding.hidden_layer.weight\", \"model.base_model.model.input_patch_embedding.hidden_layer.bias\", \"model.base_model.model.input_patch_embedding.output_layer.weight\", \"model.base_model.model.input_patch_embedding.output_layer.bias\", \"model.base_model.model.input_patch_embedding.residual_layer.weight\", \"model.base_model.model.input_patch_embedding.residual_layer.bias\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.0.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.0.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.0.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.0.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.0.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.0.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.1.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.1.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.1.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.1.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.1.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.1.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.2.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.2.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.2.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.2.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.2.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.2.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.3.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.3.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.3.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.3.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.3.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.3.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.4.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.4.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.4.layer.1.self_attention.o.weight\", \"model.base_model.model.encoder.block.4.layer.1.layer_norm.weight\", \"model.base_model.model.encoder.block.4.layer.2.mlp.wi.weight\", \"model.base_model.model.encoder.block.4.layer.2.mlp.wo.weight\", \"model.base_model.model.encoder.block.4.layer.2.layer_norm.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.k.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.v.base_layer.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.v.lora_A.default.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.v.lora_B.default.weight\", \"model.base_model.model.encoder.block.5.layer.0.self_attention.o.weight\", \"model.base_model.model.encoder.block.5.layer.0.layer_norm.weight\", \"model.base_model.model.encoder.block.5.layer.1.self_attention.q.base_layer.weight\", \"model.base_model.model.encoder.block.5.layer.1.self_attention.q.lora_A.default.weight\", \"model.base_model.model.encoder.block.5.layer.1.self_attention.q.lora_B.default.weight\", \"model.base_model.model.encoder.block.5.layer.1.self_attention.k.weight\", \"model.base_model.model.encoder.block.5.layer.1.self_attention.v.base_layer.weight\", 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" - ] + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ - "loaded = Chronos2Model.load(\n", - " \"chronos2_lora_finetuned.pt\", pl_trainer_kwargs={\"callbacks\": [peft_callback]}\n", - ")" + "np.allclose(pred_trained.values(), pred_loaded.values())" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "id": "527ad900", + "metadata": {}, + "outputs": [], + "source": [ + "import torch\n", + "\n", + "model_without_lora = model_lora.model.model.merge_and_unload()\n", + "\n", + "assert len(loaded.model.state_dict().keys()) == len(\n", + " model_without_lora.state_dict().keys()\n", + ")\n", + "\n", + "for key_loaded, key_lora in zip(\n", + " loaded.model.state_dict().keys(), model_without_lora.state_dict().keys()\n", + "):\n", + " assert torch.equal(\n", + " loaded.model.state_dict()[key_loaded], model_without_lora.state_dict()[key_lora]\n", + " )" ] }, { "cell_type": "code", "execution_count": null, - "id": "a7a64516", + "id": "ce2fcd82", "metadata": {}, "outputs": [], "source": [] @@ -501,7 +672,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.7" + "version": "3.12.12" } }, "nbformat": 4, From eeb93b4a9cd73177935e38433c02bc3b9d44f667 Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Mon, 19 Jan 2026 15:36:46 +0100 Subject: [PATCH 06/11] fix: improve callbacks to allow only saving the adapter --- darts/models/forecasting/foundation_model.py | 112 +++-- .../26-Chronos-2-finetuning-examples.ipynb | 417 +++++++++++++----- 2 files changed, 389 insertions(+), 140 deletions(-) diff --git a/darts/models/forecasting/foundation_model.py b/darts/models/forecasting/foundation_model.py index b526b4aee0..b77d17fc49 100644 --- a/darts/models/forecasting/foundation_model.py +++ b/darts/models/forecasting/foundation_model.py @@ -199,6 +199,27 @@ def internal_model(self) -> Any: return self.model.model return None + @internal_model.setter + def internal_model(self, model: nn.Module): + """ + Sets the underlying PyTorch model (nn.Module). + This allows replacing the internal model, which can be useful for advanced usage like loading PEFT adapters. + + Parameters + ---------- + model + The new PyTorch nn.Module to set as the internal model. + """ + if hasattr(self, "model"): + self.model.model = model + else: + raise_log( + AttributeError( + "The internal model cannot be set because the outer model is not initialized yet." + ), + logger, + ) + class FoundationPLModule(PLForecastingModule): def __init__(self, **kwargs): @@ -211,10 +232,30 @@ def __init__( self, transform_fn: Callable[[nn.Module], nn.Module], model_attribute: str = "model", + verbose: bool = False, ): + """ + A PyTorch Lightning callback that applies a transformation function to an internal model + within a LightningModule. + + This is useful for modifying model architectures (e.g., applying PEFT or freezing layers) + just before the training starts, while ensuring the transformation is correctly handled + during checkpoint saving and loading. + + Parameters + ---------- + transform_fn + A function that takes an ``nn.Module`` and returns a transformed ``nn.Module``. + model_attribute + The attribute name of the model within the LightningModule. Default: ``"model"``. + verbose + Whether to log information about the model transformation, such as the number of + trainable parameters. Default: ``False``. + """ super().__init__() self.transform_fn = transform_fn self.model_attribute = model_attribute + self.verbose = verbose self._transformed = False def _get_inner_model(self, pl_module: pl.LightningModule) -> nn.Module: @@ -232,15 +273,15 @@ def setup(self, trainer: pl.Trainer, pl_module: pl.LightningModule, stage: str): transformed_model = self.transform_fn(inner_model) self._set_inner_model(pl_module, transformed_model) self._transformed = True - - # Log trainable parameters - trainable = sum( - p.numel() for p in pl_module.parameters() if p.requires_grad - ) - total = sum(p.numel() for p in pl_module.parameters()) - print( - f"Model transformed. Trainable: {trainable:,}/{total:,} ({100 * trainable / total:.2f}%)" - ) + if self.verbose: + # Log trainable parameters + trainable = sum( + p.numel() for p in pl_module.parameters() if p.requires_grad + ) + total = sum(p.numel() for p in pl_module.parameters()) + logger.info( + f"Model transformed. Trainable: {trainable:,}/{total:,} ({100 * trainable / total:.2f}%)" + ) def on_save_checkpoint( self, @@ -292,7 +333,24 @@ def __init__( freeze_patterns: list[str], unfreeze_patterns: list[str] = None, model_attribute: str = "model", + verbose: bool = False, ): + """ + A callback to freeze or unfreeze specific layers of a model based on name patterns. + + Parameters + ---------- + freeze_patterns + A list of strings. Parameters whose names start with any of these patterns will be frozen + (``requires_grad=False``). + unfreeze_patterns + A list of strings. Parameters whose names start with any of these patterns will be unfrozen + (``requires_grad=True``). This is applied after ``freeze_patterns``. Default: ``None``. + model_attribute + The attribute name of the model within the LightningModule. Default: ``"model"``. + verbose + Whether to log the trainable parameter count after freezing. Default: ``False``. + """ unfreeze_patterns = unfreeze_patterns or [] super().__init__( @@ -302,6 +360,7 @@ def __init__( unfreeze_patterns=unfreeze_patterns, ), model_attribute=model_attribute, + verbose=verbose, ) @@ -321,10 +380,27 @@ def __init__( self, peft_config=None, model_attribute: str = "model", + verbose: bool = False, ): + """ + A callback to apply Parameter-Efficient Fine-Tuning (PEFT) to a model using the ``peft`` library. + + It wraps the internal model with a PEFT adapter (e.g., LoRA) and manages the merging of + weights during checkpointing so that the saved state can be loaded as a standard model. + + Parameters + ---------- + peft_config + A PEFT configuration object (e.g., ``LoraConfig``) from the ``peft`` library. + model_attribute + The attribute name of the model within the LightningModule. Default: ``"model"``. + verbose + Whether to log the trainable parameter count after applying PEFT. Default: ``False``. + """ super().__init__( transform_fn=partial(self._apply_peft, peft_config=peft_config), model_attribute=model_attribute, + verbose=verbose, ) self.peft_config = peft_config @@ -339,6 +415,7 @@ def on_save_checkpoint(self, trainer, pl_module, checkpoint): if isinstance(peft_model, PeftModel): # Merge adapters into the base model weights + # TODO: This might be inefficient for large models, think about a better way model_copy = deepcopy(peft_model) setattr(pl_module, self.model_attribute, peft_model.merge_and_unload()) try: @@ -356,24 +433,9 @@ def on_save_checkpoint(self, trainer, pl_module, checkpoint): .items() } - # # Update the checkpoint + # Update the checkpoint checkpoint["state_dict"] = new_state_dict - # Remove "peft_applied" so that on_load_checkpoint() does not try to re-wrap the model - # This allows loading the model as a regular (non-PEFT) model - checkpoint.pop("peft_applied", None) - checkpoint.pop("peft_config", None) - finally: # Unmerge adapters to keep the current model in PEFT mode setattr(pl_module, self.model_attribute, model_copy) - - def on_load_checkpoint( - self, - trainer: pl.Trainer, - pl_module: pl.LightningModule, - checkpoint: dict[str, Any], - ): - """Apply PEFT structure before loading weights.""" - if checkpoint.get("peft_applied", False): - self._apply_peft(pl_module, peft_config=self.peft_config) diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index 50fc3d1e3b..a413b4ad76 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -5,7 +5,15 @@ "id": "da55dd6c", "metadata": {}, "source": [ - "# Chronos-2 Foundation Model Fine-Tuning" + "# Chronos-2 Foundation Model Fine-Tuning\n", + "This example notebook presents how fine-tuning can be applied to the Chronos-2 model.\n", + "\n", + "The following fine-tuning methods will be shown:\n", + "1) Full fine-tuning : all the models weights will be retrained\n", + "2) Partial fine-tuning : some layers of the model will be frozen\n", + "3) PEFT fine-tuning : the HuggingFace peft library will be used to apply LoRA fine-tuning (requires `pip install peft` since it is not a darts dependency)\n", + "\n", + "To be useful, a fine-tuned model should be easily saved and loaded. For each fine-tuning method, how to save and load the model will be shown with an example (straightforward for (1) and (2), slightly different for (3))" ] }, { @@ -58,7 +66,8 @@ "id": "6b82a07a", "metadata": {}, "source": [ - "## Data Preparation" + "## Data Preparation\n", + "Here we just load an example dataset with 144 samples as a fast demo. The data is split between train and validation, with the 2 last years (24 samples) for validation" ] }, { @@ -89,14 +98,14 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 5, "id": "ea8456ae", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a08b5ab19e164a3086e0a3bf59c7f2c3", + "model_id": "426a22d045d34b1a842eec9a09e6302a", "version_major": 2, "version_minor": 0 }, @@ -113,7 +122,7 @@ "" ] }, - "execution_count": 13, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, @@ -148,23 +157,23 @@ "id": "1313019f", "metadata": {}, "source": [ - "# Full fine-tuning\n", + "# 1. Full fine-tuning\n", "\n", "In this method, all the model weights are retrained. This is done with `enable_finetuning=True` in the model constructor.\n", "\n", - "The model is saved then loaded to show that Darts model saving and restoration continue to work with the different fine-tuning methods" + "The model is saved and loaded with the usual `save` and `load` methods, so the behavior is the same as other darts models." ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "id": "72832dff", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c73e0b0c4ed942a0b8c1c3915d6de446", + "model_id": "f706e79ab1704fea9809dae3e7db1b78", "version_major": 2, "version_minor": 0 }, @@ -177,30 +186,38 @@ } ], "source": [ - "model = Chronos2Model(\n", + "full_finetuned_model = Chronos2Model(\n", " input_chunk_length=24,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=100,\n", + " n_epochs=50,\n", " pl_trainer_kwargs={\"accelerator\": \"gpu\"},\n", ")\n", - "model.fit(train_passengers, verbose=True)\n", - "model.save(\"full_finetuned.pt\")\n", + "full_finetuned_model.fit(train_passengers, verbose=True)\n", + "full_finetuned_model.save(\"full_finetuned.pt\")\n", "\n", "# Load\n", - "loaded = Chronos2Model.load(\"full_finetuned.pt\")" + "full_finetuned_loaded_model = Chronos2Model.load(\"full_finetuned.pt\")" + ] + }, + { + "cell_type": "markdown", + "id": "ba806d95", + "metadata": {}, + "source": [ + "We can compare the prediction with the ground truth, as well as checking that the loaded model behaves similarly to the fine-tuned model." ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "id": "9bbd219e", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "607d823d5a9f436289c2a9d8789c21a0", + "model_id": "467be790d94d48b09ea2ad2de1567125", "version_major": 2, "version_minor": 0 }, @@ -214,7 +231,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9815ecb465814e6b8f484402b3cb5f0d", + "model_id": "fb68e0d824904fc183dc196fd93a88be", "version_major": 2, "version_minor": 0 }, @@ -228,16 +245,16 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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2bdqE8PBwkQCrdu3aaNu2rcgkShqTy5cvi8Rdrq6uQjjJyMh4KOU5Daenpxe5HUretXDhwgLjxo4di3HjxmmzuwzDGCnU9zBMVZF4Jh4NYhNFe+vCELQfWbAGFqMdderUqVxhhEwsBPl+kHaDtB0DBw4UNVE0s2I2b95cOKtSZVcSRijlNzm5akLD9vaq2O7CTJkyRVSu1SQqKgr+/v7sWMQwJgx9yZIgwn0BU5XU6m8F3FSlhI8/AgS+GsgnvIrRSvdEWQ/J90Ou7EpotjWh8XJyV6pGS46uMmTqiYiIUKrUFoZ8UMgEpPmj7ZKqh3+mcQ5ICzdo0CA4OTkJs19ZlyOtHdX1OX/+fKXvEzlc0zNgaWmJn3/+uUzL9O3bF6+//royTPd8act+9tln8Pb2FsdBGshnnnkGo0aN0vk1qeqffLylzSc6rirel8LXrbTf8uXLtbpP+Vf952B+74tY9WYkEmPySp2360R1anjzc3F8vcwrdu4rXRghDQdpOiiShnw6KEX7rl27RLju0aNHkZCQIOajQm9ksqHQXznKJisrC//++69YjpxgqRpsUf4ipsLkyZOFwFb4pym0GRpUuM/FxaVS1vXDDz+I8G+q4EsF+oo7h+QUXR0kJycL7d8777wjHK8pPL0qIMduqsNDtYbo+Cn6jGoQ0bmtTD755BO0bt26UtfJMPrKiU1JqHMpGq7LLmNNn+BS5w9oaotoJ5Vzq3dCMmLuFPRhZCofrb1yqDNOTEwUBd6ooutzzz0nSr9TmXny6ejevTvef/99UXKevmxlTce3336LVatWoU+fPqJAXGmF4EyBRx55RLxwNH9lsa0VRWGHX0Pn1q1bQoglU2DNmjV1vTtC40JO1JRfh7QWxZkYK+O4iREjRgj/KzKNOjs7V5qQxzCmyNWF6nBepyHeZVomp4Wb8pI8vIIL51U5koEQEhIi5eXlScbCpEmTpBEjRhQ7ff/+/VKHDh0ka2trycvLS3rnnXeknJwcZXqvXr2kF154QXrllVckd3d3qXfv3mL8hQsXpEceeURycHCQatasKT355JPS/fv3leXoHM6ePVuqV6+eWLe/v7/0+eefK9PffvttqUGDBpKdnZ1Up04d6X//+5+UnZ2tTD979qzYlqOjo+Tk5CS1bdtWOnXqlLRv3z6yyRX4ffzxx8Ue37x586S6detKVlZWUsOGDaXly5cr0wIDAwush85VYWjdhbdH+xAaGira69evF/tJx9GyZUvp6NGjBZY/dOiQ1L17d8nW1lby8/OTXnrpJSk1NbXIfV26dOlD26LtFHUN6XrQtdG8TjRO89h++OGHIrdT1DERhbdD66T9feuttyRXV1epVq1aD53rhIQEaerUqZKHh4e4Tn369BHXrrjjoXHyuQsODi6wHvncEvJ13r17t9SuXTtxfrt06SJdvXq1wPb/+ecfqU2bNpKNjY24jz755JMC9+/169elHj16iOlNmjSR/vvvP7HejRs3FnluNO/5yZMnSy4uLuL+/v3338V1o3F0T9J9vW3bNq2eJVr+qaeeEs8MTf/uu+8eum6ZmZnSG2+8Ifn4+Ej29vZSx44dlXMin1NnZ+di953RHTmpOdLOwN3SVrcd0r+1dklxd9X9WUlsnxcjlqHf3D4Xqnw/TR2OV9JDyAwwZMgQdOjQAefOncP8+fOFaezzzz9/KBMuaZ3Igfi3334TGiuydZOm6vTp09ixYwfu3btXIArpvffew9dffy2SzlHUE4VoU/I6GfLRIJMATSPzAEU1kclEhhyLKSz71KlTIn/Mu+++K/x5unbtih9//BE1atRQtDwUUVUUGzduFFq1N954AxcvXsSzzz4rnJbJ4ZmgdZPWiPab1kP7URhaN03X1C7RPsh88MEHYh4y8zRs2BCPP/44cnNzFe0DLTd69GjhW0ImxcOHDxdwwtaEwtQpnJ04efKk2BY5UFY2tL8USUbIx1QcdO0pIo00kt98843wMyGTqWb0GfndbN++XVwninYjE2t8fLw4Hjr3zZo1U7ZD47SBzu+cOXPEfUY+NOTXInPo0CGhGaVrTPcRmZzonvriiy8UJ1TygaF7l/af7l3SuJYF2Tfj+PHjeOmll0Q0Hx0rXfugoCDhUE/pBuRIvbI8S2+99RYOHDggzMj//fcf9u/fL9alCd0blOxx9erV4p6hbdI9dOPGDa3OG1P93N10D7kpqme/9jgvuNUqW2RMtwmuyHngE+l0LY7DyasayUg1I3NW50u+o/Iq/NsXlF9gvTQsT6NtlBf62rWwsBBfY/JvzJgxYtr7778vNWrUSMrPV69/7ty54stPPgf05UZfnprMmjVLGjhwYIFx4eHh4ovz2rVrUnJysvgSXbhwYZn389tvvxVfwDL0lf3HH38UOW9Zvw67du0qTZ8+vcC4sWPHSkOGDFGGSRNQlEZEk6I0E/LX/aJFi5Rxly5dEuOuXLkihkljMGPGjIc0Jebm5lJGRkaR2yJtgawRKWn7FdGMEKQZKPxYFqUZIa2OJvTlT1/88rHUqFFDfM1rQlqDBQsWiDZpUlq1alVguraaEZmtW7eKcfK569evn/Tll18WWPeKFSskb29v0d65c6dkaWkpRUZGKtO3b99eJs0IHbfcF+Tm5ornhrQaMtHR0WI9x44dK9OzlJKSIjQma9asUabHxcUJjY983cLCwsSzqrm/8nG+9957os2aEf3l6ODjioYj/mSCVsvOb3pSWfbioZQq20dGkoy2UF5ymoTI+xVfT1bOw8PyemkbQNHRRGWB/GfoS01GzsVCToxdunQpEKlETsKU44WikAICAsQ48qnQhL78SLtA0UeFIW0AaU7IkZi+kIuDtAQU7UHz0/ZIm0DaDhmKMJg2bRpWrFgh/IboC7FevXpaHTcdX2EHUDq+ojQg5aVly5ZKm3w8CNIUNG7cWJwn+rpduXKlMg9FftEXOzllk3O1vqN5fPIx0vERdHx07dzd1eXQCcr3I/ukVNX5pXuTtk/aOlkTImdvpig60ljQ9SfNko+PjzKd7vey0KJFC6VN0Td0jJrjZC2ffC5Ke5bI6Z78raiulgxpXho1aqQMUzJH2n/SsGlCz1Lhc8zoF/EXU5BwQpUvxLGxI1zaO2u1vFUHd2BzvGif3pKMZqVkbGXKj9EKIzUczODrqQotrgg2Vg8P+3qqt1ERSPioX79+hZbXhDrYYcOGYfbs2Q/NSy8MynhbEqSGJjMMRXOQ8zE5TpJamtTxmlEYVBxx69atwgTw8ccfi3nkLLz6glwviZBfRHK2RTpPZBp6+eWXH1pOFvTKAoWsyeHrMuTkWt3HJx+j5vHR9SZzQ2FKcoSVQ/A0j6m44ynt/NI9RKaYwlB+oso+7pL2pTKg4yHBh8xd9F+TogR/Rn/4+71IyBlCao73LTYVRXG0nFQLbwbb4qyDG/qYW2NSlewlY9TCyOvjzcSvsundxgwR6yt/vZrQl/n69evFS0F+eOhLk/w5yF+jOMgvgJajjLhkxy8MRaZQePaePXuEdqMwFJ5NeTTIH0AmLCzsofnoC5F+r732mvDFID8HEkbIB4C+IMtyfHQ8kyapH20abtq0KbShrNsr6jyRL0NFBEHC09NT+LxoQj4qhV+Y1Q0dH1XMpnuA7oWynjs6HoJ8SMjvSD6e8mz/2rVrxZ5fuv6UuIy2I2tVyAdEF88SaUHoepHviiyIkraEwsl79eolhulc0LkibQtVI2cMA6or43oySrTJ98NleNmiaDRp18seVwLtkJwI7AsGcnMlWFpWbf9vqrADqx4yc+ZM0VmTgx7lbCHHOtJAyEmYiuOFF14QDookIJATKKnkd+7cKZxDqTOlr1JyFKQKyuQISNPpJUAOfbKwQiGspOmgaWSuIWdTTTU/OfLRFzcJKdSp03Zkswa9+OgrkoSd2NjYYtP9k8MgOTSSiYocAL///nts2LChWIfX4qDtkbmFXny0vbJqJegckOBFx0IvW9oHOsfFObAWBzkLkwMnnUtaB12jwsKJLiDzGZkmKAcLOWTevn1bHC8JmbS/8rkjkxQdP507MjmQoNq5c2fh4EzmDXLqpKKY2vLRRx+Jc0LakUuXLol10T0lr4v2j4RZEkbJpEMOr5oCcHU+S6TZoMKddE/u3btXXD/KX6P5nNG+ksaQnHLpPqXzRo7MX331ldAQMvrJ1hVJcHjgtB7RoCa8aqsyiGuDubkZ+j2whienASevVPZeMjIsjOghlAxu27ZtosNr1aqVyOVCHWZpLwaywZOAQIIHRRWQLf3VV18Vqnm5c6UoGoqkoBcGCREURSHb14cPHy60HfRSpoRY9AKj+WVIRR0XFyc6ZeqgKZqFknLRS4egiAbaV1onfWVTlEdR0EuS/EO+++47EdFB0RakXendu7dW54nKEpBtv3379mJ7dOxl9XegFy19/dKXLn350vnQ9GEoC2TKovNDwh1Fa6SkpIhzo2tIA0D3DyUdJEGUrhWVZyABUvapoEgiigYhvyU6d5QDiKCEhOQnRP5IdO8UjuAq63nZsmWLEITovJCAQxFZpHUj6F4kIZeE244dOwotnaZ/SXU/S5QDie4DMnGSoES5kgr7Y9H9SdeWnh265+geJkFcG7MeU738ftMFkxr2wNKa9dHo+fKncx/YQa0J+e9UxU3/TNGYkRcvDAD6GqHOrKypZRmGMT7IF4SEKu4LmJIIjZJQd8KDciQ+wI2/zISWozyE38vHhEH30CY1DoFOuXgrmDMXVwVG6zPCMAzDmCZLtqm/sac9Wn5BhPCvZY5p8bdQKy0NeQlmiIvKhruPdSXtKSPDagaGYRjGaMjJysfyrapoKgp+mvxIxdeZ2UyVGt4CEg6vVNVgYyoXFkYYhmEYo2Hn/Fh8feQgpt69jsebZcDbo+LRLw2Hq6v4BkRxnZqqgIURhmEYxmi4syICznk5GBUXhvH10yplnb2ecoOZlUqoSTrMwkhVwMIIwzAMYxTcuZwJ/9uxop1gbYOBz1VOhlxLR0u4dlAlDEwPSUd6WNFpC5jyw8IIwzAMYxTsmh0p/DqItO4+sLYtmDG3Inj0Vgs2sftZO1LZsDDCMAzDGDx5ufmw3BOpDPd6y7dS168pjBz/k4WRyoaFEYZhGMbg2ftHPDwzMkQ7zNsNjToWrN1VUZxa1kCqxYNsGOfikJtdefWPGBZGGIZhGCPg+mK1VqTWhOJreJUXCytz3K+tCvF1zMvFiU3Jlb4NU4Y1I4xeQoXeBgwYICoTl1RptjBUh4XSoZenwFtJULViSpFf1VTGdspyDqhuEKWEr1Gjhpg3MTFR6/VSjaLSli3qOtIy//zzD4wZqr2kzX1blZTnmaDSDFQOwFC4ezsLfjfuiXaypRUGv1KzSrYTMN4HEX3rwO6H9mg32KlKtmGqsDCiI6gYF3UQhX83b96EoVKZHTDVMqGqrtSBUg2Z4s4h1QhhtGfZsmWiQB3VH6Lz7OzsXCWnsajrSMNU06gyocJ/P/74Y6WukzEcdn4dDasHlU0SOnjDzqnyHFc1GfZGLcxY2xB9nnaHrUPVbMNU4XTwOoQKlVEBrqLKuGtLdna2KAtvLFDVYCpWRpWEmao5v1QosXnz5tV+Hb28vKp0m4wJYmGGJCtrOOdko+sblW+iYaoe1ozoEBsbG9Exa/6oMi5BVWWpoinN4+3tjXfffVdUU9VUo1J1XVKlenh4iEqpBJVAp69OKo1OFVqfeuopUSJes9AYVdOtX7++WDdVHdWsmPrOO++IKq/29vaoW7euqEqbk5OjTKeS71Tp1cnJSaj46UVDZelJZU8VYpOSkhQtD5kcimP+/PmoV6+eEKCoCuqKFSsKfOWuX79elKGn9ZAGpDC0bvq6p5Lw8vZoH2RCQkLEftJxULXWY8eOFVj+8OHDolKrnZ0d/P398fLLLyMtrewJkug8fvbZZ/Dz8xPnkUwrO3bsKDBPaeeS+Prrr8V1ovNJ1WQzMzMf2taiRYuE4GBra4vGjRtj3rx5BaZTRVqqPEzTqYJxcHBwiftO986cOXNw8OBBcd7kaslFmU9I00Uar/JQ3HXU3I5sQtiwYUOZrheZe7p164ZXXnlFuV60/1Q8jypOy/dCcSYv0p7QfhXWrlEFaXrO3N3d8cILLxS4TllZWXjzzTdFBWDafqdOnQrcawSdI3qWaP9HjhwpqluXhHzca9asUe5DqnBM2iOqBkzXkZ5hepbv37+v1X1XlvuhtH7C0Jg0NxCjQnvCanY7tOrD5hODRDIQQkJCpLy8PMlYmDRpkjRixIgip0VEREj29vbSzJkzpStXrkgbN26UPDw8pI8//liZp1evXpKjo6P01ltvSVevXhW/hIQEydPTU3rvvffEckFBQdKAAQOkPn36KMu9/fbbkqurq/THH39IN2/elA4dOiQtXLhQmT5r1izpyJEjUmhoqLRp0yapVq1a0uzZs5XpzZo1k5588kmx/uvXr0tr1qyRzp49K2VlZUk//vijVKNGDSk6Olr8UlJSijy+DRs2SFZWVtLcuXOla9euSXPmzJEsLCykvXv3iukxMTHSI488Io0bN06sJzEx8aF10LppOs0nb4/2gfabbuvGjRtLW7ZsEesfM2aMFBgYKOXk5Ihl6bgdHBykH374QRwDHW+bNm2kyZMnF3u96Ny3atVKGf7+++/Fsa5atUqcezqvdEy0vrKey7///luysbGRFi1aJNbxwQcfSE5OTgW28+eff0re3t7S+vXrxTNA/93c3MT1k88DXfMnnnhCunjxorR582apbt264hwEBwcXeSxxcXHS9OnTpS5duojzRsMELUP3mibOzs7S0qVLRVs+t/J69+3bJ4bpviuK4q6j5na0vV50ntauXVvgetH++/n5SZ999plyLxR1zQhaB61b8zmk6/jcc8+Je5rOHz17v//+uzLPtGnTpK5du0oHDx4U+/Ltt9+K6yZf6+PHj0vm5ubi2tL+//TTT5KLi4s4d8Whedw7duyQLl++LHXu3Flq166d1Lt3b+nw4cPi+a1fv77Yt7Led2W5H8rST1D/8sorr0j6CD0Hms9ZdUPvoXP7UqQ/ng+V/nz9js72w9gwWmHk1txQaU+zfaX+Tj1x5qFlaVxZlqVtlBfqBOkFTJ2s/KNOmHj//felRo0aSfn5+cr89OIm4UM+B9RZUIesCb38Bg4cWGBceHi46Iiok0xOThadqKbwURrU8VIHKUMvS/lFWBh6aZXUActQx04vQ03Gjh0rDRkyRBkmQY3OkbYCndzJ0wte5tKlS2IcdbzE1KlTpRkzZhRYjoQyeqFkZGQUua3CLzYfHx/piy++KDBPhw4dhABZ1nNJwkDh+Tt16lRgO/Xq1ZP++uuvh64zLUssWLBAcnd3L7Df8+fPL1EYIehFQ/eQJpUtjBR3HYsSRsp6vej+p77gwIEDBa4XCRgkaGhSVmGEhnNzcwvci+PHjxftsLAw8ZxGRkYWWE+/fv3Ey5x4/PHHC9y7BC1fFmFE87hJwKBxe/bsUcZ99dVXoi8o631XlvuhtH5Cn4WRCxcuiOtB+/rOO+8oAmt1EhuZJW1y2yltddshLfE/VO3bN1aM1mckNyUXmdFZpc5n65v90Ljs2OwyLUvbqAikliZzhQypgIkrV66gS5cuirqZINV0amoqIiIihDqYIBOJJmRC2bdvn1C9FmW7p6gHUjn369ev2H36+++/8fPPP4v5aXtkGiJzjMzrr7+OadOmCbNK//79MXbsWGFu0QY6vhkzZhQYR8f3008/obJo2bKl0ib1OxETEyPMHHSezp8/j5UrVyrz0DuSVOChoaHCJFISycnJiIqKEvtc+Bho3WU9l3QennvuuQLroOtO15AgMwQtS+ab6dOnK/PQemSHU1oHHSup5DXXYWhoc71U8gzKfL1Ko1mzZop5VN7+hQsXRJv+5+XlCXObJvQckUlHvgZkmtGErkFh80lpx03mEqJFixYFxtF5KOt9V5b7obR+ovCx6hNk1qLrQcyePRsX9+Xhs+9eRdselZvgrCTcfawR5V4D/nFJqEXP6NkM1GttV23bN1aMVhixdLKErbdNqfNZe1gXOa4sy9I2KgIJH+S7UZHlNaEX3rBhw8RDWhjqYMmPoiTITj9x4kR8+umnwgeFXnirV68W/gUyZId/4oknsHXrVmzfvh0ff/yxmKdwZ6xrrKyslLYs1NHLSz5Pzz77rPATKYws6FWUspzL0qD9JBYuXCj8FDTRfHlWFnSe5Be9TGEfF11fLxoXGRkp/DfMzc1LvF40vSzHo7ltefua26ZzfebMmYfOeVEv88o47sLj5H2pLErrJ/QZigDTpN+dgYh87BIOeodjyr52cPYseC2rCvO27sCuJNE++Vcc6rVmp9mKYrTCSN2ZtcWvPLRf2Ra6hL70yPGPOlK5gzpy5IhwciTHteJo27atWI4c9CwtH760FNFAjnJ79uwR2o3CUJhnYGAgPvjgA2UcOQYWhr6c6EcOg48//riICCJhhJxR5a+W0o6PjmfSpEnKOBpu2rQptKGs2yvqPF2+fLncgiBpN3x8fMQ+9+rVSxlPw+R0XNZzSefhxIkTePrpp5Vxx48fL/BVTNshIZIEm6KgdZCWihxf5a9hzXVoA0VyUditzI0bN0Q+El2jeb3oxUwvazq3JGyUdC/Q8VCeE83nSNv8M+QISusl7QQ5mhaFfB01Ke81qOh9V5b7obR+Ql+hiEH5WOja+tn2RaM0laBmEZeGJSvm4tXXXimgUa4qGg53R9ou1cdd/CFy/GVhpKJwNI0eMnPmTISHh+Oll17C1atXRcQIaSDIRKLZAReGogDi4+OFgEAe+aRy3blzp4hyoQ6VOieK8Hj77bdFhANNp4d78eLFirBy584d8QVP08jEsHHjRmX9GRkZIoKHIgnoxUqdIG1HVpNT50ZfXSTskGd+cS+yt956S0QfkImKXnjff/+9iKagiAVtoO2R+v7atWtie2X9iqdzQMICHQu9nGgf6BzTcFmhY6AvSzLF0PYp2onWRVEeZTmXBM27ZMkSIcxRFAVd40uXLhWYhzQrX331lVie5iGzAc1P54wgLRV1vmTGoRf2tm3bRGRIeejbty9+/fVXEX1BEVJkQiqsNdAFha8XmWYKXy+6Fyg6iLQmclQIRdlQJApFj9E1mDt3rtDmaQMJ3SQIksBI9yhtm6JV6JqQdpAgjQ2ZZOi8071E57AsJpryUNp9V5b7obR+Ql8h7ZQcbUbaxh8Hv61M25l/Bq+/8RrGjx+PlJSUKt+XziOdkf4gNbx7SLyoi8NUEMlAMKVoGmL//v3CMc3a2lry8vJ6yFmrOAcz8jIfOXKk8Oa3s7MT3vqvvvqq4gxL5/Dzzz8XTnvkhR8QECB9+eWXyvIUnUMOcOQsS0545PAnO+JRtMqECRMkf39/sV/kTPfiiy8WcJYjz39anm4tzeifwsybN094+dM+NGzYUFq+fHmB6WVxYKVoDYoCoH2l7ZFDZWEnS4IcLOXpMidPnlSWJefhli1bPuQYWJIzJJ3HTz75RPL19RXHQNO2b99eYJmSzqUMbZMipWgeOl6KjijsdLly5UqpdevW4pxTJFTPnj1FRJLMsWPHxDI0neajiJvyOLCSkyY5NtL5aNCggbRt27Zqc2DV5npRtEvh60XngMaRg7Zmt0bOm3S/0jE9/fTTYpnCDqyFn8PC5yY7O1v66KOPpNq1a4trTdFN9IydP39emWfx4sUiooeeuWHDhknfffddmRxYNY+7qPNZ2Cm8LPddWe6H0voJfXRg/eabb8Rx0G/Br79LO+vsFk6kmzy3Sg7mrso0cvglJ+iqZm7bM2L79Dv+78MRf4x2mNEfGAD0RVJYNcswjGlBZhrSynFfYHoMHz4cmzdvFu2TP57C/c9UuVx8x/sgdOAtYfYlJ1/Zn458rUj7U1UsfykMHn9dFe3oYQ0w9Y+6VbYtU4Df7AzDMIzeC6GU+I6gKKa83WqziP9TfiJxHZlx5OgkikQjkxWZ0MjXpCpoN14VTUVknyo5yR1TOiyMMAzDMHoN+b8kJCSIdu/WkxF/VNV2qO8A186qeljk4ExRbJoO4b/88otw9qWUCJVNk672iH3gJOxzLwEpCRVL9WDqsDDCMAzDGExIb7OUR5V2fBffAtEzlI6fnOMXLFig1OoiJ32KiiLH+sqEXAYSWtbCUSdPLPRqhCPnDcLjQW9hYYRhGIYxCGHEwswGjcJUJpocMzN0fPHhvCgknFBSRYr2I98igiKsBg4cKOpwVWbeFp+3G+GLgNbY6uaP3Re5im9FYGGEYRiG0VsoxkIWRmxrDsUyzwa4aueMiLqe8K2vzjRbGCoSSH4kVB2dICHkf//7n3CElU0+FaVvWxJ+VO3/TlXKKk0WFkYYhmEYvYWip2Sfj5qNh+M/V1+8Ubcjas5Sp80vDnJ2pXwwlK9HNufQMJXSCAoKqvC+uTuboX0jVftCCHA3jk015YWFEYZhGMYg/EVs3Dso7TbNLMrs2/HRRx+JhHdubm5KqoiuXbsqCR8rwoAOgGV+PlqmxmPfOlVoMaM9LIwwDMMweosc0ksk5ap8QBzsgLo+2q2HsraSNqRDhw5KsUMqi0GFKCm7dHnp75aKv6/uw1dhZxC/4uHyGUzZYGGEYRiG0VsUfxGbmjC/mw9zSUKLuqTx0L4GDTm00vqef/55ZRyVZCAtSWmFRIujyyAHxXHE9WZcpRc2NBVYGGEYhmH0EoqCuXLlimj3aTwZv988irVX9mL03dByr9PGxgbz5s0T9bmocChB9X3Ij6Q84b+2jha46+Mq2i452YgJVlXbZrSDhRGGYRhG7000TZy7iv+2Uj5q+lW82vBTTz0lqi1TUUsiMTFRjCuPZqP3M+psrOkn4iu8b6YICyMMwzCM3juv1syspbQDOjtVyvpbtGghKhfLfiTR0dGiGrK2+A/yUNqx+1RVoxntYGGEYRiG0XthxFkUc1bRoo9jpW3D2dkZo0aNUoZPnjyp9TocGznA1ttGtOOPJSAvM6/S9s9UKJcwsmzZMgwdOhQ9e/YUxYioKBFBaXj79++Pvn374qeffhLJamQuXbqECRMmoFu3biI7HkmgDMMwDFMUqampSi6Qpk2awzNB9Z6hejDuPqpU75VFx44dKySMUA4T994qU01+Rj5u76mcpGqmhNbCyJo1a0QxIorPPnDggEgmY2VlJWx7a9euFQIJzXP06FH8+++/Yhmqmvj2228LYWTv3r1o1aoVPvzww6o4HoZhGMYIoJoyeXkqDUO3FuNgl69qp9aqHBONJuS8KidFK48wQmQ1U/uN7FrEVXyrVBihG4PCoCilrpeXl7h45PxDBYm2bduGkSNHws/PDx4eHnjyySfFOIJS8pLAQmWeyZOZ4rrJQzoyMlLrHWYYhmFMy0RT266b0rasX3kmGk1TTePGjUX73LlzyMzM1HodvgNUCdUIi/MsjGiLVi7JMTEx4iLt3r0bf/31FxwdHYX3MQkhlNGOksrIUDnnW7duiTbFb8sey4Stra0QWmi8r6/vQ9shTQr9NMnJyeH4bYYxceRIB87lYFqRNE5JngCiRNu9lVOVXH9yYqWPZHrXBAcHo1OnTlot713XGtudnWCZk4ec+i7Iyc6DhaX2uVCMEcqCW+nCCNnx7ty5g02bNiE8PFwkj6lduzbS09Ph4OCgzEttOasd/decJk+nZYpi6dKlWLhwYYFxY8eOxbhx47TZXYZhjBTqexjjhQQCcgcgfHx8IN1WaypqNEoT9Woqm3r16intnTt3Cu2/tnRY44Ua7ioBJCLyTqXunyFTp06dyhVGyMRCTJ8+XWg3SNtBZZmpVLO9vb3iyEpQW04oQ/81p8nTaZmimDJlCiZOnFhgXFRUFPz9/cskYTEMY5zQFzEJItwXGDeU/0P+mO3duzfsjueIdqa5Ofo/WgeW1pWvcaDqvh9//LFo37x5U2Rr1ZpyLMKUQxihi0O+H7KjDyG3SfKhC9irVy8xTCYaWdKsW7cu1q1bpyxDph6qwkjji4J8UOinCW2XBBEWRhiG4b7AuKEPXJkePXpg6orOCD2fhTsXMmBtW7YCedrSunVr8d4hFwHKPcLvmupFKzUDaTj69esnImnogpGfyK5du0S47pAhQ7BhwwYhZMTFxWHlypVinOypTEWJKLqGliMn2CZNmhTpL8IwDMOYNprOqySMkGBQr7Ud+jyldhKtbEgQadOmjWhfv34dCQkVC88Nv5qJ+xEFfR+Z4tHa5vHOO++ItLmUT+SVV17Bc889Jy5g9+7dMWbMGEyaNEn879y5M0aMGKFc5G+//RarVq1Cnz59hHPQrFmztN00wzAMYwKmONl51c3NTXy4Vhea+UZIO1Ie9i6Lw+I6R3Ch2wFs+1LldMuUjtYJ/p2cnIRgUZyvB/2KolmzZli9erW2m2MYhmFMCIpoiY9X1Xehj9zqNJdQBM0vv/yi5Bshn0htqeFpBe9kVbG8tGMU4lu70vfTGKl4tSGGYRiGqSITzfyhVwAzwK1VDYyd5V2lwklFM7ESbQY6Yo2VNZxzsuEVkYDMtDzYOlSNn4sxwaEpDMMwjF4KI926dofnyUgEHruD7KU3q1xLQvmxXFxcFGFEs6RJWbGwNEd8PZVvi21+Ho6tT6z0/TRGWBhhGIZh9E4YodQPLuZNYf8gDXxKrcrPvFoYig6VtSP37t0rdz4bj97qKr7XN3E21rLAwgjDMAyjF1BCTVkAoCAIt3h1srOGPSu/Jk1VmWo6P6GO+jE7y8JIWWBhhGEYhtFLf5HkS8nKcLM+NQxGGAlsZodoJ5UmxzshGTF3OMS3NFgYYRiGYfROGKFImpRLqqgUwqlZ9WhGqEZNRYURIru5SjtCrqtHVrJ2pDRYGGEYhmH0ShixsLAQZprkyyli2NzWHA51iy4fUtlQTZqAgADRPn36tKhWXx4CH3FX2tEHK5ZAzRRgYYRhGIbROZS5+/Lly6Ldtm1b5GfZIO2WqpiqZR1HmFlUXwVc2VRDNdQo70l5aDPEWfwnUSb1fm6l7p8xwsIIwzAMo3PkrKuyv8j5vamUXkRw3bLqI2kq22/Eu64NPmvbCWOa9MVXNZuXK0zYlGBhhGEYhtE759Ww42p/Ecem1eMvUpnCCOHWugayzS2QmAqEx1TSzhkpLIwwDMMweue8etncEWs9auO0ozv8uqtMHtUFFXeVE6xVRBhpVV/dPn+rMvbMeOF08AzDMIxOId+MoKAg0abCeB4eHjiUkY9DtVRCSPyw6vMXIRwdHdG0aVNcvHgR58+fR0ZGhqhary0t69F+q8wz524Cj3atgp01ElgzwjAMw+iUEydOIDc3VzHRkH/F+RDVNP+agKtT9QojmqYaiqahSvPloYVvHsbcD8WbERdgufxaJe+hccHCCMMwDKNX/iJ37gFJD1xGWtbTzT5Vht9IwzpmmHg/BH2S7qLW9fuVuHfGBwsjDMMwjF75i5w/lQWv7HSYSZJBCyPWtha47+wg2h5p6UhJ4BDf4mBhhGEYhtEZOTk5OHbsmGj7+fkhMDAQ9/6OxOIbR7Dm6j60TYvXyX41b94ctra2FXZidWnupLxsM66rI4SYgrAwwjAMw+gM8sdIT09XTDRUOTfrhirzKlXsbdDaRif7ZWVlJZKvEbdu3RJJ2cpD+yHqmjqZ11THxTwMCyMMwzCM3viLEA5Rqpd2tpk5mnSpnjTwpZlqTp06Va511GiqTtimWWuHKQgLIwzDMIzeCCPkV+HxQFNC/hbkd6ErKsNvxOmBmYZIvsSakeJgYYRhGIbRCfn5+UoaeFdXV5Hb48LeVOXFlO1XvZlXC9OpU6cC4cflwdrVGjbeKlNT3LkUcczMw7Awwpgkdy5nYtHTt7hjYBgdcvXqVcUXg6JoKOvp7WNq7YFjE90KI3Xq1IG7u7uiGSlvfZnrlg+cWNNzcetsZqXuo7HAwghjchzdkIhD/Y7DZ+tNLJsepuvdYRiTpXBxPCJJw5Th21G3wgg508qmmtjYWNy+fbtc6zGvp/YbubqPTTVFwcIIY1JEro1CwsxTcM3OEsMWO+5w7D/D6El+EcLstvpl3bxv9VbrrSq/kdoD3RHazAcxYxqhQXfdH5M+wrVpGJNAypNwbdZ1hPxyWylLHu7pgqGbWsHJlR8DhtGlMEJ1X6g4HflTuMepIk4SrG3gVVs3Yb0lCSPjx4/Xeh2DnvUQP6Z4WDPCGD3JMdk4/USQEERk/J72w6Qz7WFjb45/v7mL+YMv4+qJNJ3uJ8OYEuHh4QgLC1McRa2trREdkg3zB34ZSTX1Q4PQoUMHpV2R5GdMyfAnIWPUnD+QiqAng1HzQaigmaUZmn7ZGAHP+At78MqZYfDecgOBAE6vdkTjTqrUzQzDVH9+Ed/6tngsui9uBmXAJ1U/ok48PT2FI2toaCjOnDkjCvpZWvKrs7JhzQhjtGxbkoDrY0+oBZEaVui4vj0CpwYIQYRo9KirMn/SUd2knWYYU6QoYYSwsDRHo44OaN1Xt86rRZlqMjIycOnSpXKvJyEmBwdXJSD8KkfUFIaFEcbooPC72SsljF9ijwQLKzEu2skRdf/uBPfubgXm7TisBtLNVUmV3MISONSXYapZGLGwsECXLl30+rxXhhPrqrcjcKzJXqS+eBIHf+cKvoVhYYQxKjKyJDw5S8K7CySkmlthVkBr3GjojTGnOoqvrcJQdscYX5V2xDknG+f2st8Iw1Q1lFtE1jC0adMGjo764R9SlcJIrWZ2SjvpYnKl7JcxwcIIYzSEnM/A4GmZ+Gu3ety0553w0pEWcPZUaUiKwq69WltyfiObahimqjly5MhDJprUxFzMa3Uavz12DTvm65fmgAQm0uBURBhp0U9tdrK4wzVqCsPCCGMUkB32xMDjeHTfOVjm58PBDtjwuRk+mmwGc3M5mLdomo1QCyNpJ1gYYRhdJDu7sC8VtSPiEHDoNm6titari+Dg4IDmzZuL9sWLF5GWpr0G1dPPGvE2tqLtHp/KJuFCsDDCGDx/vRWOhJdOCTNL04wkzMy4hWPzzDCyZ8lCiEy7wU5ItVB5x7uHJyAvVz+8+BnGFJxXu3XrJv7fOaHWFjg0qQF9NdVQLpSgoKByrSO5lsocZZ+XixunMyp1/wwdFkYYgyUrI0/kB3FZchlWD3IThHm54b31tdGiXtkEEdl7PzZApR1xys3BmR2crplhqor09HScPn1atBs1aoSaNWuKdnMz9XPXfpCjUfqNWNRTm2quHmRTjSYsjDAGyd3bWVjSPgiBJ8OVcWEd/fHM6bblytro0Eltqrm0iU01DFNVUPVbytVROKQ35bJaGGnQU381IxURRjzaqIWRmCD+6NGEhRHG4Aj6Lxn/dT+BwLsqoSHHzAyJzzTF89ubwsZO5WSmLS0ec8NVO2es8aiNg/nq3CMMw1R9fhEKx0+5pNIU2NSygY2Htd6d9qZNm8Le3r5CwkjDHmphJPs6CyOasDDCGBT/fnsPoRNPwiNDZW9NsrKG6y8d8MS3/lqv69q1a3j77bexcuVKtOnviK/bdsSyWg2wPqIGcnPLVyqcYRjthZHMqCzkJOSIdo3m+pPsTBPKukr1cwiq3hsTE6P1Opp0tkeWmeq163CPhRFNWBhhDIrIPXGwy89TtV2c0HFHZ/R8XDtNRkREBGbMmIFmzZrh22+/xVNPPYVbt26hTxvV9JR0IOh6Vew9w5g2ZJ45duyYaPv6+qJ27dqifXqHOu+GVFv//EWKMtWcOnVK6+Utrc1x30V1fNm5ZkhOVPVlDAsjjIExdWMj3KnlitBGXnj8TEfUa61OJFQa8fHxQhPSoEEDLFy4EHl5eYqK+ODBg+jTVu30ui+4SnafYUya4OBgJSyWtCJyWYbrGs6cYXb6qRmpLL+RS+NaYnTjPni2QTdcimB9gAyfCcagIJ+QJw61wfOHW8DRpWzFqqjz+/LLL1G3bl2hCcnMVNWFoCqhMsePH0fftkIygU9WGkI3aa+CZRimfPVoMq+rNSP1ujkatTDSoJ09Mh+kEjh3q9J2zeBhYYQxOGq4W8HcvPRbNycnB/Pnz0f9+vXxwQcfICkpSYy3sbHBm2++iRs3bihZFcnDv4Ef8Ev4SSy8eRQD915AZhqrUBmmqpOdEfucvLHBPRBBTu5o1kN/K2cHBgYqocgkjJBWVVta1Ve3z91k3zQZFkYYvWfvsjhs/Coa5/alIDuzdAGBkhKtWrUKTZo0wcyZM3H37l0xngSYadOm4ebNm0JDEhAQ8FBWRXNflbe8bX4eTvyrEl4Yhqk49OKWhREXFxfhs0VkZknYmO2JxV4Nsb5f23JHxFUHZFaStSNk9g0JCdF6HS3qqtvnWTOiwMIIo/dcmXsHNt+dR+SYo7heQtZC6uy2b9+Otm3b4oknnhBOqTJjxowRhbnIV8TPz08Z36lTJ0WAOXPmDFy7uSvTsoMSquyYGMbUoOi1+/fvK1lXZe3mpdv0/KnmaanxojYEUw1pVLXFxckM4/Oj8FrERYzZcpIzPpdXGKEohK5duwoVG/1efvllMX7z5s2iY5fH00/+IiXoRTBhwgRxE9I6oqP1q/YAo7/Y31M5vGWbmaNh+6IdVo8ePYrevXtjyJAhOHfunDK+X79+Qp26du1aNG7c+KHlZGFE7lgGTlNH5tS4ycnPGKaq/UU0tQOt6pc9c7Ih+430TI9B/6RoNEpLwvUznBa+3JqR//3vf+LGot/PP/+sjKcYbHk8/by8vMT47OxsEcVAwsjevXvRqlUrfPjhh+W6iIxpkZ+dj5oZ6aKdXdMe1rYFVbhkXhkxYoQQcikiRqZ9+/bYtWsXdu/ejQ4dOhS7fk1hhJxY3Rs6wM5fVcwq4WQi8spgFmIYpvzCyM1jKfDMzhDO4y3r6f+Z1OxPyiuMWNZXO+leP8D5RqrNTEPqbysrKzz22GPCeXDq1Km4cuUKIiMjq2PzjAGTFpIOszyVk1eD7uoHmJIOTZ48GS1btsSmTZuU8Q0bNhRaEOok+vfvX+r6ya+kRo0aBVSu7j1Uppr8rHwknma/EYapTGHE1tZWfCzI+G24hj9uHMbfV/ejWS1V4jN9xs3NTTjFE1QwjxzltaVxL3W6+9oZLIwQZYuNLMT3338vftTxv/baayJvA3HhwgWhFqeLNX78eGGnJ8jJR55HvhnJbk/jKfFNYUiTQj9N6IKTXZ8xLVKuqB9UxwYOwvT31Vdf4bfffitwj9B99NFHHwkBhTIlkv9IWT3d6Utnz549iIqKwp07d+DazQURf6kE5fBdcXDt6lIFR8aUB7kP4L7AsKBEg/QBIWsj6Rmla5ifL8EtVvWM51qYo5avary+Q30GOcJnZWUJszD5qWlDm4EOOPSRqp1zM8UgjrkilCX6UWthhHxEKF8Drfzvv/8Ww+vWrRMXg4bJNHP58mUROunq6iqEk4yMDDg4FAzXomGq3lgUS5cuFY6GmowdOxbjxo3TdncZA+f+iVilveboGnz16ZdK0iTC2dlZRMxQFlUScsujbaPKoSSMEFu2bEHPlmqNyrFVsXCeXC6ZnalCwsPVBRIZ/UdTe9miRQuEhYWJdtSNfFEpm4h3t1fG6zuyZoTYsWMH3N3Vju9lQTKXYGZnBilDQsK5RIM57vJSp06dUufRupeVQyGJSZMmiZuMNCKdO3cuMA/5h+zbt08II3Z2dgVeIAQNy0WHCjNlyhRMnDixwDj6avX39y+ThMUYDzeuJyrt+ZvmIy1fdR/RvfPqq6/ijTfeEGGCFWHAgAGYN2+eaIeGhuK55+rjtP091ExPh098Clwd26OGu/6GG5oS9AVJggj3BYbF1atXlfbQoUNFvg7i8pZYyC6rlvWdlfH6zqBBgzBr1izRpqi98ux3dLMYJJ1OQk5kDnzdfGHpZNofPRU++uKEA4rHltXkpEkh7YkMZcAktR2NLwrKjKmZHZMgnxPaFgsjpkXEmTR4PajMG51/V6h3KRqLHKBlB+mK0qVLF6VNviZ0j6U3dEX6+SzE+LkiNiIHLp5WlbItpnLgvsCwOHLkiHLdNMN6755JhfeDedxaOhlM/06WAOqLqNYO1agpz347NHYSwghx7VAqWjzqBlNGqzOYkpIiIg7IVk8+HFTtNDk5WWhCKLQyISFBkYLJZNOzZ08lyoZsa//++69YdsmSJcJxsCh/EYaRyUrPg0eqypQXYWmBfORi+fLlmDt3bqUJIkStWrXUBbtOnxYdzLhlDTE8vA9mBrdD/TZFa/AYhikdei9Q1BvRunVrODmpa89kXlP7hNXrrr81aQpD2n5ynifILYHejdpyQVI75J/9j51YtRJGqJOmFwFFKZCairyjf/rpJzg6OopIBPLp6N69O95//308/fTTYh6CtByU8ZKyYvbp00cUS5JVXAxTHNcu5+CqvTNSLCxxxzxNfH3I91RlI4f4kh8TdZweftYPhREzDFM+rYisJdcM6SXsolUvYdJ8Nuuuv2ngS8o3QsdGEaPa4t9JLXylXGJhRCszDTmkrlixoshpFFVDv+Kg1L+rV6/WZnOMiXMtxQbv1Okg8g9Y3f5EeLBTpFZVCSOkzSNIsKYvOIZhqi6/SFpSLjxTVJrP+04OsHWwMDhhhKL6ZPMuJV3Uhpb9nLCqsTfsGjui5SPqZIumiml7zDB6zeXbigMScjIuCUfTqqJwJtZnn31WGc7KyENqQh7cfQr6MTEMo50wQppzmUsH02ABlcYky9dwTDSVlYnVzcsKLxxRmXoYrk3D6DGXbmvkCUm/jIEDB1bZttq0aSMc0jSTn106nIr5LU9ja8A+rH1W+4JYDGPqUFoH8sMiKC8V+WfJ3LuZiSwzlaeAfSPDE0aovAS5KFQkEyujxjBclxmT5HLog0Z+Nhws7hYIH68KhzQqU0BQduCkpCS4+1khMDJOVPC1uMx1ahhGW0iwlzOUFvYXGfZaLQyL6oeAf7uh/1tyTI3hYGFhoWSSpXBzrrdWMVgYYfQSMo28+d8hfHH7DEbfPYN+fXuJ8O6qRBZ2yCGNwvW8atsgqobqy8c7MQX3IwpmBWYYpnz+IjKW1uZo3t0R/o1V9aAM2VRDfUZ5SEnIxZF1iTj+r2mXnmBhhNFLrh5PR82cTLROi0e99Lgq9Rcpzm+EyGnqpjwoR1epQtcZhqkcYcTQqajfyI2gdOyvvwdJz55A0Kca5YtNEBZGGL0k5Hiq0r6TH12l/iIlCSN+/dTRO1F746p8HxjGWKBUEMeOHRNtHx+fMqUENzVhpG5LW2Sbq6KIHO+ZdngvCyOMXnIvOFlpJ9rdK1BosaqgbVD4uiyMkLmm63hX5D2Ybn2FNSMMU1aogFxqaqoSRUNZuWX2LY/DvDZnsGDMdZzaarjmCSr46u3trZhptC14Z2FpjlhXlSnYIzMTcVGmawpmYYTRS9KuqV/8vm0sCnRkVQVtQ/7SiYmJEcWr3H2tcddVVe7bOyUVUbeyqnw/GMbYTTSh+5NQ+04s/PeFIuSYWgtqaGj2GYmJiaKSr7bkBagjic7vMdxzUVFYGGH0EqfYTPE/B2boN7pRtW1X01RDpQ+I/GbqhETHV3NUDcNUVBjJuq6RBr6r4YX1VqapxqmZ+vjDT5iuqYaFEUYvI2lqZarUlZFWFhg0uG+1bVszfFj2GwkYoPYbubufhRGGKY28vDwcPHhQtJ2dnQtUeyeaQaUBkCzM0LyXYaWBr2xhJLCzWhhJvczCCMPoDce2RcLqQWbGu7a5VZYCvrSORRZGuoxzRe6DQudZYar01QzDlKwViY2NFe1+/fqJnBwyeVn5SLuRJto1GhleGvjCyLlGNPsMbWjRT10wz/IOCyMMozcc2XhDaed4Vb2viCbu7u6oX7++aAcFBYkq0y41rbC+W0s806A7Xvdqh6hYjcywDMM8xNq1a5X22LFjC0xLu54KKVf1DDk1NWwTDeHi4oJGjVSm5LNnz4oK9drgWtMKsXZ2ou2RlIrcbO2cYI0FNtMwekfsRdVXE+HTtvoLSMl+I9SpnD9/XrT9h9XEPWtVh7E/uNp3iWEMykSzYcMG0baxscHQoUMLTE/WqFBbo7nhCyOaGlX6eJH7DG1I9VKdB9v8fFw9aZraVxZGGL2CQuN23J+Lb8wOYq3dPfSbVH3OqyU5sfZpq9bQ7A1izQjDFMfRo0dx9+5d0X7kkUfg5FRQ4Di6WS2MWNZTmyhM2W/EqoHqHN2zssW186YZ3svCCKNXXLhwAVej/sOBuC8R22YtmnZShdVWJ0U5sXZtDlg/yEa/jzUjDFMs69atU9pjxox5aHrcObUwYlbXuDQj5RVGPJ/0x7jGvfFMwx4ItnKBKaIqU8owesKuXbuUdnVkXS0KKphH6mUy08jCiJ2NGUbVSoT96XtoeSseN4Jao0Fbe53sH8Pos2Zz/fr1ok21pIYNG/bQPC6xqkiaZCsr+Da0hjFAfQYdLxUFLI8w0rKNNdIsVBrXcyaaFZ41I4xe8d9//+lcGLG2tkabNm1E+8aNG4iPV4Xz9pXiMDouDA0yU3BmLYf4MkxhSHiPjIxUnl8K69Xkbmw+/vCsj3/d/HG9gQ/MzY3jFUQfL61btxbtq1eviqrf2lDbC3B68G1znoURhtEtGRkZuHEyD53dXkbLgOGoW1sV1aILNP1G5C+d+oPVIcZxh1kYYRhtTTTnQ8zwn6svfvdujKTxDY3qBGqaak6fPq3VsubmZmhZT9W+cw9ISDE9vzTjEEsZo+Dw4cPobDsOH2IIvkqdic1zYnS2L0UVzes80hm5lqpHpmFCgqhdwzCMCnoeZGHE0tISw4cPf+jUaH71t6pfvWH7+u430scyHi9HXsIPt04geFMiTA0WRhi9MtEEmKuKThF1u+jO076oiBo7JwvU6qYKNc6JzkR6qGmG4DFMUZA24M6dO0qis6KSFZ4PUQvwsibAWKioMNLIPAODEqPQMDMZ4UfVhUJNBRZGGP0SRjJVD2GeuRmadNadgyiVO/f09FQ6FlkL4t6dTTUMUx4TDZF4IgGuOVmwNJfQJNC4zmPDhg1Ro0aNcgsjtTU+vkwxLTwLI4xeQHkJLp6/CD+oHN6cGzrAxs5Cp9U4Ze0IObDK1Tjde7AwwjAlmWgo9ftjjz320DyZaXmYevQM/rx+ED9EnoaNtXGZacgZt0OHDqIdFRWlOPKWlZb9HCE9OCVNJRZGGEYn7N69G97mPrAyU4X6OTbSffGsovxGnFvXgPmDWhph/8WLUEaGMXUoDXpISIho9+nTBx4eHg/Nc/FQGqweaBjNPG1hjFTEVFPD3QoOdVXa4KybqZDyTMsnjTUjjN6YaAIt1Hpbp8aOeimMmFuZI9RVlZTIOiUbFw+oU9czjKlSFhNNyBH1175dI+NIdlbZfiM1mqnOS35GPtJCTMsnjYURRi9UvJTsLMC2rTLOsZHuhRFZ5arpxErYtFebas5t5BBfxrSh51cujEemiqJMNET8ebUw4t2ehZGicHogjBApGjV8TAEWRhidc/HiReEzEuDYXxkX7+KgF9U4mzRpItrnzp1DZmamaLd53BNhnQOQ935rDHlXHf3DMKb6/FJyQKJnz56oVatWkfNJIarMq0TT3rr/2KgKfHx84OvrK9qnTp3S2ozroKERPvufaUXUsDDC6E3W1YB8lb00F2ao114/Uq3LphpK8xwcrCpK06a/E57f2gTD3qgFdx/jSGfNMOVF1oqUZKIhXO6rvvSTLa3g38TGaE+43GekpKTg2rVrWi2b6q3WjIQeZc0Iw+igHo0FUqwckW5ugVhHe9g+cBLVR78RhmEe9hehCLSRI0cWeWoib2TCOUdVjTbBw8lo0sBXtt9I/Ta2SLNQlYyrEaPWJJkCXCiP0Slk+jhw4ABgVw/v1elIBmg80SUXz+jJdWFhhGGK5/Lly7hy5Ypod+vWTZgpiuLSPo0Xax3jNNEUJ4xMmjSpzMuam5sjsW8AkqzNhV8NmXmMWXDThIURRucp4IUvhntT1QgzMzRobKU3V6VFixaws7MTdXMKa0ZuBqfj9Jp4ZCXkYtJvtXW2jwyjz1E0ROTJFMieJK4tjNN5VaZdu3ZCS0SOveWJqJm+ugFMEdMQuRj9r9Jr31Tt3FZbf5IhUY0N6lyI0NBQxMSo6uXQF8vpR46jxu+XYL/hFnKzOd8IY9rCyKhRo4qdLycpBzlmque6blfjFkYoC2tRju9MybAwwuiBv0hBYaRZHegVnTt3fjjfiLk54gJUdWoc8nJxertpOZsxDDlnXrhwQXlG/P39iz0pM9Y2xCPh/eD9d1e07GvcZhpNUw05vlNCOKZ0WBhhdMa9e/eUB/XzdH98FhaEZ2JuoIGffl2U4vxGanRR5xu5sonzjTCmxfr168tkopGh8g4UiaYvzun6nPwsIyUPJzcnYfOcezAV2GeE0WkKeMIcVmiWngVrKQN+yIS1VSODEEZajnRD5EpVO+N0HHnm6WL3GEbnJprRo0fzVahEYWRV82PwSk1Dnpk5sl/oC2tb4xfgWDPC6NxE42XfAdaSyucivZbuk50Vxs/PD97e3krHIicyatHLAYlWqjwjtaISkZWRp9P9ZJjq4tatW0renfbt26N2bXbgLuz4bmNjU37NiJfKlEX94uWjppEWnoURRieQp7nsvFrPqZsy3koPw/40K/gmJyfj6tWrit9IQh2VqcYuPw+nNptWxkTGdNHGRLN0WijmtQvCwgk3EHHdNJw5ra2t0aZNG9Gm7LRU+VsbbBqqnXxvHjYNfzQWRhidcOnSJURHR4t2Cw+1StOjhf4JI8U5sRIuXdV+I9e2sN8IYxqUNaSXyDwZh9q378N3VwhysyWTNNWcPn1aq2VrtVX3g3FnWRhhmKqPogHgL6lrWdTuqH9mmpL8RtqMUQsj2UEsjDDGT1hYmKi7QtDXf7169Uqc3yVW9TJNsbRCQFPjTQNfkjBy8OBBrZZt0lutGcm7xcIIw1R9fhEA7mmq/AN5MEPTbvopjJBdXM6EqCmMNO5kh3gbW9H2upsovOAZxpjRxkSTFZsN5yxVGnjn5o4mk02U6N27t3K8ixYtQlZWVpmXrdtKnRbe2UTSwpvOncHoXwp4AL4+gfBMzRDtWAf9qUlTGEdHRzRr1ky0KbdCerrKqYw6m/hGHgh2cMNqz7o4dZGTnzHGjTYmmpRL6q/6gE7GneysMFS9V04ER2kMVq9eXeZlzalfcVeZalyzs3A3tOyCjKHCwghT7Rw9elSkVycGdHxGryNpijLV5OXl4cyZM8r4Gm83xf9qt8MazzrYd5Wj5RnjJSIiAseOHVMiRho2bFji/MkawohTsxowNV577TWl/cMPPwjH/bKSX1stvF3YY/ymGhZGGJ2aaBq69FDaVnUMQxghjh8/rrT7qJzmBfuCTcdBjzE9tE10pqkZqdFMP53Tq5IuXbqgQ4cOSmp4WSNcFpybq4WRyFPGb6rRWhiZMWMGunbtih49eojfyy+/rEz7448/0L9/f/Tt2xc//fRTASmQoicmTJggKjvSOuRICsa0hZFHnmmM5BnNcKdHbTQY5gF9priImkAvM9R9UKz02CUgI4sFEsY40cZEQ1zZrxJGJHPAsZHpCSOUFqCwdqSs1HlQwyfW0gZRsSbQp0haMn36dGnr1q0PjT906JA0ZMgQKTw8XLp//740btw4aePGjWJaVlaWmEbDmZmZ0q+//ipNnTpVq+2GhIRIeXl52u4uo2fcu3ePnirxa9u2rWRI5ObmSo6OjmLf/fz8Ckyb+nWeZN49V6rXPkHatSVNZ/to7FAfwH2BboiMjJTMzMzE/d+kSZNS589Mz5X+cd8pbXXbIS32PySZKtnZ2ZKvr684b3T+bty4UablUlNyJZduGRJ65EltnjH+d1+lmWm2bduGkSNHimyVHh4eePLJJ8U4guzrVlZWeOyxx0RWuqlTp+LKlSuIjIysrM0zBsKePXuU9oABA2BIWFhYKCpXsp1HRUUp0wbYJmDV1f34OeQEbi2N0OFeMkzVsHHjRkXbXRatyOXDabB6MH+Gj+lpRWTo3ffiiy+KNp2/n3/+uUzLOThawKu2KsPzpdtAbq5xa0fK5W33/fffix85L5EKqkGDBqK8+qBBg5R56tevL1IGEyEhIWIeGVtbWyG00HjyOC5Mdna2+GlC1Q/lNNyM4bJz506lTSY9Q7umlDtg3759ok2OfCSAi/H97HHls1zRNjsfb3DHZSjI55XPr25NNBQlUto1uJxkjT+9m6BuZgqadXQx6Ws2bdo0zJo1S0ThLVmyBJ988glcXFxKXa5lPeDqHSA7B7gSJqFZHcMUSMoS0q21MEI+InXr1hUr//vvv8Uw3aR0kh0c1A6I1JYjJui/5jR5uhweWZilS5di4cKFBcaNHTsW48aN03Z3GT2Cvgp27NihCKR2Zr74a9ZN+Lc1h29jc1hYqvKN6DN16tQp4PvStm1b1YADcM/eDrXSM+Adn4yQy6GwcGD/8KoiPDy8ytbNPMz9+/eVxF1Uh6ZGjRoi+VlJHLrlgh1uqhLcC/vElDq/sUMfLitXrkRaWhq+++47TJ8+vdRlAtwpAslVtPecuA9Hc8OsU6PZb1aaMNK8eXOlPWnSJGzatEnkXbC3txcnWYbadnZ2ok3/NafJ02mZopgyZQomTpxYYBypxP39/U0qaY6xcfnyZRFvT/Tq1QuxQa5w+/kc6M7Y278upq0qOZOjPvDoo48q7WvXriEwMFAZbjQsHYl/R8BCkuAU7QTPfvrtkGuI0Nc1CSLcF1Qv9BEhazYoEKEshfFu31e3B3SpCf+aMGk++OADIYwQ9J+0I5aWJb+CewZkID3qitAuWW90R+AE/e8jy0uFkyLIwgFJPjdv3hQvGYJMNHKaYNKkaKr4KOkV2dxpfHFFhuhX2O5G22JhxHDZvXu30iaT3v3gNDwIQoGbgWRnJLNiQEAA7ty5I+pNkLaHfEmIOoPcEfy3yl8k4UgCag0w8d63CuG+oHrZsGFDAS11ac/q5XNZOHqBXi9mcHEEAmqZicgSU6ZJkyYYMmSI8KWk/uPff/8V57IkmtUxh0WCqk8Ju2ZpEH1kedHqyFJSUkR+BfLnIB8Oku6oiilpS+gk0w1LQkZcXJyYRuOIdu3aiVS4dPJpWbKZ0YUpyl+EMY2Q3oEDByIwS60ta9hFv3OMFJVvhLR7FLIu49ZNXacm7hDXqWGMg9jYWMVPij465Wq0xUGVeU8PPYHJt67AXMrHiO6qEFfm4SRopVG7hQ1S5bTw94078ZlWwkhubi7mzp0rHA/py/bQoUMinwilyu7evbvwsCbTDf2nnAwjRowQy5GW49tvv8WqVavQp08fBAcHC2cexnQgYVRO+OPj44OmTZvC7p4qkY+ZhRma9TAcb/viiubZeFjDqanqOJLOJyM9vqATNsMYIvQRSVmHCerbSxIsUhJysW1IMDwyMvBIQiTeybyBn19hQUSmX79+iqsDOcBr9h9FQZoQqwaqfCMu2dmi1o+xopWZxtXVFStWrCh2Ovl60K8oqK6HNrn5GeNLAS87LIuQ3nwg9YZKM2Jfxx4WNuYGK4xoOqKlN3QDLqeK49vzRwKGva6uSMwwhoimib0ks0Judj5W9D+P2gnJYjjB2gbTFtdGDQcWRmRIkHv11VdFdA3x448/io/0kmjUywm3ryYoGW1ternDGDGcNwBjVCaa9LB05GeqHOIcGxuOiYagCBrZT0QzLTyR1VhtqonYw6YaxrBJSEhQfL3IV4qqVxfHwhFXUfuB12q6uQUaLW2Lui1VQQyMGgrO8PT0FO21a9eWGhnm1MypyFo/xgYLI0y1sGvXLqVNZr5wjVoLTgaWJpqiwFq1aqVECJHflEyXx11JKYJEK2uY2+lnBWKGKSsULUnm+dJMNH88exuBJ1Uv1VyYwXFWa7R/xPQK45UFSmvw/PPPizaZv3799dcS56+hIYykXGRhhGEqlKMgKChItFu3bo2aNWvi8Fa1MHLTwrA0I5qmGoqmoagaGU8/azTY3h0Tonrh2XUlVzRlGGOoRbPxq7vwWHdNGU6b3hSPPMdh7SVBwogcMfr7778/lPpCE8fGjoCFSggMOcrCCMNUKAW8nEaaTDRE1i21MFKzlWFpRkpyYiUadXQw6hA8xjRISkpSzKsU+ah5z8scWp0AzLmgqNgj+tfF41+rEp0xxePl5YXHH39ctBMTE7Fs2bJi57WwtcBdO1VOLvOIVGRlqJyJjQ3uMZlqNdHIwkhSKpBpZg56rJp1M1zNCFGaRzzDGCKbN29WynKMHj36IQGbkqBd/ugabCSV71doU2+DSFyoj2G+P/74Y4np8jN8VKYaqvVz8WDxWhRDhoURpkohjYj8dUWZeLt164a8PAmzPFtgTJO++LxXD9g5GZ5vBdVlcnZ2VpxYZc1PYdKSVPZ2hjE2Ew0JJ8O2t0GEuzPCvNwwdUcz1ghqAfmdUaoL4saNG9i+fXux8/qN8kLkoHrIebc1arewhTHCwghTpVy9elUkwiN69uwpnLdCo4HMbFFPG75NDPPBoo6YiuYRlOKeMipq8udrd7Cg0QnsrrcXd29n6WgvGaZ8UIJLuY4UmRS6du1a5Hw+9WzwxMn2GLerFWwdDO+jQtdQmG9ZkqCNeKsWpv9VX/x39ymYndxYYGGEqdaQXuLybfX0ZqXXT9JbKLFfcaaa1Jvp8I9NFGrV43+rcgQwjKGwdetWkahQrtArh7Ln5eYjI6Wgz4Kji6XRviCro9YVVbiXfevOnz8PU4WFEaba/UUuaQgjTWsbbkKkkvxG/Pqp841E7+d8I4xxmGgWjryO5R1OI+aO8WYCrW4N6yuvvFLAd8RUYWGEqTLoy0quaeHt7S2y8BLWy6/ho7BgTLl7A008cgz2CshmmqKEkS7jXIRzLmF9hTUjjOFAYaZUzI2g5Fw9evQQ7RUvhSHgaBj87ydiS8+TyEwzzqiO6mby5MmK/xnVdIuJiSlyPoqiCfovGWs/ikJshPEJgyyMMFUG1V7QTAEvJ0yqcTMenVJjMTLuNhrUMdxbkDpqufL0mTNnRPFIGVJb33VVJX3yTklFdAj7jTCGATlSZmRkiPbIkSNFmft722PgvvqqMo/NqED2EakkqLbb9AclJSh6af78+UXOt2Tsddx9/Bgc5l7Ama3qRIvGguG+CRiDNNHk5uTDI1kVmhZnbw8HZ63KI+mtqSYzM/Mhe29eU1elfXwNa0cYwzTRJAYlIXj6OVFviYh/pA4mfu+vux00Ql566SXFL2fevHmiPymMawt1Jtaok8aX/IyFEaZanFcpBTxx40yGkpcgvabh5RfRxonVvz/7jTCGBWlEtmzZItpubm7oVKcTTj8RhPwM1TPrPdoLE1c00PFeGh8BAQEilwtBZpqiisrW7aoWRtKvsTDCMGUiLi5OmC7kePpatVTVa28eVWdetahjeJlXtXFi7TzWVfEbsXlQdZNh9JmdO3cqqckfe2Qydg8/j+z7Kv8Et66uaPlLC5iZG67TuSGF+UqFche16O2IPKjOvW0kCyMMU+4U8ETMOXX2QLdmhi+MUK0ducZEYWHE3duqgN9I1C32G2EMw0RjaWaPNidGwfae6nm1r++Atstbw8KGlelVRZcuXZSPGzL5ys7/MpQc8r6TKi28R0qa0TkQ853FVFt+ESJToyZNnU6GL4zY2NgIgYS4du2aKLmuSV4zDb+Rf5Oqff8YRpvoN6rSC5hhVOBK1E1QPatJVtbwndsG1q6cS6S6U8SXmBb+gHGlhWdhhKnSFPCUcbV79+7KNOtoVQdHMn2Tbiop35hMNSdPniwwLWCCD77ya4knGvXCXjOuZMrot8M5ZV5F4Cys93sUu1x8kGlujsB5bdCgveH7dxkCo0ePhr+/yjmYfHcoTbwmdo3VfiO3jhiXqYaFEabSuX79OsLDwwukgJezN3okGU8kTVn8RroPd8Ixt1pIsrTG/rM62DmG0cZE4zUdCHgPeWbm+NmvKSx/6YKuo1z4HFYTlpaWePHFF5WPup9++qnAdJ8OamEk4TwLIwxTLhONsUXSlCWipoaDGdo1VLUvhQIxCUUX1GMYXUL5LdbvTgXq/6qM+/kVcwyfYPimVENj+vTpsLdXaY2XLl1awPTbtJdaGJFCWRhhmDILI5TsTMbN2wqJzzRFWJcAuA2saTRnkRKfeXh4KMJIYS/43iqXEsEB1o4wesjS2cfwTd7LCMhS5bd4YzzwwiiOmtEFrq6umDJlimhT0shFixYp0/waWyPZygoJFtaIzrEqtlq4IWImGcjRhIaGIjAwkEtUG8AXFuUnoPBACueNjo5WMq8aM0OHDlVSaN+8eRP16tVTpm07kIuvX45By7R41G1lh9fXq6cx2pGfn4+wsDDuCyqRG0HpODH4ONxyc5BqbolVPQOwfm19mHMIr05N3Y0aNRJt8iEJCQkRJhzi0RezsPW8lWiHrDZDHR/j6F/ZZ4SpVI4fP67kKSATjSkIIqX5jXRpIuGtiIsYkhAJl9PROtg7hima8KuZODritBBEiDtW+Vg4z5sFER3TsGFDUdGXIP+79evXK9O6dlJHNW08BKOBhRGmWkw0piSMkECmiWtNK0S7qfKNeKWmIfLmw6meGaa6ocq7/z1yGp7pqjo04VaWON3hH3jUYj8RfQ7zHdNbPc/a/QZh2CgTLIwwlQZZ/NasWfNQCng5kmbH/PsIOZ8hVO3GRkkVfAnHTurU8DnBnI2V0S1xd7OxvucJeKeotJj3LC3xQeKrGPt0X740ekKfPn3QsmVL5QNH/shp6G+GFqr6nLh8Lhu3bxhHBV8WRphK48CBA0pcPD1I3t7eyrSbQRnI/18QrvY5iPldCxaUMxanM9nGe/bsWZFASpMBz6iFkdQTLIwwuvtg+GfdTixpfwiBKaqK2vEWlvgg5X8Y+VRnUaWX0Q/MzMweShEvM6l+Cr64fQZ/XjuAA3OiYAywMMJUGr///rvSnjFjRoFpN46qswVa+hlHsrPiTDXkxEsCiSauHV1gZqnyn4k/Eq+T/WNMm6NHj6J3j4E493I+mmXkinHJ5hZYXW8L/tn/ExYuXMgBAnrG448/jpo1VZGH5Ddy584d0e7fzRyt0+JBdX4z992DMcDCCFMpxMbGKk5W7u7uD31huT5ILU34tHY0OSdWS0dLOLdxFu3U62nIiuE6NUz1cPHiRYwYMQLdunVD7pWW6JCl6vbTzS2Q8rItNh/9voCZkdEfbG1tMXPmTNHOy8vDr7+q8sC06uOEu46qXE3+sYlIuq3y+zFkWBhhKoXly5cLjQAxefJkUbNFE8f7as1IrxGOJufESrh3U9epOfk3a0eYquX27dviWSS/A1XNGeBo/Pf40yUMWWbmcPmmNaZ/2N1kIt4Mleeee04pxkna59RU1Yed/0hVJXQi4b8YGDosjDCVYocmFa9mBsHCpFx9oBkxBxzqG0/2VU2o05dT3xflxBrhpRZGLvzLwghTNcTExAhfA/JhWrZsmZIYy8fHR7zMll2dgrYHuqP/FK6VZAjUqlULEydOFO2kpCT88ccfot35WS9lnrubDd9Uw8IIU2EOHz6Mq1evinavXr0UR04ZKV9C2o0Hpchr28PCjiydxoeVlRXatWsn2pSk6P79+wWmt3/MBblQfYXaXWcnVqZySU5OxieffCIS7lFNE1lTWd+zL7755huRjI8+FOg+DWxmx6ffQMN8f/rpJxGR6NjYUfmwiz+WgKx7hm36ZWGEqVLHVSLuRjry0qlOL+DY0Di1ImWp4OvsaYWI9n6I6F8X/p800cHeMcZIZmamyENBQsinn36qqPHt7Ozwdret+C7/HTQye1oMM4ZJixYt0K9fP9EmoXLr1q3CvOY1/IGpRgLCNtyFIcPCCFMh4uPjsXbtWtGmNPCjRo16aJ7jO9T+ItfMjNNfpCxOrMTMnU0x4+8G6P+MezXvGWNskEMjqexJE0lfzuRETlDacHJ6XP5iEHpdsYCVJMHsq3O4cFDtRM4YHq8WEebrMVTtN7L3F8M21bAwwlSIFStWKDk1nn76acVnQpOYc+pO0KqO6WhGDh48qNN9YYw4V8g//wgfJSqoJod7yqGgZDL9oN//YL8kTBl/d1BdtOhp3B8Cxs6QIUNEmnhi3759OHfuHFxbOuK+vUrj5XsvwaCzO7MwwlSoU9Q00RTluErE3c1FtpnqVqvd0bg7xICAANSvX18RRjRfFAxTUYKCgtC1a1cROn/58mVl/ODBgxEcHIy//voLjjeccO75C0J1T+QOC8TUPx+k7GQMFnNzc7zyyivKMJnmaFxmB5V2JMrDBXdvGW42VhZGmAolUZI7xO7du6Np06ZFzrfGrz5GN+mDGQ26ollv4xZGyI5LGiJZWPvzzz8fmoecz4J3p2D5S2EG/SXDVC/kEN23b98CYeNdunTB/v37RcXo1q1bI2Z/LIKfOQcpVyWJ+D/li2FLG3EyMyPh6aefhouLi2iT4JmQkIDBnwei6YGeePZaJ7QbpKqBZYiwMMJUmeMqkZ8v4fJtIN/MHLZ1HODgZJyRNJo89dRTBfKvyKGVMoufCkH0+KPw+Osqjq3kEF+mbHz//fcitJNo0qQJ/v33Xxw5ckREsBGH1yTgyLizyM9S1X7yHuWF5nOacR4RI8LR0RGTJk0SbYqWosKkAU1tUbu54TsnszDClAuSyOWieCSpjxkzpsj5wu4C6Q8+/pvVNo2TXbt2beUFce3atYeiagJ7qb5siJiDLIwwpRMXF6dk36QEWPQSGj58uCJonN6RjOgXg2CTp4pas+/hgVbzWsDMghOaGRvDhg1T2hRVYyywMMKUi5UrV4qQQll1WFzY4GW1Dx2amogwQsimGlk7okmXsS7IefASsed8I0wZIP8AOWT3mWeegZ+fnzLteriED77IgHW+ShC5U8sVHf5oBXMr7t6NkR49eggNCbF9+/YCVdCpfX6/YUZN8d3KVJnjKhH5VyQ+uHMWT9+7iRYOhl8/oayQpkgW0FatWlWgiq+TqyXueqjq1NRMT8fti6ZzXpjyaSF//vln0aaEZe+9954y7c49Cf1fk/CfmSc+CWiD0JpumLC/DRxcLPlUGynW1tYYMGCAaFM496lTp0R78eQQ/OV3CLdHH0XMHcNzZGVhhNEayp9x4cIFxYGuefPmxc6bcy4eXVPuY3xsKOo7qyqFmgI1atRQcq7Qy2TLli0Fppu1UKeGP7WWs7EyxUOCCGVXJajWDEVsEffiVYJI+IOyJPmt3PH4iXZwqWnFp9PIGTp06EOmmuzYLLhlZcISEvbMM7xaNSyMMFXiuCpjHaVKeEaKxCbdjTvHiDammjqD3JR2zCH2G2GKhhxWyURDWFhYKFqRmPBsvDMuEjciVPM18AP+m2MGtxrcpZsCgwcPVtoUSUU0f0pdqyZhu+ElQOM7l9G6c1y9erVoOzs7Y9y4ccXOm5ebD/cklTASZ2cnzBOmBKVvpuJkcoehWaum82i134jjDRZGmKIhp9XExERFuK1Tpw4SYnLwT98gjAu+hAkxIfD3lLD7BzPUcmNnVVPBx8cHbdq0Ee0zZ84gOjoaXUc7I/5BtXTfyDjERhiWqYaFEUZrx9WMDJWPw5NPPgl7e/ti5711NhO2D5zq0jxNSysif8nSOSJyc3OF70hRfiOe6RkIOc9+I0xBUlJSRDgvQcmt3n//faQl5eLv3sHwi1eF+A5PDMfOj3IRUIsFEVPMyCqzY8cOWFiaI6W1KgEalQDYM79goU6jFUbOnz+PDh06YNGiRWJ48+bNIhU2efrKv7t31YV7Ll26hAkTJqBbt25CtU+SHGO8jqvEzaNqr26LOsad7Kw45JwABJVz18SsldpUc3od+40wBZk7d66o/URQCfkAvzpY1uc8Au6p7pU0C0s0+KMdmrRSfQ0zpsXQIvxGmkxU16qJ23bX+IURCh8iib1wxk0qn37o0CHl5+XlpSRnefvtt4UwsnfvXrRq1Qoffvhh5RwBU22cPn1a1EMgSPCk61gSdzVq0rg2M01hhJ6R9u3bK6m8L168qEyrM9ANyRZWOOJUE8Gx7HTIqKEw3jlz5og25RJ57733sWjIFdQOU33tZppbwHtuW7R/xHAzbjIVo2PHjnB3VxXcpLwz9J7tMd4FCdYPTDXhcYi/m2Mwp7lcRvwNGzaICAo57r00yKZFIWmPPfaYGJ46daqwp0dGRsLX1/eh+emk0k+TnJycAvHUTPWzYMECpT1t2rRSr0fGDXW1Xv/2DiZ7/SgjKwlysnZk9uzZot1lvAs8VvZCVq4Z6sUDX5jo+dEG+R4y9ntp/vz5ShXe8ePH4/Dnlqh9TpW0h3yNHL5oJXwEjP08MMVDQuqgQYNEWngy6ZECoE+fPkhqVROup8KFqWbX3BiM/dQbuobMjJUujJAzFdm+qXS1LLnLULgnCRlUSp4eIDkrZ0hICBo0aKDMR5VdKWkPjS9KGFm6dCkWLlxYYNzYsWNLdJZkqha62WWfB0q4QyG9YWEaGc2KwDIiRfyn7tIpMB5hYaZpiiDTJJV1J78RiqohMyUNE63q1cLJa7a4FQUcC4qAj7vKx4YpmfDwcKM9ReSTJQus9MJpZ/EqfLffUqbHPh2AvgNSERZmmMmtmMrVjvz111+iTYEFdevWhecgK0CVegT3Nkch7BndO7KS43WlCyPz5s0TZaqdnJwKjG/bti3+/vtvYZqh4mlvvvkmXF1dhXBCD5eDQ0EHRhpOT08vchtUFptspJpERUXB39+fCz7pUCsiXy+6NlQboySoJo1nyi0lkmZISxNKv1qIwMBA4Wy2adMmxMTE4ObNm+KLhhjUGTh5TTXfzVg/dGmr233Vd0gTQIKIMfcFP/30k0j/TjzV/Sc02q5yViXujmiAKd+Z7rPEFIT64tdff108F1SniPoa3+clrJ8dAYu8fNxMt4ebZyCcio8z0Bu0EkauXr0qBI133nnnoWmaGg4y4ZB/yL59+4QwQpko09LUKnuChouLxKAMc/TThMw81PkYawek78iOysSzzz5b6nXIycpD+sSGuHctFRaOliZ/3ShZFQkjxIoVK5Q8AX3aSJi1TIJlfj6C9mVg0iMFhXymaIy1L6APt2+++UYZfnR8H6TOug/nnGyEdfTHs4tqG+VxM+XDw8NDaKlJELly5YrQVpMWIviZdvjhoD1yzc3R9YQZJvTT/2grre5qcsCjg6WvPPqy27Vrl1A7f/rppw/NS+pFuVopqY7oa1CGappERESI8Yz+Qz4/dO0JcsaU49tLwsbOAk/+GIDntzfFjLUNYerQM0PmS2Ljxo1KRs3OTSV8Fh6MNVf3oe3KYB3vJaNrFi9erEQhUgbfsS80R9tNHRHWJQDT/23MgghTpqiawWOchCBCrNtfsGq4UQgj9HBQR0q5JujXs2dP4ctBaqKjR4+KtNeyBoVMNjRdjrKh2hxU8pocU5csWSLU/EX5izCGnXGVKRobGxth3pSF8bVr14q2na05PG3zYCPlwzMjAzeDizZdMsYP9ZFff/21MixHHDbq6IDntzSBpTVrRJiS843I2Vh7tAQ8HxQH33YcSMvQf4FEq7ubHE9JLST/qIMlEwz5j1C9EnIw7d69u0jOQ9kCZbs4mVy+/fZb4QBJ3r7BwcGYNWtWVR0TU4lQxJTsIEWOq2R+Yyo354h5K3Wdmtu7TdPJl1E57sdGp+Kxmj9i+KMj0bp1az4tTKm0bNlS+bAn1wjy7bO0NMPIHqrpZuk52L5Z/5MqmkmyLUXPCQ0NFc45bC+tfl8RObkZaUU0w3tL4uiGRPg3tYVvQ2u+Zg+gR43yjpDmkLh165YwVV7dEoeQSarQX78nfNHyl+ILD5o65KhHpmJj6wtIY9ygfmM8lfsLumZZ4rqfC6YdaAdHrr7LlAHqm+UIVCrKSaabXbsycWTaJbRJi0NEvZp44YR+C7fG8zQzemOioRfG3WdP40K3A1jc4DhfGQ0/Kk3tCDmyEg36u8DcRvUoxh3hOjWmyLI/lmFo8hQhiBB+USm4cVr/v2YZ/fUb6dnDCk0yk0S+Ee+QWKQk6HfVdBZGmGIhc9qpU6eU0G3y/SkLIRo1aXJqcKpqTahWDQklBDl/k7bEwtYCLh1UdWoywjKQEc4vIVOCEjqe+uQMHrXoKIZzzczg9HlrtOnPkVVM2aCoVTkClYQR6ldsbC0Q27SmGEf98dWNqiR6+goLI0yxaCaeK60OjSbZIepkTA4NTDMNfHFQsj/qOAhK+kcheYR7N3WdmtjDqhwTjGmw7rX1eCxrpDLc9PtmGPSsh073iTEsHB0d0atXL9G+c+eOSMFBdH1WXavG8vg96DMsjDBFQnlg/vzzT9GmfDBPPPFEmc+U7V11Tpl+o1gYKQw5dxd2ZLVpp3Zi3bqAnVhNhav/xMBxlbq+jO3T1qj/NEcZMpVjqmk12h1WD/yOYnbcR16m/mZ4ZmGEKRIKzaYU8ASFpNaoUfaCXKnX1MKIU2MWRooKkacvGWLNmjUi0ZV7e2dkmakeR/sb7DdiCpzamoSL08/DAhZi+KxHMPp831vXu8UYUYivuZU5ag1RaUfy0vIQu09/ta4sjDCVnlsk5aqmmaZgGQBGVQpBrttEyc8o/46DsyXu1VT5jUjmZoiN0H09CabquBGUjhvTgmD/wLfqmFkkuv3WRfEnYhhtofpvcg24w4cPizpyhNdwtakmbJ0qoZ4+wsII8xDnz58XeWOIVq1aoUOHDmU+SxRJIwsjdoF2sHQoV2FokzLVkCMr0eGHxmi8rycmhfeEh1/BcgiM8RCfLOGJr8xw31zl3H3F2hyHm6xHrz4qmz/DVNRUk5eXh//++0+0PXq5I89O1Q/f2XwfGSn6aaphYYQp0XGVtCLafK2FnMtEfrrqZg+3Ya1IcZCzWUBAgGjv3LkT0dHRaDeoBuq2tOM70ojJzJIw4n0Jp+/Z4N3a7bHVyRGfxU3Hh5++oetdY4zVVGNtjjt1PEXbPi8Xe5fqp6mGhRGmAJS9T85/Qdl1C1dPLo0bR9X+Ium12F+k2AfP3BxPPfWUok2i8gqMcZOXJ+HJzyUcPq8azsyLw7x7T6FFRz+RmZphKgqVYCEzMLF9+3bRtxABo1SmmihnJ0iqUXoHCyNMAahmSlKSqmT5+PHj4eys8mMoK5HXspALlSbFpSkLI9pE1RROhix3JIzhQ9fyh8l3sGNvjhg2l9KBS48CmaH46KOP2FeEqRSoREv//v1FOyYmRhQ5JfpP80Cdrd0xLaQrHn1VlXtE32BhhKk0x9X7iRKW5vpgVNO+eK5+F9R9TKUaZIqmYcOG6Ny5s2hfvHgRZ8+exfn9qZg/+DIW1zmCNR9E8akzEpZND0PTbVfxTehpeOamI//SWCA1CJ06dcKAAQN0vXuMkYf42jlZoElnB50Uf3zzzTfLNC8LI4wCvRCp+jLRvHlz5UVZlq++v3fmoelTEo5eBPLMzBHj5IhmLaz47JaCZnp4cmRNiMpG4MlweCenIu4wh/gaA+s+jUKtf66Ldu2sVPRIWAIk7BDDrBVhqtJvZOsDYURXkMZ3zpw5ZZqXhRGmQo6rdy5nYn7Hczg28zJiVdYduNUA/vrQDA52HKZYGmQKk9M4k99I2yEOSr4R51sJbKoxcHYviYPVLxeV4XPtnLHh6iui3b59ewwePFiHe8cYI76+viIKkjh9+jTu3bv30Mfj6R3JyMrIq/IyB19++WWZ52dhhBFQ4i05xNTW1lbUUCkJuqFXvx+J472PoE5oDAYmRqFtaixG9QQuLTPDqF4siJQFV1dXDB8+XLTv37+PA4d34a6Xixh2y8rE9VNcp8ZQObMzGYnvnhWFyojQVr5YF/eiMp21Ikx1mGq2b9+utDd8Ho3lgUcQM/EY9i+rWs0rBUJQhe2ywsIII1i3bp2SJGfcuHHiJVkct85m4Lc2Qaix4CIc81SVIJOsrPHBRGD95+bwcmdBpLymGlJrWrVR16kJXs+p4Q01qdnVyUEilJK47e+BgFfCERSkcihs3bo1Hn30UR3vJWNqphozCzPUTE8X7Vtrqq5WTW5uLr744gutlmFhhCnSRFMUIgT19XAEDziC2hHqWPXQxl7ofbQrRr2hn17a+s6gQYPg6aly9t20aRN8e6krHccfYb8RQ+PwmgScHnICrtlZYjjStQYm7m6JL776VJmHtSJMVdK5c2e4uak+aij5GZlMiP7PeSDTXPXad7sUg+wqqlVDJmcqBEqU1UGbhREGV65cwaFDh8SZaNq0Kbp27frQWbl6Ig0LWpyB67LLSgrrBGsb5P2vNV440greddUvUEY7rKyslHwu2dnZuJW2TekwnEPj2W/EgLh0OBWxM0/DOUeVzj/G3h5DdrTBiaB9SlbjFi1aYMSIETreU8aYsbCwwCOPPKKUnJCrgzu5WiK6rurDp0ZuDg78mVDlWhESvMsCCyNMAa3I9OnTH3JcDd6dgsuPHkXgXfVX+u0WPhh0qiuGvaaue8BUjqlm5eqluFdL9hvJwrWT7DdiKDTr7oioNj6ifaemKx451BE+9Wzw6adqrciHH34okt4xTHVnYyW8h6n77Bur71VJkdUbN26INiXz6969e5mW4yfCxMnMzFSXsbexUbKCatKqrwPu1VS9HONsbGH+eVvM3N+C66dUIuT9Tl/MxPHjx5HTyFaZFryeTTWGxNRNjREzphEmn24Hr9o22LdvnxIyT5rH0aNH63oXGRPgkUceUT4sNf1G+j3roUTsuV6MQW525SVXpJo4n3/+udZaEYKFERNnw4YNiI9Xveyokqy7u/tDZgH6iuu7tCnCOvrj0bNd8cjznMyssqFOQ1M7EmatcnQkEo6yE6u+EnI+A7sWxRYYZ2NngckLasPWwUIMf/bZZ8q0//3vf6wVYaoFd3d3JVfU5cuXcfv2bdF29rRCVG0PVTsnGwf/SqjUQIirV6+Kdo8ePUQNrrLCwoiJUzjjatB/yVjc8MRDHWyjjg54fntTuNbkRGZVxRNPPKG8qDYc+RIbvGrjw8A2+N6j8UOp4hndc3RDIo4POo6U986KvA1FceDAAfGTM+5SpBrD6CLEd5uGqaaWhqnm6qrKMdXQR+ysWbPK7aTNwogJc+3aNaWjbNqwKaQt3gh/4jh8E5IR/cllJN1XeWAz1YO3t7eIrCFuh9/AuY7uCHL0QEiCJW5G8FXQJ6L/uYu450/BJTsbtvl5OP266muwMIW1IuRYyDC6TA1P9HvOE9kPTDUu5+4hL6fippqNGzfi0qVLok1BEP369dNqeRZGTJhFixaJ//Us6mOW+ZdIWxyiJGjKszBHxDVVaCKjm+J5+fF7lfb+s3wV9AHSUF2ffRPBU8/BIlfVgYd7umD4ZlXGS00OHz6MvXtV17B+/fp4/PHHq31/GdOmVatW8PFROVTTvUjJLQnXWlaICnBHhrkFztm54ugJVT6cimhFNAXv8oSuszBiolABoz+XrsLTdpPwQ42fYBvzwGHSwgwRfepg3PnOIjKAqV4o5FOulHz52Hxl/P5gNtPomryMPJyddh43v7mljPMY44OnT7UXETOF0VRZf/DBB7C0tKy2fWUYggQCOaqGghXImVrG+a0meKJRL3zj3xLrzlTs3ty8eTPOnz8v2h07dsTAgQO1XgcLIyb6dTdz2EJ8YrkM4+0eh4WZSnXs1MwR3XZ1xox1DeHgzB2nLrCzs1P8CjJjDyMgLxkDEyLgs+YK5xvRIWGXMrC89UlhnhGYAY0/bYgOvzUXFVELQxFRlGyKqFOnjpJHhmH0JRvro8NsARvVvbv+IGk3pHK/TyqqFSFYGDExYhIkzOx6DKPPNIB/zgPVnCXQ4L366La7C5xb1dD1Lpo8iqlGysXzEWfwStQV9ImOwOWjqjTOTPVy4t8kHO5/ArViVU6q5g4WaPdnG9R9sU6RnS6pwp999lll+P333xeJ7RhGF/Tv31+5/8iJVXaGd3Y0w8AOqnki7wMnLpdv/STgBAUFiXbbtm0LCD/awMKIiUBS74J/JdQZm4WNUislzvx2DQfUX98FDd6sB3Nrvh30gW7duqFu3bqiHZR1TRl/boNph/ieOnUKb7/9Nk6ePFlt21y/X8IrX2ajRrYqo2qcrS18l3ZErUeKL33wxhtvKCpryiui6QfEMNWNk5OTEmJL4b2UcVtmzIOCpjb5edi+uuiIsOrQihD89jEBgs7noutMCc/NkZCebY171nZY6uGLw+0lPHujKxp2Z22IPkEPs/wCO5++SxnvG22ayc+io6MxZcoUYYueM2eOSMwnJxGrKqiT/XyZhDEfSThh444F3o0Q7u6Mvgc6oUW/4p+X9evXY/78+Ur1a8pGaW1tXaX7yjDlzcY6rJuEtyMv4K+r+9FwyVnk52kXVbNz507xkSA7y8oVyMsDCyNGTPzdHMwfcgVnBx7F2YsaBZHuLYdz18X4YscgWFjyLaCPyJlwb6ZsRpaZKqop71yCSeUbISfrb775RuTn+OOPP5TxVPRr7NixiIqKqpLtpiXn4cnP8vHhYvW5dn/cH08Hd4BvfXVm3MKEhoZi6tSpyvDPP/+M5s2bV8k+MkxlhPi61TBHoGMObKV8uGVl4tiGpDKvk/qiwmUOyqsVIfhNZIRQmNWGz6Oxvc0RBJ64A6+cDDwREwKkXwbO98HA2quwZMHXFbpxmKqFzDSUwTAPebiQpVL5Z93LQtpN4/cboU6OvPPpRf7OO+8gNTVVjHdxcVFS5t+9e1dkDKbCgpVJ+NVMrGx3CtmrVdkq6RH5+lkz/PG+GeweZFQtCtqPCRMmIClJ1ZmPHz8e06ZNq9R9Y5jy0qBBA9SrV08JOZfvU8J1kJfSjt9R9gRoe/bsEY7aBD2rI0eOREVgYcTIuHw0Db+1CoLtD+eVEubkH5KUvBsIaosWAQlYu3YtO9QZAHJ6+Au5KmGEiD9i3KYasmdTTQ1S9968eVOMo6y0zz33HK5fv45du3aJ5HDEsWPH8Morr1Tatk9tTcKBvifgF5+ESTE30SszBhs+N8M7E81KFdwpdFf2ZSFBkjIbs7DP6AtmZmaKdoSq6tJzJNP/RU+R0oFwDIopk/a1KK1IRYs/sjBiJKQl5WLh4zdxffhR1I6KU8afc7bC82nvYsO9F+FVyx1btmxBjRrsI2IIkCmC/A4u5KiFkUubjFMYSUhIwKuvvio0H3JILEGOd2fOnBF+GJ6enuL322+/iaKOBLUXL15c4e3/++09hE8+KVTVRKKNDb792A6P9Shde7h9+3Z89913ok1RC+Qnws8YYyimGs8AG3j0dBPtjDsZSDpbuiMrZe4mDQvRpEmTSin+yMKIEbBzQSzWNj8G3/9uwVpSOSDF29hid5ckvB/aD/cyg2Bvby8EkYCAAF3vLlNG6IVGqs8beTeQ/uDLPOFovFHlG6EqnwsWLBB+IT/99JMYJug+XbNmjUjS1Lp16wLLkMAiO4kSM2fOLHeETVZGHhZOvAmrr8/C9sF5jXBzRq+9ndFhqCr5XElERkYWiJYhH5f27duXa18Ypirp2bOneA/IArRmP+I1XF2r5sioM5jb5yK2/RqDzDQNX8MqLnPAwoiBc/d2FtL+F4ya6SpfglyY4U73QKS8ewc/bB0vxpH6bPXq1WjXrp2O95Ypj6kmH/m4ZK3qFFxysnHxkHH4jdDXFd2TZIKJjY1Vkr6R+pcqf5JmqDhTB52XF198UfHXGDVqFO7d067g177lcfizyXH47lBnVL3d0AsTT7WHf+PiHVVlSHB68sknlX0fNmxYpZqNGKYyIS0r5Rwh6FmRc4MQtYbUgrmdShwwS85BnfORwMfBOLTq4XQChw4dUjK50kcE+UdVBiyMGDhetW2QOKyeUiPDb1Vn1H8pAi+/8Ywyz48//ig6SsbwoM6DfCTO593AHStLJMxsgGbdVF83hkpYWJjIMtu7d2+cO3dOGU+1W6h4I+UqIKGkNL7//nvh5CtrKEh4oUib0khNzMXcbueR8dppeKeonGPpGzFqcH08d6QFHFzKln34888/x/79+0Xbz88PS5cuZT8RxiCzsdp4WKPj2vaimm/WA9+PFEsr9HrStcDyVM19wSsXYGfhofhKVVrxR8lACAkJkfLy8iRT58j6BCkuOrvAuMz0XGndZ1FSbk6edPHiRalGjRrkgSR+L7/8ss72lakc3nrrLcnG3Fkyh6X0888/G+xpTUtLkz766CPJ1tZWuT/p16ZNG+nQoUNlWgf1AZp9wd27dyVfX1+t7ndadn6TE9JWtx3i93u9o9LhtQlaHcu+ffskc3NzsU36f/DgQa2WZxhdcOfOHeVZ6dixY5HzJMfnSP/MjpZWvnHnoWk/NT4qnpmN7julT/12SCvfDpPuhWVVyr6xMGIgxIRnSXP7X5Q2u+2Q5g25XOQ80dHRUmBgoHKzDR8+XMrNza32fWUqlwsXLijXtF27dgZ3evPz86VVq1ZJ/v7+BYQQT09PaeHChVrdo4WFEeL48eOStbW1st5ly5aVup7gPcnSX7X2SiteCZNysrT7yImJiZG8vb2V7c2aNUur5RlGl7Rs2VLct2ZmZtK9e/fKvNz98CzpX7edihAv/2jcvGYnxbN050pGufeLzTSVTGJiIlJSUip1nTH/3UdQnyOoHRQh7Gp+x+/gzM6CHs/p6ekiHJJU4HKNgL/++qvyVGiMzqAYfrqeBEWWXLhwQXG+1HeCg4OF4xyZYMLDw8U4ql77+uuvi1BdysVR0Xu0U6dOmDt3rjJMdWFke3jE9UzM7XkeO+bfL7BM675OGH6tB578MQCWWpRBIKc/8lehrLBEv3798N5771Vo/xlGF6YaUkbs2LGjzMtdux2MD/NWYrNNIuIs1KZMS0gIjI6H24orONftABY0PoHf5iThzj3tEjSyMFKJXLp0Cb6+vvDw8BBOeZSRsaJEbYjGmSeDkRevSu6UaW6B2JEN0bynQwFHOqoKKqfl9ff3F5EzDg7qeRjDZvLkyUr7x/d2YF7rM1g04BL0lZiYGMyYMUM4qMohgMTgwYNx8eJFkdadkphVFiTUyMXpqFT66MdGY/+nV3Cs+xHUuRSNe19eQUZKQeGtPJWpyU+FIhGImjVr4s8//2SBnzGKEN/S+Hr25ziftBy/RU9A2qe34PhrR9zpGohYW9sCAoX//UR8tNYSgWMldJyRj9kryyaUmJF6BAYAvdgDAwMrnFilKiHvfs0vNPriI297+nJq1KiR1uuLWBWJ8y9fVHnXAfAY6AmPd5ugbquCzn30lfnDDz8oRZGOHDmiZKpkjIPk5GQR7pqenIdl7hvhnE+5WYGAdV3Rqo8T9AnSgHTo0KFAdAt53dM9Wt6KnpqaCdL+FdUXUPr4Pn36IPFUIp63fwH1LOsr09IsLOG3oB26jCy/AHTixAl0795dJI2S63IMHDiwAkfDMNVPbm6uEKQpt4+zszPu379fahJM0jTK0Zj0sUsJCeWaS/RMntqSgnPL78H65D0k5lnitXqdlGUtLYCcfaW/t/X3zW5g0AXZuHFjgXGksVi2bJlICkPhT3Ilz7Lw52t3cP5FtSDi/7QfOqxs85AgQsKPLIiQ8LNu3ToWRIw05whp23KkVGywUFXyJePG4XfVYan6AkWZyIIICceUEIxMSxUVREoj9Z6E75v8iO9q/FBAEAlt7oOuR7tVSBAh8yule5cFkXfffZcFEcYgsbS0xKBBg0Sb0sJTJuPSmDVrltKmj2vN4o/0UdBpuDNmrGuIyXd6oN+Odpg11QytG6im91VZmEtHMhD0PZrm6NGjikNbv379pE8//VRydXUt4LAnO5WeOHGixHUtnRFawEHo4juXhRNgYbZs2aJ49NPv999/r8IjZHRNZGSkcNS0MXeV/vTcrdwfp7YnSfpCRESE4kzq5OQkhiuTohxYyQF1+cth0hqNc0K/X2rMlZpYNpH++uuvCm2Tnr3Ro0crz1mXLl2k7OyCEW0MY0isWLFCuZ/ffvvtEuc9e/asMi9FrmVmZpZ5Ozcj8qWzNx5+dxVFuTUj9JVPqthFixYp46iyJuVF6Nu3r8imqGkBIn8K+rLo1q2bsCXLDmDGApUOlyHTDOVKIHXy7NmzhUpMZtOmTcLhjtS7Bw8efGg9X/+Rh9TNkcpwRM/aaPpV44fyF5BjIGlb5Cx6VFBs+vTpVXR0jD7g4+Mjqvlm5SdgrZlay3byA1UNF32AtCBy8boXXnhB+FBVJScuS/ik+zW4/3kFDnkqrYWFkyXih8bileSXcCX3iqikq5nPRFso5bz8fJOfy6pVq7i2E2PQDBo0SHmnlOY3QppOGXrPyKUYykI9XzO0ql/GgqxSOaCvkkmTJklPP/20CM0jKE/AkCFDpPDwcOn+/fvSuHHjpI0bN4ppWVlZYhoNk1T166+/SlOnTjUazQh9OdWuXVtIjpaWllJcXNxD+RUoP4RmPgT516NHD2nHjh3i2D5clCehR57k3CVD+s3rkLRwwvUij5nOsY+Pj7IOOtf6em6YyuXKlSvimluZOUrLa6o1AUc3aJcnoyqgkFc7Ozuxf/Rfm7BBbTUj9+LypGmzVc+Ld8cU6R93Vcjhr93PSTEhGeKZfOaZZ5RnpE6dOg89l2WBvgptbGyU9ch9GsMYOp07d1bu69u3b5eaVsDLy0tKT0+vsv3R3p0cwIYNG0S4oVzam9i2bZuoo0GZCGXtAJUBf+yxx0Q4IjnIUJugLxUKiaOsiUV9OdGXVeHS4JRZUV9rcpBzz+3bqpLjlFWSvp4095XS8NJXInn8L1++XGhL5EgbSq1LVUprdV6Ge1ZPinFJltZI/qIj3pisujya66Kw4UcffRRRUVFiuEuXLliyZMlD8zHGCTmCUjZderZW4zRegKpuS/DHN9FpRFmNs1UDRZpkZGSINt3rFFVW2fdkdmYe1q+3wlf7JcQnq764om3ssblFYzwxxQHPP8gYSVrZX375RfiqUJQZPW+kmaWvwLKGElP/RtpHcoyVHdQpfJ6fM8YYGDx4MI4fPy7aFH35/PPPl6gVeeutt4RWpDz3f1kCTyzL48hFakoyyVB4ngw97LJTDFG/fn3cuqVyrgsJCUGDBg0KvJxJaKHxRQkjlFZ54cKFBcZRqmdKIa2P0LnQrDIq5/ooCjLPkBmLLj45n4bcCsUI3z+w01yd339064MY2dMPYWEFO01yniNTjKxypuiKn3/+WYRRMqYDmWpIGPnv/qcY47kFtXJzUDsyDht/vYW2w8r1fVEp0T6//vqraNOHB734S3oOysPNk3kIfe8e3NNzkVa/FmBuAUfbfLw6KhFP98+DpUUywsIK5t8h5+4RI0YgLi5OlE2n2jHUqZYFmo/S0xPNmjUTHxSVfUwMoyvatGlTQMFQ2MGcImaoWCXh7u4uPprLe//XqVOn1Hm07rnmzZsnEhiRl3zhpFuaeS2oLX8l0f/COS9omJYpiilTpoi8GZqQJoBCivQxtHfPnj3iP9ngnnnmGXh5eZW6DHWKzz/7In7seRotQ5PR5U4wPgpojayQF7H+0CJc2NlQ2OfoPFDnTl961BlScTHC1dVVJKwpT8gwY9hQWGvXrl1x9OhRrJKO4FV0FOPv/5aAwBd1UzH2iy++UDSlVMW2c+fOlbr+a6cycP/Vk/B7oDEdGxuK/Cfq45vnzeHtTuXPVSXQizpXa9euxYABA0R0G1X7Je3lmDFjStweaTBlPxFHR0fR1vygYhhDJyAgQNS9Iv9Niqgh30bNmlBUjVf2+3z77bfRuHHjKt0frYQRqqR5+fJl8ZIsDJUmTktLU4apLR8Y/decJk+XyxkXhsKGNEOHCHohkyCib8IInQ86LwTlICAnw7KqmxcPuCwEEaJJeiL6p87H1rsqh2DKTknmLCrVTOebQrCo1Lp8LiiMmEKGGdOEvtrJLLrn/iyM99qBVHNbrLCpjQZBQL/21fuMkBBCDusEPZ8U+leZz2nkzUycHHMGng8Ekbv29pj0jhv6TynbNij3CJmQ5Iq69MFAmg76FQVpQ+SKwLIDKwv9jLGaapYsWSIUBhRQQcPy+4cqvRNkbp05c2aVv3vNtfWNIDUNqXPIJENqT/qCoJLfpIYhtY4MmWjq1VNVk61bt26BaZQhMSIiQow3piia0aNHl2mZzLQ8LOxxHnWu3hXDuTBDzustsfnsK9i9e7f4cpOh8003gmbKabp5yBzEmC7ku0D+I/nIwTu5q/Bq3U444+SBj5ao/CWqk99//12YQQjSmsrPfWUQfzcH2wYFwTNdpWW95+iAlqt80XdS0ZqQ4njppZeEH5v8IUSCHJmcC0N9E5mD5Y8nElwKa2kZxhizsW7btk1pf/nll4pvyBtvvCG0g1WONt6uGRkZIlJG/r377rsiSiQ5OblANE1sbKw0YcKEAtE0gwcPlv755x/Rnjt3rtFE07Ru3VrxNg4LCyt1/tTEHGlu69NKFARFAWz67u5D8x0+fFics8LRN5988kkVHQljaFAkm+q+MJeceoeJyBL6bT9etrj+yoD6BPKyl+9PqhpdWdCzolldd4X3PulGUFq5+wKKaqMKwfK+Dh069KH1zJw5U5nepEkTKTU1tdKOh2H0jaSkJMnKykqJOKMotJs3b0oWFhZinJubm3i/VwcVSnr28ccfK6G9xJIlS6S+fftKvXv3ln788ccCibqokxo/frzUtWtXadq0aVJUVJTBCyO3bt1SOq4OHTqUOj+VZqbqhnLnusH9P2n7vJgSlzl9+rQ0cuRIydHRUXrttdeKTH7GmCYFBAGPMYow0n5abrU9K/PmzVOeAbpPKwtKZPZr+yDlWVldc490dm9ykUnPtCE0NFRyd3dX9vmjjz5Spq1bt04Zb2trK8IaGcbY6du3r3LfU+oAUhTooiI1Z2CtAN98841y0b7++usS542/ly3Nb3xc6VzXe+ySdi+JrcjmGUb68ssvH9yDZpL7gDCpWdtY6Su/E9K/3z6sbatsKAtpYGCg8gyQ4FwZkKAxt98FjWflP+nQmnhlWkU/THbv3l0gczFpbGmdzs7OyrgFCxZUyrEwjL4zZ84c5b5/6aWXRK4satPzkJiYWG37oV/eoAbsLzJq1KgS5137QigCYlQ26nQLS3j83A79prhX+T4yxg3Vq1HZcyV4n/0a39w+jZbpCbg/9ybycqs278xff/2lhPpR2J9cSKuiZGdIQFyW4k9l90lrdB+ryh9SGVCOI8r1oxkqTc8vOYkT5DPC2YwZU2GIRkgv5eaR6y+9+uqropBedcHCSDkhB1yq4klQhdzSwv6eWlIPt/3ckWphCd8F7dDz8crrXBnThUK8qbwCcfH+fIQ4qMp5eyen4tB8ddXcyobCZL/66itl+IMPPqi0dds6WGDq0daiwF3Wi80x+AVPVDbklEcJzeREgmfPnhVtcqonh9zC5RcYxlhp1KjRQ8EklLpDjj6rLlgYKSeaFXrLEkVj52SBpw+0RuM1nSpUPZRhCkNfMFSJk1idq9bWmf91C1Je1UTWUJIkOSFYz549RVh7ZWJjZ4EXDrTA2E/LFiqvLSRsLF68uECFawqZp3DG6vwaZBhdY2Zm9lDCs5dffll86FQnLIxUUUjv7YsZuHqiYG4VRxdLtOxdDSFSjElByQAppJY4Ev0LMgJUyQRTr6chan3lF6QkXzNKclaZWpE9S+NwM7joJIhVBSVe/Oeff5QkhZStlYp/Mowph/g6ODjgtddeq/Z9YGGkHFD6daopQ1Cuh8LJk26cSceBR07h1KjT1d7BMqaJZorz3+7PV9o3vrmJ/JzK9R2h+i5ySYL27duL7KYV4ci6RCS9HYwTQ04ieHcKqhNST1+5ckXkRaIMxwxjivTu3Vt5j33yySci/Xt1w8JIOfj333+VhDDk+KZpX067lYagkafgmZEB98xM7Jp0ufKuFsMUA5kb5OyJuyN3Ibdhjminh2YgeH5klWpFKuJfkXI9FdEvBcE2Pw+u2Vk4OktVcLI6ocKWxpCAkWHKC9WLO3LkiMgo/uabb0IXsDBSiSaahFOJOD7sFJzSMsXwPQd7DP6r6JTTDFOV2pFFSepCk5e/DkFGSl6lbGPfvn1KpU+q3E2ZYMtLRmQmTo05A/tsleB0p5YrJm/iEgcMowvIV0qXJUZYGNGShIQEpTAeFeGicEb6WgyZexvHHz2JrHuqkETbBo4YsLsDajdXFx5imKpWtZLZhNh8ZRNu1Kwh2u5ZmVj3QUSlbENTK/L++++Xu15Fdnw2To05jcxIleDu0NwJ4/a2gYOzbqoOMwyjW1gY0RIq3S7HYZOJJuZONhZ3DMLVj65BylVFLrh2ckH3rR3g11AVZskw1QGZS6i6psw+183i/52aLgjsohJMKgJV9ty7d69o169fX+TjKA/JcTk4OSFIONgS9nXs0HltO7h5WVV4HxmGMUxYGClHSKNMc/cJ2NXlOHxCYpVxdV+pg07/doC1e8GqwwxTHZCALPs//HvsK6R+6oUZlzpUSl4bTa3Iu+++CwsLC63XkZWRh5V9ziH5jCrBmE0ta3Rc1x42NW0qvH8MwxguLIxoWSp9586d9A0Kp8afYOn6ALhlqdTMKZZW8PqlDRp/1BDmVnxaGd1AAgIl9JL55+jsSin9TUnBKIpGDiWmrKXaQhlhF/W/iMBIVYXfTCtLtF/TDva17Su8fwzDGDb81tQCKrGcmWsPNP0XKZ4f4rBjTfzr5o9wTxd03N0FbZ+oWXVXimHKyOTJk+Hh4SHaa9aswe3bFY9QoZLiMmQKsrbWTvNHflVvzpNwMlblQ5VlZg7Xb9vAuXnFzUcMwxg+LIxowZrFN4A2ZwB3dYIYz9cbYsrZ9qjTgh1VGf3A3t4eL730kpK2nZJ5USj69rn3Mb/5KcRFZWu1vqtXr2LdunWiXatWLUydOlXrfZq9EvhxnRmW16qPhd4NYfleS/R5yk3r9TAMY5ywMFJG9fLCSTcw6XQH9M9Q2ck9XSTs+M4Mnz9vCWtb7W3nDFOVUAIvEkqIRYsWYcHj1yB9FITA6HhseOOOVuv6+uuvhWaDeP3112Fnp53gvWiLhPd+V6elHza7Noa9UUurdTAMY9ywMFIK0SFZWNAuCL5bQmABCc9HX0UrXMTZJeYY1JGLaTH6CWVQfOaZZ0Q7PT0dER4HkQfV/eq6J0xEgZWF0NBQ/Pnnn6rlXF3x/PPPa7Uf/865h58+jVeGv37WDM8M5eeGYZiCsDBSAvtXxmNvt2OoHaFyuKOcqxutwvHZ6xHw8eAOldFvSIshO68uXPshwlp6i7Z9Xi42vhZapnV88803wtQjF8+iap5lZe+yOEhfncdnoUHolByD18cBbz9RrkNhGMbIYWGkGLPM4kkhSHn5tEhRTSRaWOLD/LXYlP4aBg3uV93XiWG0pk6dOkoukPv37yOjx3nkPEjd7nkwHJE3Vfd2cURFRWHJkiWi7ejoKISRsnJqaxLi3zoLaykfNlI+nqxxH9/ONKtQ6niGYYwXFkYKEXUrC7+3DYL3lhvCLEPccnPES0kv4mziYjz66KOwseGcCIzhpYj/fdUniGznK9pUC2ZTKdqROXPmIDtbZc6ZOXMm3NxKdjilStWr3o7A3E5nETb5lNDAiPF+Hpi+synMzVkQYRimaDj3sgYnNyfhxoxgBD7QhpBZJrp/XZyvMQfxi64qSaUYxlBo27Yt+vXrJ0oY3Lx5E7YvhyLrjI3QVngdC0fYpUAENnvYITU2Nha//fabUkSLTD7FJTFbOu4GrC7EwTslFc5U40Jjeri7M57a3wo2duzkzTBM8bBmRAO/pur07UlW1rCZ3Q7P/FUXmzZtFOMoiuCRRx4p4XQyjP6hmSL+txWf4W4XP9EmgWTrG0VrR3788Ufh+EpMmzZNhPRSeHBhx1cSMuyCY4QgokmahSVCm/lg1N62cHLlbx6GYUqGhRENfOrZwPe7lgjzcUf3/V0wYJoHDh8+jJiYGDGdSrQ7ODiUckoZRr8YMGAAWrVqJdqnTp2CzxNxyDRXaSp8T0fgZrBK6JBJSkrCr7/+KtrOls6Y3vpZzOt3ESv9DmFTr1MPrT+tqbvQIka41kBEvzpw+KUDRtzpjRcOtoCnH5dFYBimdEz6k2Xf8jg07OoA3/pqjUjviW7o+biLEoWgWYtm9OjROtlPhqkI5DRKviNPPvmkGF648msM6zkH/vtv46yDG/avycMPbVTz5mbn4+e31mBI1lC0dWqHxtZNEPF2JGrLK8sCwq9mwr+x+pkZ8n1d2DrWh1dt9qViGKZ8mElyNiM9h/IdBAYGVkqdjYTLqVj1+h34nwpHhI87ZgS3hYXlw+sltTRtMyIiAlZWViIiwdlZ0yLOMIZBTk6OqLR7544q4dnBXefx2ie+OGPuAqp399PjWcDia/C4HQ+n3Jwi15FtZo5oLxd0+bkxWvcte4hvZULPZFhYWKX1BQzD6Acm8zTn5+Qj+t+7ODHiFI71OILap8JBiurAqDis+yS6yGVIpU2CiKzqZkGEMVRImNZ0Ql385xwMn6aq5EtpRN5cZgG/WzEPCSIODRxQ+9kANP6jLfrd6IPnL3bQmSDCMIzxYvTCCNnDV0y8jn0tDyD4mXOIO6zOBknFuqIG18foj1TJoAqzfv16pc0mGsbQoZoylEWV+OuvvzC2axTcHtSpy7SwxBU7F6SaW+CwTQ5+zlkDnzW10Ot4dzT9sgnqDvNkR1SGYaoMo/QZyc+XsOO4hJCXziHwdgzcVaZuBYd69vB+yh8uI3xQM6BoBzuyXsnCCJVlHz58eDXtPcNUDZS4jPKFfPHFF8Jss2Thj/jni28w7x8JDf2B1OuReHz2eOQjByNGjEDrfq35UjAMUy0Ylc/I/UQJS7YCCzZJCI0G3gs/h+7JqkiYfDMz+DxaEwFT/OHe063UTJDnzp1D69aqzrhv374iTwPDGDr37t0Tz1FWVpZI7R4eHi7Mj7m5uWjYsKF4zoiTJ0+iQ4cO0DfYZ4RhjBODN9NQ50Q1ZH7qdRG1R+bh3QUqQYTY6uqPBGsbRA6qhxYHeqDtH63h0cu9TCmp2UTDGCOUL2Ty5MminZKSggULFoj2qlWrFEFk4MCBeimIMAxjvBisZiT+bg62fhmF7E0RSsKlb3yb44CLyv9jYAfg+RHAkI4SrG21z/7YrFkzXL58WQgukZGR8PYu2q+EYQyNGzduoFGjRsIUSff1rVu30K5dO1y5ckVMP3DgAHr27Al9hDUjDGOcGJzPyKltyTj1/R14nbsL93xVNVGZgel30eE5bzw73Az1/cpfB+Pq1atCECG6du3KgghjVDRo0AAjR44UOXSio6MxYcIERRDp3r273goiDMMYLwYjjOz5MQt520/CPy5JnYBJo/6Fyzh/vPJWLTg4V9zypJnojGvRMMaaIl6+zzdt2qSM/+CDD3S4VwzDmCoGY6bZ5r6zwDCls77bygsdXw9A+yEP4hMrCVJZBwUFKeah2rULiz8MY/j06tULBw8eLHDfU26dsvhU6Qo20zCMcWIwmhGqfUE6j2gnR1gP98PQ933g5mVV6dsh4UMWRKhzZkGEMVYoRbymMEJaEX0WRBiGMV4MRhi51M0FHcfWx5SJrlWaBppr0TCmwpAhQ4TAfebMGbRt21bkFmEYhtEFBhPa+/m+/sipdabK61GwMMKYCvQs7dixA8uWLcPOnTu51gvDMDrDYHxGSH1saWmJhQsXKnkSKpuoqCj4+voqob0XL16sku0wDFM+2GeEYYwTg9GMEJQlcsqUKfj4449FjoTKZuPGjUqba9EwDMMwTPVgMMLI008/rbQ/++wzoR3Jzs6u1G1w1lWGYRiGqX4MxkwTEhKCf/75B2+++aaiFenTp4/w8XBxcanw+mNjY0WqbFID169fH9evX+fIAobRM9hMwzDGicFoRshn5NVXX8XatWtha2srxu3btw/dunVDWFhYhdf/77//io5OTnTGIY4MwzAMUz0YjDCi6cuxd+9eeHh4iGFK2965c2cRnlgR2ETDMAzDMLrB4IQRokuXLjh+/LiosUHcvXtX1NPYsmVLudaXmJiI3bt3i7a/vz9XLGUYhmEYfRZGvvjiCwwaNEikkh4/frySwXHz5s3o1KkTevToofxISJC5dOmSKMhFZpUZM2aIAl0VoV69ejh27JhYH5Geni6SNs2bN0/rdW3duhU5OTmizSYahmEYhtFzYWTixIlC8KAy4x999BE+/PBDoVkgKJvjoUOHlJ+Xl5cYT1EvVJiLhBEysbRq1UosV1Hc3d2FRmPcuHFimHw+XnjhBZHmWvb/KAuaJhoujMcwDMMwei6MUK0Wa2tr0SYnT8r9cf/+/RKXIX8OKysrPPbYY7CxscHUqVNFyfLIyEhUFHJmXbVqFd555x1l3HfffSe0NhkZGaUun5aWJrJQEjVr1lQ0LQzDMAzD6HFtmq+//lpoR7KyssTLm0Jhr169igsXLqBfv35wc3MTwsCYMWOUsFzZv0MWIPz8/MR4OeOpJqRJKZxDhMwoJWk7vvzySwQGBuLFF18U861bt05kVKVEZrKza3EmGlloIWGJBCxttCoMw1Qf8rPJzyjDGA5lKeNSLmHk3XffFaYQ0njcunVLvMCp0Nbff/8tTDMU4UL5QFxdXYVwQi97BweHAuugYfLzKIqlS5eKtO+ajB07VjHHFMcjjzwilnvppZfEuo8ePYqOHTtiyZIlqFOnTpHL/Pnnn0q7ssKEGYapWsLDw/kUM4yBUNz7t1Kq9lpYWIgXPZlIKAKle/fuyrTmzZsL/xDKA0LCiJ2dnTCHaELD9vb2Ra6bUr6Tb4ompOWg7ZQmYVFmVvJJGTZsmHCSJeGChBhKmNa1a9cC85JmZ//+/aJNghNpc8icxDCMfkIaERJEytIXMAxjOJRbGJHJy8tDRETEQ+NJWyJnSq1bt64wm8hkZmaKZWh8UZBPiuyXIkNCAnU+ZemAyJGWQn+HDh0qit3FxcWhf//+WLFihdCwyOzZswcpKSmiPXz4cOHPwjCM/lPWvoBhGMNAq6c5NTVVOHuSCYQcVymS5fTp02jTpo0wiSQkJIj5yH+ETDaU+0MWDkgLQVlOyReEzCZNmjQp0l+ksggICMDhw4eFEELQ9klDQs6tspDEic4YhmEYxsBq05Aw8sYbb+DatWvihU6q0meeeQZ9+/bFDz/8gG3btgn/EIpKoRc/mWo084zMmjVLqFibNm0qit15e3uXeUdDQ0OFg6q2X0Mk/Dz77LP4448/lHEzZ87EnDlzhDAUHx8PR0dHEREkp5lnGEY/4do0DGOcGEyhvPIKIwQd4ueffy7yosi0aNFCRP8Q5CuyevXqSt1fhmEqHxZGGMY4MQmjK/mvUJK15cuXKw6qsiAi17thGIZhGEY3mIQwIvPUU08JnxdnZ2dlHJlmBg8erNP9YhiGYRhTxqSEEYL8W44cOSJMPsTTTz8tfEYYhmEYhjHQ0F5DpFmzZiIx29mzZ9G+fXtd7w7DMAzDmDQmKYwQlHCtcBI0hmEYhmGqH5Mz0zAMwzAMo1+wMMIwDMMwjE5hYYRhGIZhGJ3CwgjDMAzDMDqFhRGGYRiGYXQKCyMMwzAMw+gUFkYYhmEYhtEpLIwwDMMwDKNTWBhhGIZhGEansDDCMAzDMIxOYWGEYRiGYRidwsIIwzAMwzA6hYURhmEYhmF0CgsjDMMwDMPoFDNJkiTd7gLDMAzDMKYMa0YYhmEYhtEpLIwwDMMwDKNTWBhhGIZhGEansDDCMAzDMIxOYWGEYRiGYRidwsIIwzAMwzA6hYURxmCJiopCp06ddL0bDMPoEO4HjAMWRvSMUaNGYeLEiTB1hg0bhrNnz8LUWLt2LUaPHo1u3bqJc7Bw4ULk5eWVuMzmzZsxc+bMattHpurhfsC0+wFT7Assdb0DjJqLFy8iNjYW2dnZCA0NRZ06dbQ6PZS/jn7m5ixjGiJLly4VHdDnn3+Oli1bIiQkBP/73/9w//59vP/++7rePaaa4H6AWWqCfQG/tfSI7du3o1evXsL0sG3bNmV8+/btsXr1agwdOhSDBg3C8uXLlWmffPIJZs+ejeeeew7du3dHREQEjAk6vkWLFhmF5F8Sqamp4jjfeecdtG3bFpaWlmjYsCFmzZqFf/75B2FhYUhISMAHH3yAAQMGoF+/fvjll1/E9f7qq69w5swZ9OjRA+PGjdP1oTAVhPsB0+0HTLkv0BthxJTVcURubi527dolbq6BAwdix44dQsshc/jwYfz9999YsGABVq5ciZMnTyrT/vvvP7zyyis4cOAAfHx8dHQETEU4f/68uAdIoNSkUaNG8PLywunTp8WXka2treiQtm7dKgRXPz8/vPfee2jXrh0OHTqENWvWGPyFMOW+gPsB5ryJ9gV6I4yYOsePH0dOTg66dOmC3r17Iz4+HsHBwcr0yZMnw9HREbVr18aIESOE4CLTt29fNGnSREjQ9GMMj8TERLi4uMDCwuKhaW5ubmI6ffG8+eabcHBwEB0RqW8Z44L7ASbRRPsCS320l37zzTdCFeXk5IQnn3wSEyZMENNIKxAeHi5e2seOHRM+FV9++SV8fX1hDKpZEkKsrKzEr2vXrmIcqekIkohlatWqhRs3bhQYZgwbZ2dn0cmQg1rhTogEUxpHHZGdnR1MBVPsC7gfYJxNtC/QO80IfdmTg86+fftERzR//nxcvXpVmU7jx44di7179yIwMBC///47DJ309HRhYqFjIp8Q+p04cQJ79uwRzqzE3bt3lfnv3bsHDw8PmAL0wGVlZSnDcXFxMEboy4bufTLHaXLt2jVER0ejRYsWwk6cmZn50LJmZmYwRkytL+B+oHhMpR8w5b5A74SRxo0bix9FhDRt2lSENZ07d06Z3rFjR+HQSReLfCs0NQSGCnWmNWrUwPr164U/CP3WrVsnJGD5hiSnVXJsun37NjZt2oT+/fvDFGjQoAGOHDkijp0ctOjYjRH68p8yZYpwRg4KChI2Y7q3P/zwQwwfPlzYgUlLNmfOHPHSoo7owoULYllXV1choNIyxoSp9QXcDxSPqfQDptwX6J2Z5tatW+IkX79+XahgSTNAfhIypJ6SIVsZXQxDh1Sz5AdSWNtBNx5NI8hsM378eHFOnnjiCZNJ9jVkyBChhqdIIroPSGuk+UIyJqZNmyY6IgrnI00Y3evkzDl16lQxncaThoDG0RfQyJEjxVdShw4dhOMyOT+TyY4ir4wBU+sLuB8oHlPqB0y2L5D0hEcffVQKDg6WZsyYIc2fP1/KyMgQ49977z3pt99+E236/9lnnynLnDp1ShoxYoRk7LRr1066e/euZEr07dtXCg0N1fVuMDqA+4Ki4X6AMWb0zkxDXzcUNWJjYyOiSUg1x5gWFLpGYc3e3t663hVGh3BfYNpwP2Ba6J2Z5qWXXsIXX3whnNHIFNGzZ09d7xJTjdC1p/BGclwkgZQxXbgvMF24HzA9zEg9Aj2AssgtXry4gE2YYRjTg/sChjE99MJMw+o4hmG4L2AY00XnZhpWxzEMw30Bw5g2emOmYRiGYRjGNNELMw3DMAzDMKYLCyMMwzAMw5iWMEJpzidOnCjCdqnYlQxZi2iYMuxRwTjKMEdZF2VmzJghspD26NFD/F5++WVlGtUsoGx0lJWPPPHnzp1b3YfFMEw19QXEsmXLxHQK/aeMxGlpacq0P/74Q5RLoGrWP/30k1gfwzD6TbULI5TynAQL6ig02bx5sygMt3TpUmzdulUUQlq4cGGBef73v//h0KFD4vfzzz8X6Hxu3ryJtWvXih8Vmfvnn3+q7ZgYhqm+vmDNmjUiNTilAqACk59++qmodE1QLSfqA6hPoPmOHj2Kf//9ly8Pw+g51S6M0JdOr169RN59TagTGTVqFGrWrAkHBwdMmjQJW7ZsKdM6aVn6wqJic5TD//HHHxcdGsMw+kt5+gIqq75kyRLxYeLl5SXqclARNWtrazF927Ztok6Hn5+fEHaefPJJMY5hGP1Gr3xGCqtTY2JiRJVGme+//16oX2fOnPlQhU7NZakdEhJSDXvMMEx19gX0n6qU7t69W1TqJaFl48aNynyhoaFCOJGpX7++KLjHMIx+ozfCCPmDrF+/HtHR0UhJSREqWiIjI0P8Jx8RKhtNX0hkY6Zh2U7cpUsXrFy5EomJiYiNjRWVCuXlGIYxLErqC2Sh5M6dO6I/oDLr5CNGdazkejakTZGhNvcFDKP/6I0wMnz4cFH2mGzI48ePR8eOHWFpaamUCW/evDns7e1FqXBS21L7woULYtozzzwjvoDIkY1KLPfp00eUT2YYxvAoqS+Q6xVNnz5d9AWkBSENiVxQk/oFTWdWatvZ2ensWBiGKRt6I4yYm5vj2WefFb4eZOOtV68eGjduDAsLi2Lnl6FO6Z133hHLkbOas7MzmjZtWo17zzBMdfQFgYGBwlmVfEVkNNt16tQRzuwyZKKh5RmG0W+qXRjJzc0Vobj5+fnCGY3a9J9MLBEREcJWTB3IDz/8IL5+CFLVUiXX7OxsEeJHJpnk5GShLSHu3bsnzDO0zvPnzwu1LmlIGIbRX8rTF5CWQy6kR/0B+Yjs2rUL3bp1E9OHDBmCDRs2iOUpCof6ChrHMIx+U+3p4Cl/QOGQ3Y8//lgIFq+99hru378PT09PIUwMGzZMTE9ISBA+ImFhYUJd27BhQ7z66qvia0kutEfroE6MvOip9Hj37t2r87AYhqmGvkD+OPnss89ECL+LiwsmT54sHFll6GPkzz//FELOY489JvoOTe0JwzD6B9emYRiGYRhGp+iNzwjDMAzDMKYJCyMMwzAMw+gUFkYYhmEYhtEpLIwwDMMwDKNTWBhhGIZhGEansDDCMAzDMIxOYWGEYRiGYRidwsIIwzAGTfv27cWP0sczDGOYsDDCMEypUNE6+aX/+OOPF5hGmY8pHbs8/Zdffqn0M0qChrx+hmGMDxZGGIbRihs3biAoKEgZ/ueff0RdGYZhmPLCwgjDMGWGakMRf//9t/hPhe3WrVunjNckKSkJs2fPxtChQ9GpUycMHDgQH374Ie7evVugPg1pO6j2zO7duzF69GhRV4oK492+fVvM88knn+DTTz9VlpE1JLSsJqmpqWK+Xr16YfDgwVi0aBFfWYYxEFgYYRimzFCRSl9fX+zfv19Uyz548KAQLqiSriakKSHTztq1a0VF7cDAQKSlpWH79u2YMmWKKH6pSUxMDP73v/+Jgna0bHBwsCiGR1DxS9qmDBXSo1+tWrUKrOPXX3/FsWPHYGVlJYrs/fbbb6LaN8Mw+g8LIwzDlL3DMDfH2LFjFY2IrCEZP358gfl27tyJW7duiTZpR9asWYPFixeL5UlQoGFNaH3ffPONWKfsk3L+/HlkZmZi2rRp4ifzxx9/iB9V5NWkUaNGwrdEU1Nz6tQpvroMYwCwMMIwjFaMGDECdnZ2QqA4ffo0mjRpgpYtWxaY5/Lly+K/ra0tevfuLdqNGzcWGhLN6TKOjo7o2bOnaNetW1cZX1iDUhL9+/cXWhEXFxe4ubmJcfHx8Xx1GcYAYGGEYRitcHJyEj4ZZHYpSitS3nXKWFhYKG1Jkiq0Dm2WZ/7fvh3iKAxEYQCeNZBgGgJ4RGtQ3IIbcA4cd8FUcQxugcBW9AQVOJZ0kiXZZZOFNS9pvs9Mk5Fj/rz3F+III8DbttttPqfTaS6m/rRarfLZr1n6fknvcrmkpmm+3b+qn7B8uV6vXgwG5rkCD/CHsizT6XTKE4jRaPR0v9ls0vF4zL2R/X6f1zNt26bb7ZYWi8UjzLxquVw+vvvOynw+T7vdLq3Xa28FA2AyAvxLURS56/Gb8XicDofDIzj0E5HJZJLXO3Vd54nKO6qqyiXW2WyW/945n8+p6zovBwPx8WmpCgAEMhkBAEIJIwBAKGEEAAgljAAAoYQRACCUMAIAhBJGAIBQwggAEEoYAQBCCSMAQChhBAAIJYwAACnSHapwbdLRFHzUAAAAAElFTkSuQmCC", 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" ] @@ -247,17 +264,21 @@ } ], "source": [ - "pred_trained = model.predict(\n", + "pred_full_finetuned = full_finetuned_model.predict(\n", " n=len(val_passengers),\n", " series=train_passengers,\n", ")\n", - "pred_loaded = loaded.predict(\n", + "pred_full_finetuned_loaded = full_finetuned_loaded_model.predict(\n", " n=len(val_passengers),\n", " series=train_passengers,\n", ")\n", "val_passengers.plot(label=\"Ground truth\")\n", - "pred_trained.plot(label=\"Forecast of the trained model\")\n", - "pred_loaded.plot(label=\"Forecast of the loaded model\")" + "pred_full_finetuned.plot(label=\"Forecast of the full finetuned model\", linestyle=\"-.\")\n", + "pred_full_finetuned_loaded.plot(\n", + " label=\"Forecast of the loaded full finetuned model\",\n", + " linestyle=\"--\",\n", + " title=\"Full finetuning\",\n", + ")" ] }, { @@ -265,28 +286,28 @@ "id": "d3dc22f4", "metadata": {}, "source": [ - "We can also verify that the prediction of the trained model is identical to the prediction of the loaded model" + "We can also verify numericaly that the prediction of the trained model is identical to the prediction of the loaded model" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 8, "id": "599402d3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "False" + "True" ] }, - "execution_count": 22, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pred_trained == pred_loaded" + "np.allclose(pred_full_finetuned.values(), pred_full_finetuned_loaded.values())" ] }, { @@ -294,26 +315,64 @@ "id": "3cabab8a", "metadata": {}, "source": [ - "# Partial fine-tuning with layer freezing" + "# 2. Partial fine-tuning with layer freezing\n", + "With this method, top layers of the model will be frozen. That means that their weights won't be updated during the fine-tuning. \n", + "\n", + "This is done with the `LayerFreezeCallback` available in darts. \n", + "\n", + "
\n", + "LayerFreezeCallback\n", + "\n", + "\n", + "Here is the source code of the callback method.\n", + "\n", + "It extends the `ModelTransformCallback` which applies a transform function to the model attribute (by default `model`) on the setup callback of `pytorch_lightning`.\n", + "\n", + " ```python\n", + "class LayerFreezeCallback(ModelTransformCallback):\n", + " @classmethod\n", + " def _freeze_layers(\n", + " cls, model: nn.Module, freeze_patterns: list[str], unfreeze_patterns: list[str]\n", + " ) -> nn.Module:\n", + " for name, param in model.named_parameters():\n", + " if any(name.startswith(layer) for layer in freeze_patterns):\n", + " param.requires_grad = False\n", + " if any(name.startswith(layer) for layer in unfreeze_patterns):\n", + " param.requires_grad = True\n", + " return model\n", + "\n", + " def __init__(\n", + " self,\n", + " freeze_patterns: list[str],\n", + " unfreeze_patterns: list[str] = None,\n", + " model_attribute: str = \"model\",\n", + " verbose: bool = False,\n", + " ):\n", + " unfreeze_patterns = unfreeze_patterns or []\n", + "\n", + " super().__init__(\n", + " transform_fn=partial(\n", + " self._freeze_layers,\n", + " freeze_patterns=freeze_patterns,\n", + " unfreeze_patterns=unfreeze_patterns,\n", + " ),\n", + " model_attribute=model_attribute,\n", + " verbose=verbose,\n", + " )\n", + "```\n", + "
" ] }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 9, "id": "33fa7fc4", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model transformed. Trainable: 72,280,224/119,477,664 (60.50%)\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "970d4406f6974c1085b70f9585de66c4", + "model_id": "5f830deafaf54b249882fcad5c672577", "version_major": 2, "version_minor": 0 }, @@ -333,30 +392,30 @@ " unfreeze_patterns=[\"output_patch_embedding\"],\n", ")\n", "\n", - "model = Chronos2Model(\n", + "partial_finetuned_model = Chronos2Model(\n", " input_chunk_length=12,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=100,\n", + " n_epochs=50,\n", " pl_trainer_kwargs={\"accelerator\": \"gpu\", \"callbacks\": [freeze_callback]},\n", ")\n", - "model.fit(train_passengers, verbose=True)\n", - "model.save(\"partial_finetuned.pt\")\n", + "partial_finetuned_model.fit(train_passengers, verbose=True)\n", + "partial_finetuned_model.save(\"partial_finetuned.pt\")\n", "\n", "# Load - no callback needed, structure unchanged\n", - "loaded = Chronos2Model.load(\"partial_finetuned.pt\")" + "partial_finetuned_loaded_model = Chronos2Model.load(\"partial_finetuned.pt\")" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 10, "id": "50830283", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fbb261b4924248879c6f3224ae0b331a", + "model_id": "3f92740814334e009f614fb2668b88c2", "version_major": 2, "version_minor": 0 }, @@ -370,7 +429,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8b52f68fea154de68b9bd3f5887178bb", + "model_id": "be8c720307a84928a25298ca935b3992", "version_major": 2, "version_minor": 0 }, @@ -384,16 +443,16 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 30, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -403,19 +462,25 @@ } ], "source": [ - "pred_trained = model.predict(\n", + "pred_partial_finetuned = partial_finetuned_model.predict(\n", " n=len(val_passengers),\n", " series=train_passengers,\n", " random_state=42,\n", ")\n", - "pred_loaded = loaded.predict(\n", + "pred_partial_finetuned_loaded = partial_finetuned_loaded_model.predict(\n", " n=len(val_passengers),\n", " series=train_passengers,\n", " random_state=42,\n", ")\n", "val_passengers.plot(label=\"Ground truth\")\n", - "pred_trained.plot(label=\"Forecast of the trained model\")\n", - "pred_loaded.plot(label=\"Forecast of the loaded model\")" + "pred_partial_finetuned.plot(\n", + " label=\"Forecast of the partial finetuned model\", linestyle=\"-.\"\n", + ")\n", + "pred_partial_finetuned_loaded.plot(\n", + " label=\"Forecast of the loaded partial finetuned model\",\n", + " linestyle=\"--\",\n", + " title=\"Partial finetuning\",\n", + ")" ] }, { @@ -428,7 +493,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 11, "id": "01717b70", "metadata": {}, "outputs": [ @@ -438,13 +503,13 @@ "True" ] }, - "execution_count": 31, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "pred_trained == pred_loaded" + "np.allclose(pred_partial_finetuned.values(), pred_partial_finetuned_loaded.values())" ] }, { @@ -452,26 +517,24 @@ "id": "b0d126dc", "metadata": {}, "source": [ - "# LoRA fine-tuning" + "# 3. LoRA fine-tuning\n", + "This fine-tuning method uses HuggingFace `peft` library. This library makes it easy to use **P**arameter **E**fficient **F**ine-**T**uning methods such as LoRA which greatly reduces the number of fine-tuned parameters.\n", + "\n", + "More information about peft can be found in the [official documentation](https://github.com/huggingface/peft)\n", + "\n", + "To use LoRA fine-tuning, the `PeftCallback` is used. A `peft_config` is required. In this example, a `LoraConfig` is used with the same parameters used in the [official Chronos-2 implementation](https://github.com/amazon-science/chronos-forecasting/blob/f889ae66477b53f6beb130f5c7b13590b29a1035/src/chronos/chronos2/pipeline.py#L202)\n" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "6981052c", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Model transformed. Trainable: 1,206,912/120,684,576 (1.00%)\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6e469e8f90df46a0b3673668261f603b", + "model_id": "f747f8932c964382b4e2c45025fac6ec", "version_major": 2, "version_minor": 0 }, @@ -481,6 +544,16 @@ }, "metadata": {}, "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=50, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" } ], "source": [ @@ -498,7 +571,6 @@ " \"o\",\n", " \"output_patch_embedding.output_layer\",\n", " ],\n", - " # lora_dropout=0.1,\n", ")\n", "peft_callback = PeftCallback(peft_config=lora_config)\n", "\n", @@ -506,42 +578,43 @@ " input_chunk_length=24,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=100,\n", + " n_epochs=50,\n", " pl_trainer_kwargs={\"accelerator\": \"gpu\", \"callbacks\": [peft_callback]},\n", - " log_tensorboard=True,\n", ")\n", - "model_lora.fit(train_passengers, verbose=True)\n", - "\n", + "model_lora.fit(train_passengers, verbose=True)" + ] + }, + { + "cell_type": "markdown", + "id": "e86085e3", + "metadata": {}, + "source": [ + "## 3.1 Full-model saving\n", + "Darts `save` and `load` methods can be used to save the full model weights." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "49b2c2e8", + "metadata": {}, + "outputs": [], + "source": [ "# Fully save the model including adapters\n", "model_lora.save(\"chronos2_lora_finetuned.pt\")\n", - "loaded = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")\n", - "# loaded_full = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")\n", - "\n", - "# # Save adapters using PEFT's native method\n", - "# model.model.model.save_pretrained(\"chronos2_lora_adapters/\")\n", - "\n", - "# # # === Loading ===\n", - "# model = Chronos2Model(\n", - "# input_chunk_length=12,\n", - "# output_chunk_length=6,\n", - "# enable_finetuning=True,\n", - "# n_epochs=10,\n", - "# pl_trainer_kwargs={\"callbacks\": [peft_callback]},\n", - "# )\n", - "# model.fit(train_passengers, verbose=True)\n", - "# model.model.model.load_adapter(\"chronos2_lora_adapters/\")" + "model_lora_loaded = Chronos2Model.load(\"chronos2_lora_finetuned.pt\")" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 14, "id": "41e8a82f", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "56b8b427e22348b19709bde1107f6367", + "model_id": "9423ea48aac342ea9600ae6f45f168ae", "version_major": 2, "version_minor": 0 }, @@ -555,7 +628,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "90797a2c2c8740cea37643d332b9f7e1", + "model_id": "01bbd79720504a9db991aed2291c721e", "version_major": 2, "version_minor": 0 }, @@ -569,16 +642,16 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 6, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -588,24 +661,36 @@ } ], "source": [ - "pred_trained = model_lora.predict(\n", + "pred_lora_trained = model_lora.predict(\n", " n=len(val_passengers),\n", " series=train_passengers,\n", " random_state=42,\n", ")\n", - "pred_loaded = loaded.predict(\n", + "pred_lora_loaded = model_lora_loaded.predict(\n", " n=len(val_passengers),\n", " series=train_passengers,\n", " random_state=42,\n", ")\n", "val_passengers.plot(label=\"Ground truth\")\n", - "pred_trained.plot(label=\"Forecast of the trained model\")\n", - "pred_loaded.plot(label=\"Forecast of the loaded model\")" + "pred_lora_trained.plot(label=\"Forecast of the LoRA trained model\", linestyle=\"-.\")\n", + "pred_lora_loaded.plot(\n", + " label=\"Forecast of the loaded LoRA model\",\n", + " linestyle=\"--\",\n", + " title=\"LoRA finetuning - Save all\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "32cef0b5", + "metadata": {}, + "source": [ + "Again, we verify that the prediction of the fine-tuned model is the same as the loaded model to make sure that saving/load works correctly" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 15, "id": "9a96ca55", "metadata": {}, "outputs": [ @@ -615,42 +700,144 @@ "True" ] }, - "execution_count": 8, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "np.allclose(pred_trained.values(), pred_loaded.values())" + "np.allclose(pred_lora_loaded.values(), pred_lora_trained.values())" + ] + }, + { + "cell_type": "markdown", + "id": "c633f2ad", + "metadata": {}, + "source": [ + "## 3.2 Adapter saving\n", + "Another method is to save only the adapter. This results in a light-weight folder containing only the LoRA weights which can be plugged to the original model.\n", + "\n", + "For that, we need to access the internal chronos model with the `internal_model` attribute to save only the adapter." ] }, { "cell_type": "code", - "execution_count": 106, - "id": "527ad900", + "execution_count": 16, + "id": "ce2fcd82", "metadata": {}, "outputs": [], "source": [ - "import torch\n", - "\n", - "model_without_lora = model_lora.model.model.merge_and_unload()\n", + "model_lora.internal_model.save_pretrained(\"chronos2_lora_adapters/\")" + ] + }, + { + "cell_type": "markdown", + "id": "6e2f159a", + "metadata": {}, + "source": [ + "Then, a new model can be created, and the internal model can be replaced with the loaded adapter" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "630bb5bc", + "metadata": {}, + "outputs": [], + "source": [ + "from peft import PeftModel\n", "\n", - "assert len(loaded.model.state_dict().keys()) == len(\n", - " model_without_lora.state_dict().keys()\n", + "model_new = Chronos2Model(\n", + " input_chunk_length=24,\n", + " output_chunk_length=6,\n", ")\n", + "model_new.fit(train_passengers) # Initialize model\n", "\n", - "for key_loaded, key_lora in zip(\n", - " loaded.model.state_dict().keys(), model_without_lora.state_dict().keys()\n", - "):\n", - " assert torch.equal(\n", - " loaded.model.state_dict()[key_loaded], model_without_lora.state_dict()[key_lora]\n", - " )" + "# Replace _Chronos2Module with PeftModel containing _Chronos2Module + adapters\n", + "model_new.internal_model = PeftModel.from_pretrained(\n", + " model_new.internal_model, \"chronos2_lora_adapters/\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "c1fddf83", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "73a4c844302a4b458ad0780a7e2898f4", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Predicting: | | 0/? [00:00" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pred_lora_trained = model_lora.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + " random_state=42,\n", + ")\n", + "pred_new = model_new.predict(\n", + " n=len(val_passengers),\n", + " series=train_passengers,\n", + " random_state=42,\n", + ")\n", + "val_passengers.plot(label=\"Ground truth\")\n", + "pred_lora_trained.plot(label=\"Forecast of the trained model\", linestyle=\"-.\")\n", + "pred_new.plot(\n", + " label=\"Forecast of the loaded model\",\n", + " linestyle=\"--\",\n", + " title=\"LoRA finetuning - Save adapters only\",\n", + ")" ] }, { "cell_type": "code", "execution_count": null, - "id": "ce2fcd82", + "id": "6f74bc02", "metadata": {}, "outputs": [], "source": [] From 76a8efa3893ca031be55647d7231ee5b119b3f64 Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 30 Jan 2026 17:05:28 +0100 Subject: [PATCH 07/11] feat: modify foundation model to integrate full and partial fine-tuning --- darts/models/forecasting/foundation_model.py | 273 +++--------------- darts/utils/callbacks/__init__.py | 5 + darts/utils/callbacks/fine_tuning.py | 237 +++++++++++++++ .../progress_bar.py} | 0 .../26-Chronos-2-finetuning-examples.ipynb | 133 +++------ 5 files changed, 331 insertions(+), 317 deletions(-) create mode 100644 darts/utils/callbacks/__init__.py create mode 100644 darts/utils/callbacks/fine_tuning.py rename darts/utils/{callbacks.py => callbacks/progress_bar.py} (100%) diff --git a/darts/models/forecasting/foundation_model.py b/darts/models/forecasting/foundation_model.py index b77d17fc49..3a24e65435 100644 --- a/darts/models/forecasting/foundation_model.py +++ b/darts/models/forecasting/foundation_model.py @@ -10,17 +10,14 @@ """ from abc import ABC -from copy import deepcopy -from functools import partial -from typing import Any, Callable +from typing import Any -import pytorch_lightning as pl -from pytorch_lightning.callbacks import Callback from torch import nn from darts.logging import get_logger, raise_log from darts.models.forecasting.pl_forecasting_module import PLForecastingModule from darts.models.forecasting.torch_forecasting_model import MixedCovariatesTorchModel +from darts.utils.callbacks.fine_tuning import LayerFreezeCallback logger = get_logger(__name__) @@ -31,6 +28,8 @@ class FoundationModel(MixedCovariatesTorchModel, ABC): def __init__( self, enable_finetuning: bool = False, + freeze_patterns: list[str] | None = None, + unfreeze_patterns: list[str] | None = None, **kwargs, ): """Foundation Forecasting Model with PyTorch Lightning backend. @@ -58,6 +57,13 @@ def __init__( enable_finetuning Whether to enable fine-tuning of the foundation model. If set to ``True``, calling :func:`fit()` will update the model weights. Default: ``False``. + freeze_patterns + A list of strings. Parameters whose names start with any of these patterns will be frozen + (``requires_grad=False``). This is only used if ``enable_finetuning=True``. Default: ``None``. + unfreeze_patterns + A list of strings. Parameters whose names start with any of these patterns will be unfrozen + (``requires_grad=True``). This is applied after ``freeze_patterns``. This is only used if + ``enable_finetuning=True``. Default: ``None``. batch_size Number of time series (input and output sequences) used in each fine-tuning pass. Default: ``32``. n_epochs @@ -164,13 +170,7 @@ def encode_year(idx): whether to show warnings raised from PyTorch Lightning. Useful to detect potential issues of your forecasting use case. Default: ``False``. """ - # initialize `TorchForecastingModel` base class - super().__init__(**self._extract_torch_model_params(**self.model_params)) - - # extract pytorch lightning module kwargs - self.pl_module_params = self._extract_pl_module_params(**self.model_params) - - # validate and set fine-tuning flag + # validate fine-tuning flag if enable_finetuning and not self._allows_finetuning: raise_log( ValueError( @@ -180,6 +180,41 @@ def encode_year(idx): logger, ) + if not enable_finetuning and (freeze_patterns or unfreeze_patterns): + logger.warning( + "`freeze_patterns` or `unfreeze_patterns` are specified, but `enable_finetuning` is False. " + "These patterns will be ignored." + ) + + if enable_finetuning and (freeze_patterns or unfreeze_patterns): + pl_trainer_kwargs = self.model_params.get("pl_trainer_kwargs") + if pl_trainer_kwargs is None: + pl_trainer_kwargs = {} + else: + pl_trainer_kwargs = dict(pl_trainer_kwargs) + + callbacks = pl_trainer_kwargs.get("callbacks") + if callbacks is None: + callbacks = [] + else: + callbacks = list(callbacks) + + callbacks.append( + LayerFreezeCallback( + freeze_patterns=freeze_patterns or [], + unfreeze_patterns=unfreeze_patterns or [], + ) + ) + pl_trainer_kwargs["callbacks"] = callbacks + # we must update model_params to be picked up by super().__init__() + self.model_params["pl_trainer_kwargs"] = pl_trainer_kwargs + + # initialize `TorchForecastingModel` base class + super().__init__(**self._extract_torch_model_params(**self.model_params)) + + # extract pytorch lightning module kwargs + self.pl_module_params = self._extract_pl_module_params(**self.model_params) + self._enable_finetuning = enable_finetuning @property @@ -225,217 +260,3 @@ class FoundationPLModule(PLForecastingModule): def __init__(self, **kwargs): super().__init__(**kwargs) self.model: nn.Module - - -class ModelTransformCallback(Callback): - def __init__( - self, - transform_fn: Callable[[nn.Module], nn.Module], - model_attribute: str = "model", - verbose: bool = False, - ): - """ - A PyTorch Lightning callback that applies a transformation function to an internal model - within a LightningModule. - - This is useful for modifying model architectures (e.g., applying PEFT or freezing layers) - just before the training starts, while ensuring the transformation is correctly handled - during checkpoint saving and loading. - - Parameters - ---------- - transform_fn - A function that takes an ``nn.Module`` and returns a transformed ``nn.Module``. - model_attribute - The attribute name of the model within the LightningModule. Default: ``"model"``. - verbose - Whether to log information about the model transformation, such as the number of - trainable parameters. Default: ``False``. - """ - super().__init__() - self.transform_fn = transform_fn - self.model_attribute = model_attribute - self.verbose = verbose - self._transformed = False - - def _get_inner_model(self, pl_module: pl.LightningModule) -> nn.Module: - """Get the inner model from the Lightning module.""" - return getattr(pl_module, self.model_attribute) - - def _set_inner_model(self, pl_module: pl.LightningModule, model: nn.Module): - """Set the inner model on the Lightning module.""" - setattr(pl_module, self.model_attribute, model) - - def setup(self, trainer: pl.Trainer, pl_module: pl.LightningModule, stage: str): - """Apply transformation before training begins (before optimizer setup).""" - if not self._transformed: - inner_model = self._get_inner_model(pl_module) - transformed_model = self.transform_fn(inner_model) - self._set_inner_model(pl_module, transformed_model) - self._transformed = True - if self.verbose: - # Log trainable parameters - trainable = sum( - p.numel() for p in pl_module.parameters() if p.requires_grad - ) - total = sum(p.numel() for p in pl_module.parameters()) - logger.info( - f"Model transformed. Trainable: {trainable:,}/{total:,} ({100 * trainable / total:.2f}%)" - ) - - def on_save_checkpoint( - self, - trainer: pl.Trainer, - pl_module: pl.LightningModule, - checkpoint: dict[str, Any], - ): - """ - Handle checkpoint saving for transformed models. - - For PEFT models, we could optionally save just the adapter weights - or mark the checkpoint as requiring transformation on load. - """ - # Mark that this checkpoint was saved with a transformed model - checkpoint["model_transform_applied"] = True - - def on_load_checkpoint( - self, - trainer: pl.Trainer, - pl_module: pl.LightningModule, - checkpoint: dict[str, Any], - ): - """ - Apply transformation before loading checkpoint weights. - - This ensures the model structure matches the saved weights. - """ - if checkpoint.get("model_transform_applied", False) and not self._transformed: - inner_model = self._get_inner_model(pl_module) - transformed_model = self.transform_fn(inner_model) - self._set_inner_model(pl_module, transformed_model) - self._transformed = True - - -class LayerFreezeCallback(ModelTransformCallback): - @classmethod - def _freeze_layers( - cls, model: nn.Module, freeze_patterns: list[str], unfreeze_patterns: list[str] - ) -> nn.Module: - for name, param in model.named_parameters(): - if any(name.startswith(layer) for layer in freeze_patterns): - param.requires_grad = False - if any(name.startswith(layer) for layer in unfreeze_patterns): - param.requires_grad = True - return model - - def __init__( - self, - freeze_patterns: list[str], - unfreeze_patterns: list[str] = None, - model_attribute: str = "model", - verbose: bool = False, - ): - """ - A callback to freeze or unfreeze specific layers of a model based on name patterns. - - Parameters - ---------- - freeze_patterns - A list of strings. Parameters whose names start with any of these patterns will be frozen - (``requires_grad=False``). - unfreeze_patterns - A list of strings. Parameters whose names start with any of these patterns will be unfrozen - (``requires_grad=True``). This is applied after ``freeze_patterns``. Default: ``None``. - model_attribute - The attribute name of the model within the LightningModule. Default: ``"model"``. - verbose - Whether to log the trainable parameter count after freezing. Default: ``False``. - """ - unfreeze_patterns = unfreeze_patterns or [] - - super().__init__( - transform_fn=partial( - self._freeze_layers, - freeze_patterns=freeze_patterns, - unfreeze_patterns=unfreeze_patterns, - ), - model_attribute=model_attribute, - verbose=verbose, - ) - - -class PeftCallback(ModelTransformCallback): - @classmethod - def _apply_peft(cls, model: nn.Module, peft_config) -> nn.Module: - try: - from peft import get_peft_model - except ImportError: - raise ImportError( - "Please install the `peft` package to use PeftCallback: `pip install peft`." - ) - peft_model = get_peft_model(model, peft_config) - return peft_model - - def __init__( - self, - peft_config=None, - model_attribute: str = "model", - verbose: bool = False, - ): - """ - A callback to apply Parameter-Efficient Fine-Tuning (PEFT) to a model using the ``peft`` library. - - It wraps the internal model with a PEFT adapter (e.g., LoRA) and manages the merging of - weights during checkpointing so that the saved state can be loaded as a standard model. - - Parameters - ---------- - peft_config - A PEFT configuration object (e.g., ``LoraConfig``) from the ``peft`` library. - model_attribute - The attribute name of the model within the LightningModule. Default: ``"model"``. - verbose - Whether to log the trainable parameter count after applying PEFT. Default: ``False``. - """ - super().__init__( - transform_fn=partial(self._apply_peft, peft_config=peft_config), - model_attribute=model_attribute, - verbose=verbose, - ) - self.peft_config = peft_config - - def on_save_checkpoint(self, trainer, pl_module, checkpoint): - # We replace the state_dict in the checkpoint with the one from the base model - # (with adapters merged), so that the model can be loaded as a regular model. - peft_model = getattr(pl_module, self.model_attribute, None) - try: - from peft import PeftModel - except ImportError: - return - - if isinstance(peft_model, PeftModel): - # Merge adapters into the base model weights - # TODO: This might be inefficient for large models, think about a better way - model_copy = deepcopy(peft_model) - setattr(pl_module, self.model_attribute, peft_model.merge_and_unload()) - try: - # Get the state dict of the base model - # This returns the weights including the merged adapters - # base_state_dict = peft_model.get_base_model().state_dict() - - # We need to prepend the model attribute name to the keys - # because the PL module expects keys to start with `model.` (or `model_attribute.`) - prefix = self.model_attribute + "." - new_state_dict = { - prefix + k: v - for k, v in getattr(pl_module, self.model_attribute) - .state_dict() - .items() - } - - # Update the checkpoint - checkpoint["state_dict"] = new_state_dict - - finally: - # Unmerge adapters to keep the current model in PEFT mode - setattr(pl_module, self.model_attribute, model_copy) diff --git a/darts/utils/callbacks/__init__.py b/darts/utils/callbacks/__init__.py new file mode 100644 index 0000000000..5e0391b415 --- /dev/null +++ b/darts/utils/callbacks/__init__.py @@ -0,0 +1,5 @@ +from darts.utils.callbacks.progress_bar import TFMProgressBar + +__all__ = [ + "TFMProgressBar", +] diff --git a/darts/utils/callbacks/fine_tuning.py b/darts/utils/callbacks/fine_tuning.py new file mode 100644 index 0000000000..8583191b94 --- /dev/null +++ b/darts/utils/callbacks/fine_tuning.py @@ -0,0 +1,237 @@ +from copy import deepcopy +from functools import partial +from typing import Any, Callable, Optional + +import pytorch_lightning as pl +from pytorch_lightning.callbacks import Callback +from torch import nn + +from darts.logging import get_logger + +logger = get_logger(__name__) + + +class ModelTransformCallback(Callback): + def __init__( + self, + transform_fn: Callable[[nn.Module], nn.Module], + model_attribute: str = "model", + verbose: Optional[bool] = None, + ): + """ + A PyTorch Lightning callback that applies a transformation function to an internal model + within a LightningModule. + + This is useful for modifying model architectures (e.g., applying PEFT or freezing layers) + just before the training starts, while ensuring the transformation is correctly handled + during checkpoint saving and loading. + + Parameters + ---------- + transform_fn + A function that takes an ``nn.Module`` and returns a transformed ``nn.Module``. + model_attribute + The attribute name of the model within the LightningModule. Default: ``"model"``. + verbose + Whether to log information about the model transformation, such as the number of + trainable parameters. If ``None``, it will be set to ``True`` if the trainer has a + progress bar callback enabled (e.g. when ``model.fit(..., verbose=True)``). + Default: ``None``. + """ + super().__init__() + self.transform_fn = transform_fn + self.model_attribute = model_attribute + self.verbose = verbose + self._transformed = False + + def _get_inner_model(self, pl_module: pl.LightningModule) -> nn.Module: + """Get the inner model from the Lightning module.""" + return getattr(pl_module, self.model_attribute) + + def _set_inner_model(self, pl_module: pl.LightningModule, model: nn.Module): + """Set the inner model on the Lightning module.""" + setattr(pl_module, self.model_attribute, model) + + def setup(self, trainer: pl.Trainer, pl_module: pl.LightningModule, stage: str): + """Apply transformation before training begins (before optimizer setup).""" + if not self._transformed: + inner_model = self._get_inner_model(pl_module) + transformed_model = self.transform_fn(inner_model) + self._set_inner_model(pl_module, transformed_model) + self._transformed = True + + verbose = self.verbose + if verbose is None: + verbose = trainer.progress_bar_callback is not None + + if verbose: + # Log trainable parameters + trainable = sum( + p.numel() for p in pl_module.parameters() if p.requires_grad + ) + total = sum(p.numel() for p in pl_module.parameters()) + logger.info( + f"Model transformed. Trainable: {trainable:,}/{total:,} ({100 * trainable / total:.2f}%)" + ) + + def on_save_checkpoint( + self, + trainer: pl.Trainer, + pl_module: pl.LightningModule, + checkpoint: dict[str, Any], + ): + """ + Handle checkpoint saving for transformed models. + + For PEFT models, we could optionally save just the adapter weights + or mark the checkpoint as requiring transformation on load. + """ + # Mark that this checkpoint was saved with a transformed model + checkpoint["model_transform_applied"] = True + + def on_load_checkpoint( + self, + trainer: pl.Trainer, + pl_module: pl.LightningModule, + checkpoint: dict[str, Any], + ): + """ + Apply transformation before loading checkpoint weights. + + This ensures the model structure matches the saved weights. + """ + if checkpoint.get("model_transform_applied", False) and not self._transformed: + inner_model = self._get_inner_model(pl_module) + transformed_model = self.transform_fn(inner_model) + self._set_inner_model(pl_module, transformed_model) + self._transformed = True + + +class LayerFreezeCallback(ModelTransformCallback): + @classmethod + def _freeze_layers( + cls, model: nn.Module, freeze_patterns: list[str], unfreeze_patterns: list[str] + ) -> nn.Module: + for name, param in model.named_parameters(): + if any(name.startswith(layer) for layer in freeze_patterns): + param.requires_grad = False + if any(name.startswith(layer) for layer in unfreeze_patterns): + param.requires_grad = True + return model + + def __init__( + self, + freeze_patterns: list[str], + unfreeze_patterns: list[str] = None, + model_attribute: str = "model", + verbose: Optional[bool] = None, + ): + """ + A callback to freeze or unfreeze specific layers of a model based on name patterns. + + Parameters + ---------- + freeze_patterns + A list of strings. Parameters whose names start with any of these patterns will be frozen + (``requires_grad=False``). + unfreeze_patterns + A list of strings. Parameters whose names start with any of these patterns will be unfrozen + (``requires_grad=True``). This is applied after ``freeze_patterns``. Default: ``None``. + model_attribute + The attribute name of the model within the LightningModule. Default: ``"model"``. + verbose + Whether to log the trainable parameter count after freezing. If ``None``, it will be + set to ``True`` if the trainer has a progress bar callback enabled + (e.g. when ``model.fit(..., verbose=True)``). Default: ``None``. + """ + unfreeze_patterns = unfreeze_patterns or [] + + super().__init__( + transform_fn=partial( + self._freeze_layers, + freeze_patterns=freeze_patterns, + unfreeze_patterns=unfreeze_patterns, + ), + model_attribute=model_attribute, + verbose=verbose, + ) + + +class PeftCallback(ModelTransformCallback): + @classmethod + def _apply_peft(cls, model: nn.Module, peft_config) -> nn.Module: + try: + from peft import get_peft_model + except ImportError: + raise ImportError( + "Please install the `peft` package to use PeftCallback: `pip install peft`." + ) + peft_model = get_peft_model(model, peft_config) + return peft_model + + def __init__( + self, + peft_config=None, + model_attribute: str = "model", + verbose: Optional[bool] = None, + ): + """ + A callback to apply Parameter-Efficient Fine-Tuning (PEFT) to a model using the ``peft`` library. + + It wraps the internal model with a PEFT adapter (e.g., LoRA) and manages the merging of + weights during checkpointing so that the saved state can be loaded as a standard model. + + Parameters + ---------- + peft_config + A PEFT configuration object (e.g., ``LoraConfig``) from the ``peft`` library. + model_attribute + The attribute name of the model within the LightningModule. Default: ``"model"``. + verbose + Whether to log the trainable parameter count after applying PEFT. If ``None``, it will be + set to ``True`` if the trainer has a progress bar callback enabled + (e.g. when ``model.fit(..., verbose=True)``). Default: ``None``. + """ + super().__init__( + transform_fn=partial(self._apply_peft, peft_config=peft_config), + model_attribute=model_attribute, + verbose=verbose, + ) + self.peft_config = peft_config + + def on_save_checkpoint(self, trainer, pl_module, checkpoint): + # We replace the state_dict in the checkpoint with the one from the base model + # (with adapters merged), so that the model can be loaded as a regular model. + super().on_save_checkpoint(trainer, pl_module, checkpoint) + peft_model = getattr(pl_module, self.model_attribute, None) + try: + from peft import PeftModel + except ImportError: + return + + if isinstance(peft_model, PeftModel): + # Merge adapters into the base model weights + # TODO: This might be inefficient for large models, think about a better way + model_copy = deepcopy(peft_model) + setattr(pl_module, self.model_attribute, peft_model.merge_and_unload()) + try: + # Get the state dict of the base model + # This returns the weights including the merged adapters + # base_state_dict = peft_model.get_base_model().state_dict() + + # We need to prepend the model attribute name to the keys + # because the PL module expects keys to start with `model.` (or `model_attribute.`) + prefix = self.model_attribute + "." + new_state_dict = { + prefix + k: v + for k, v in getattr(pl_module, self.model_attribute) + .state_dict() + .items() + } + + # Update the checkpoint + checkpoint["state_dict"] = new_state_dict + + finally: + # Unmerge adapters to keep the current model in PEFT mode + setattr(pl_module, self.model_attribute, model_copy) diff --git a/darts/utils/callbacks.py b/darts/utils/callbacks/progress_bar.py similarity index 100% rename from darts/utils/callbacks.py rename to darts/utils/callbacks/progress_bar.py diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index a413b4ad76..8c3f9d92d2 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -105,7 +105,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "426a22d045d34b1a842eec9a09e6302a", + "model_id": "8547492bdce140e5a935ba4db13a6b21", "version_major": 2, "version_minor": 0 }, @@ -119,7 +119,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 5, @@ -128,7 +128,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -149,7 +149,7 @@ " series=train_passengers,\n", ")\n", "val_passengers.plot(label=\"Ground truth\")\n", - "prediction.plot(label=\"Forecast\")" + "prediction.plot(label=\"Forecast\", title=\"Base model (not finetuned yet)\")" ] }, { @@ -173,7 +173,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f706e79ab1704fea9809dae3e7db1b78", + "model_id": "16d446f7866f4d0ca54ded638d7e66e3", "version_major": 2, "version_minor": 0 }, @@ -190,7 +190,7 @@ " input_chunk_length=24,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=50,\n", + " n_epochs=100,\n", " pl_trainer_kwargs={\"accelerator\": \"gpu\"},\n", ")\n", "full_finetuned_model.fit(train_passengers, verbose=True)\n", @@ -217,7 +217,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "467be790d94d48b09ea2ad2de1567125", + "model_id": "30691d9dda1d4f998b5ed5001809a6b5", "version_major": 2, "version_minor": 0 }, @@ -231,7 +231,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb68e0d824904fc183dc196fd93a88be", + "model_id": "9cba0f4cc07645f69c14457c61b59d40", "version_major": 2, "version_minor": 0 }, @@ -254,7 +254,7 @@ }, { "data": { - "image/png": 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2bdqE8PBwkQCrdu3aaNu2rcgkShqTy5cvi8Rdrq6uQjjJyMh4KOU5Daenpxe5HUretXDhwgLjxo4di3HjxmmzuwzDGCnU9zBMVZF4Jh4NYhNFe+vCELQfWbAGFqMdderUqVxhhEwsBPl+kHaDtB0DBw4UNVE0s2I2b95cOKtSZVcSRijlNzm5akLD9vaq2O7CTJkyRVSu1SQqKgr+/v7sWMQwJgx9yZIgwn0BU5XU6m8F3FSlhI8/AgS+GsgnvIrRSvdEWQ/J90Ou7EpotjWh8XJyV6pGS46uMmTqiYiIUKrUFoZ8UMgEpPmj7ZKqh3+mcQ5ICzdo0CA4OTkJs19ZlyOtHdX1OX/+fKXvEzlc0zNgaWmJn3/+uUzL9O3bF6+//royTPd8act+9tln8Pb2FsdBGshnnnkGo0aN0vk1qeqffLylzSc6rirel8LXrbTf8uXLtbpP+Vf952B+74tY9WYkEmPySp2360R1anjzc3F8vcwrdu4rXRghDQdpOiiShnw6KEX7rl27RLju0aNHkZCQIOajQm9ksqHQXznKJisrC//++69YjpxgqRpsUf4ipsLkyZOFwFb4pym0GRpUuM/FxaVS1vXDDz+I8G+q4EsF+oo7h+QUXR0kJycL7d8777wjHK8pPL0qIMduqsNDtYbo+Cn6jGoQ0bmtTD755BO0bt26UtfJMPrKiU1JqHMpGq7LLmNNn+BS5w9oaotoJ5Vzq3dCMmLuFPRhZCofrb1yqDNOTEwUBd6ooutzzz0nSr9TmXny6ejevTvef/99UXKevmxlTce3336LVatWoU+fPqJAXGmF4EyBRx55RLxwNH9lsa0VRWGHX0Pn1q1bQoglU2DNmjV1vTtC40JO1JRfh7QWxZkYK+O4iREjRgj/KzKNOjs7V5qQxzCmyNWF6nBepyHeZVomp4Wb8pI8vIIL51U5koEQEhIi5eXlScbCpEmTpBEjRhQ7ff/+/VKHDh0ka2trycvLS3rnnXeknJwcZXqvXr2kF154QXrllVckd3d3qXfv3mL8hQsXpEceeURycHCQatasKT355JPS/fv3leXoHM6ePVuqV6+eWLe/v7/0+eefK9PffvttqUGDBpKdnZ1Up04d6X//+5+UnZ2tTD979qzYlqOjo+Tk5CS1bdtWOnXqlLRv3z6yyRX4ffzxx8Ue37x586S6detKVlZWUsOGDaXly5cr0wIDAwush85VYWjdhbdH+xAaGira69evF/tJx9GyZUvp6NGjBZY/dOiQ1L17d8nW1lby8/OTXnrpJSk1NbXIfV26dOlD26LtFHUN6XrQtdG8TjRO89h++OGHIrdT1DERhbdD66T9feuttyRXV1epVq1aD53rhIQEaerUqZKHh4e4Tn369BHXrrjjoXHyuQsODi6wHvncEvJ13r17t9SuXTtxfrt06SJdvXq1wPb/+ecfqU2bNpKNjY24jz755JMC9+/169elHj16iOlNmjSR/vvvP7HejRs3FnluNO/5yZMnSy4uLuL+/v3338V1o3F0T9J9vW3bNq2eJVr+qaeeEs8MTf/uu+8eum6ZmZnSG2+8Ifn4+Ej29vZSx44dlXMin1NnZ+di953RHTmpOdLOwN3SVrcd0r+1dklxd9X9WUlsnxcjlqHf3D4Xqnw/TR2OV9JDyAwwZMgQdOjQAefOncP8+fOFaezzzz9/KBMuaZ3Igfi3334TGiuydZOm6vTp09ixYwfu3btXIArpvffew9dffy2SzlHUE4VoU/I6GfLRIJMATSPzAEU1kclEhhyLKSz71KlTIn/Mu+++K/x5unbtih9//BE1atRQtDwUUVUUGzduFFq1N954AxcvXsSzzz4rnJbJ4ZmgdZPWiPab1kP7URhaN03X1C7RPsh88MEHYh4y8zRs2BCPP/44cnNzFe0DLTd69GjhW0ImxcOHDxdwwtaEwtQpnJ04efKk2BY5UFY2tL8USUbIx1QcdO0pIo00kt98843wMyGTqWb0GfndbN++XVwninYjE2t8fLw4Hjr3zZo1U7ZD47SBzu+cOXPEfUY+NOTXInPo0CGhGaVrTPcRmZzonvriiy8UJ1TygaF7l/af7l3SuJYF2Tfj+PHjeOmll0Q0Hx0rXfugoCDhUE/pBuRIvbI8S2+99RYOHDggzMj//fcf9u/fL9alCd0blOxx9erV4p6hbdI9dOPGDa3OG1P93N10D7kpqme/9jgvuNUqW2RMtwmuyHngE+l0LY7DyasayUg1I3NW50u+o/Iq/NsXlF9gvTQsT6NtlBf62rWwsBBfY/JvzJgxYtr7778vNWrUSMrPV69/7ty54stPPgf05UZfnprMmjVLGjhwYIFx4eHh4ovz2rVrUnJysvgSXbhwYZn389tvvxVfwDL0lf3HH38UOW9Zvw67du0qTZ8+vcC4sWPHSkOGDFGGSRNQlEZEk6I0E/LX/aJFi5Rxly5dEuOuXLkihkljMGPGjIc0Jebm5lJGRkaR2yJtgawRKWn7FdGMEKQZKPxYFqUZIa2OJvTlT1/88rHUqFFDfM1rQlqDBQsWiDZpUlq1alVguraaEZmtW7eKcfK569evn/Tll18WWPeKFSskb29v0d65c6dkaWkpRUZGKtO3b99eJs0IHbfcF+Tm5ornhrQaMtHR0WI9x44dK9OzlJKSIjQma9asUabHxcUJjY983cLCwsSzqrm/8nG+9957os2aEf3l6ODjioYj/mSCVsvOb3pSWfbioZQq20dGkoy2UF5ymoTI+xVfT1bOw8PyemkbQNHRRGWB/GfoS01GzsVCToxdunQpEKlETsKU44WikAICAsQ48qnQhL78SLtA0UeFIW0AaU7IkZi+kIuDtAQU7UHz0/ZIm0DaDhmKMJg2bRpWrFgh/IboC7FevXpaHTcdX2EHUDq+ojQg5aVly5ZKm3w8CNIUNG7cWJwn+rpduXKlMg9FftEXOzllk3O1vqN5fPIx0vERdHx07dzd1eXQCcr3I/ukVNX5pXuTtk/aOlkTImdvpig60ljQ9SfNko+PjzKd7vey0KJFC6VN0Td0jJrjZC2ffC5Ke5bI6Z78raiulgxpXho1aqQMUzJH2n/SsGlCz1Lhc8zoF/EXU5BwQpUvxLGxI1zaO2u1vFUHd2BzvGif3pKMZqVkbGXKj9EKIzUczODrqQotrgg2Vg8P+3qqt1ERSPioX79+hZbXhDrYYcOGYfbs2Q/NSy8MynhbEqSGJjMMRXOQ8zE5TpJamtTxmlEYVBxx69atwgTw8ccfi3nkLLz6glwviZBfRHK2RTpPZBp6+eWXH1pOFvTKAoWsyeHrMuTkWt3HJx+j5vHR9SZzQ2FKcoSVQ/A0j6m44ynt/NI9RKaYwlB+oso+7pL2pTKg4yHBh8xd9F+TogR/Rn/4+71IyBlCao73LTYVRXG0nFQLbwbb4qyDG/qYW2NSlewlY9TCyOvjzcSvsundxgwR6yt/vZrQl/n69evFS0F+eOhLk/w5yF+jOMgvgJajjLhkxy8MRaZQePaePXuEdqMwFJ5NeTTIH0AmLCzsofnoC5F+r732mvDFID8HEkbIB4C+IMtyfHQ8kyapH20abtq0KbShrNsr6jyRL0NFBEHC09NT+LxoQj4qhV+Y1Q0dH1XMpnuA7oWynjs6HoJ8SMjvSD6e8mz/2rVrxZ5fuv6UuIy2I2tVyAdEF88SaUHoepHviiyIkraEwsl79eolhulc0LkibQtVI2cMA6or43oySrTJ98NleNmiaDRp18seVwLtkJwI7AsGcnMlWFpWbf9vqrADqx4yc+ZM0VmTgx7lbCHHOtJAyEmYiuOFF14QDookIJATKKnkd+7cKZxDqTOlr1JyFKQKyuQISNPpJUAOfbKwQiGspOmgaWSuIWdTTTU/OfLRFzcJKdSp03Zkswa9+OgrkoSd2NjYYtP9k8MgOTSSiYocAL///nts2LChWIfX4qDtkbmFXny0vbJqJegckOBFx0IvW9oHOsfFObAWBzkLkwMnnUtaB12jwsKJLiDzGZkmKAcLOWTevn1bHC8JmbS/8rkjkxQdP507MjmQoNq5c2fh4EzmDXLqpKKY2vLRRx+Jc0LakUuXLol10T0lr4v2j4RZEkbJpEMOr5oCcHU+S6TZoMKddE/u3btXXD/KX6P5nNG+ksaQnHLpPqXzRo7MX331ldAQMvrJ1hVJcHjgtB7RoCa8aqsyiGuDubkZ+j2whienASevVPZeMjIsjOghlAxu27ZtosNr1aqVyOVCHWZpLwaywZOAQIIHRRWQLf3VV18Vqnm5c6UoGoqkoBcGCREURSHb14cPHy60HfRSpoRY9AKj+WVIRR0XFyc6ZeqgKZqFknLRS4egiAbaV1onfWVTlEdR0EuS/EO+++47EdFB0RakXendu7dW54nKEpBtv3379mJ7dOxl9XegFy19/dKXLn350vnQ9GEoC2TKovNDwh1Fa6SkpIhzo2tIA0D3DyUdJEGUrhWVZyABUvapoEgiigYhvyU6d5QDiKCEhOQnRP5IdO8UjuAq63nZsmWLEITovJCAQxFZpHUj6F4kIZeE244dOwotnaZ/SXU/S5QDie4DMnGSoES5kgr7Y9H9SdeWnh265+geJkFcG7MeU738ftMFkxr2wNKa9dHo+fKncx/YQa0J+e9UxU3/TNGYkRcvDAD6GqHOrKypZRmGMT7IF4SEKu4LmJIIjZJQd8KDciQ+wI2/zISWozyE38vHhEH30CY1DoFOuXgrmDMXVwVG6zPCMAzDmCZLtqm/sac9Wn5BhPCvZY5p8bdQKy0NeQlmiIvKhruPdSXtKSPDagaGYRjGaMjJysfyrapoKgp+mvxIxdeZ2UyVGt4CEg6vVNVgYyoXFkYYhmEYo2Hn/Fh8feQgpt69jsebZcDbo+LRLw2Hq6v4BkRxnZqqgIURhmEYxmi4syICznk5GBUXhvH10yplnb2ecoOZlUqoSTrMwkhVwMIIwzAMYxTcuZwJ/9uxop1gbYOBz1VOhlxLR0u4dlAlDEwPSUd6WNFpC5jyw8IIwzAMYxTsmh0p/DqItO4+sLYtmDG3Inj0Vgs2sftZO1LZsDDCMAzDGDx5ufmw3BOpDPd6y7dS168pjBz/k4WRyoaFEYZhGMbg2ftHPDwzMkQ7zNsNjToWrN1VUZxa1kCqxYNsGOfikJtdefWPGBZGGIZhGCPg+mK1VqTWhOJreJUXCytz3K+tCvF1zMvFiU3Jlb4NU4Y1I4xeQoXeBgwYICoTl1RptjBUh4XSoZenwFtJULViSpFf1VTGdspyDqhuEKWEr1Gjhpg3MTFR6/VSjaLSli3qOtIy//zzD4wZqr2kzX1blZTnmaDSDFQOwFC4ezsLfjfuiXaypRUGv1KzSrYTMN4HEX3rwO6H9mg32KlKtmGqsDCiI6gYF3UQhX83b96EoVKZHTDVMqGqrtSBUg2Z4s4h1QhhtGfZsmWiQB3VH6Lz7OzsXCWnsajrSMNU06gyocJ/P/74Y6WukzEcdn4dDasHlU0SOnjDzqnyHFc1GfZGLcxY2xB9nnaHrUPVbMNU4XTwOoQKlVEBrqLKuGtLdna2KAtvLFDVYCpWRpWEmao5v1QosXnz5tV+Hb28vKp0m4wJYmGGJCtrOOdko+sblW+iYaoe1ozoEBsbG9Exa/6oMi5BVWWpoinN4+3tjXfffVdUU9VUo1J1XVKlenh4iEqpBJVAp69OKo1OFVqfeuopUSJes9AYVdOtX7++WDdVHdWsmPrOO++IKq/29vaoW7euqEqbk5OjTKeS71Tp1cnJSaj46UVDZelJZU8VYpOSkhQtD5kcimP+/PmoV6+eEKCoCuqKFSsKfOWuX79elKGn9ZAGpDC0bvq6p5Lw8vZoH2RCQkLEftJxULXWY8eOFVj+8OHDolKrnZ0d/P398fLLLyMtrewJkug8fvbZZ/Dz8xPnkUwrO3bsKDBPaeeS+Prrr8V1ovNJ1WQzMzMf2taiRYuE4GBra4vGjRtj3rx5BaZTRVqqPEzTqYJxcHBwiftO986cOXNw8OBBcd7kaslFmU9I00Uar/JQ3HXU3I5sQtiwYUOZrheZe7p164ZXXnlFuV60/1Q8jypOy/dCcSYv0p7QfhXWrlEFaXrO3N3d8cILLxS4TllZWXjzzTdFBWDafqdOnQrcawSdI3qWaP9HjhwpqluXhHzca9asUe5DqnBM2iOqBkzXkZ5hepbv37+v1X1XlvuhtH7C0Jg0NxCjQnvCanY7tOrD5hODRDIQQkJCpLy8PMlYmDRpkjRixIgip0VEREj29vbSzJkzpStXrkgbN26UPDw8pI8//liZp1evXpKjo6P01ltvSVevXhW/hIQEydPTU3rvvffEckFBQdKAAQOkPn36KMu9/fbbkqurq/THH39IN2/elA4dOiQtXLhQmT5r1izpyJEjUmhoqLRp0yapVq1a0uzZs5XpzZo1k5588kmx/uvXr0tr1qyRzp49K2VlZUk//vijVKNGDSk6Olr8UlJSijy+DRs2SFZWVtLcuXOla9euSXPmzJEsLCykvXv3iukxMTHSI488Io0bN06sJzEx8aF10LppOs0nb4/2gfabbuvGjRtLW7ZsEesfM2aMFBgYKOXk5Ihl6bgdHBykH374QRwDHW+bNm2kyZMnF3u96Ny3atVKGf7+++/Fsa5atUqcezqvdEy0vrKey7///luysbGRFi1aJNbxwQcfSE5OTgW28+eff0re3t7S+vXrxTNA/93c3MT1k88DXfMnnnhCunjxorR582apbt264hwEBwcXeSxxcXHS9OnTpS5duojzRsMELUP3mibOzs7S0qVLRVs+t/J69+3bJ4bpviuK4q6j5na0vV50ntauXVvgetH++/n5SZ999plyLxR1zQhaB61b8zmk6/jcc8+Je5rOHz17v//+uzLPtGnTpK5du0oHDx4U+/Ltt9+K6yZf6+PHj0vm5ubi2tL+//TTT5KLi4s4d8Whedw7duyQLl++LHXu3Flq166d1Lt3b+nw4cPi+a1fv77Yt7Led2W5H8rST1D/8sorr0j6CD0Hms9ZdUPvoXP7UqQ/ng+V/nz9js72w9gwWmHk1txQaU+zfaX+Tj1x5qFlaVxZlqVtlBfqBOkFTJ2s/KNOmHj//felRo0aSfn5+cr89OIm4UM+B9RZUIesCb38Bg4cWGBceHi46Iiok0xOThadqKbwURrU8VIHKUMvS/lFWBh6aZXUActQx04vQ03Gjh0rDRkyRBkmQY3OkbYCndzJ0wte5tKlS2IcdbzE1KlTpRkzZhRYjoQyeqFkZGQUua3CLzYfHx/piy++KDBPhw4dhABZ1nNJwkDh+Tt16lRgO/Xq1ZP++uuvh64zLUssWLBAcnd3L7Df8+fPL1EYIehFQ/eQJpUtjBR3HYsSRsp6vej+p77gwIEDBa4XCRgkaGhSVmGEhnNzcwvci+PHjxftsLAw8ZxGRkYWWE+/fv3Ey5x4/PHHC9y7BC1fFmFE87hJwKBxe/bsUcZ99dVXoi8o631XlvuhtH5Cn4WRCxcuiOtB+/rOO+8oAmt1EhuZJW1y2yltddshLfE/VO3bN1aM1mckNyUXmdFZpc5n65v90Ljs2OwyLUvbqAikliZzhQypgIkrV66gS5cuirqZINV0amoqIiIihDqYIBOJJmRC2bdvn1C9FmW7p6gHUjn369ev2H36+++/8fPPP4v5aXtkGiJzjMzrr7+OadOmCbNK//79MXbsWGFu0QY6vhkzZhQYR8f3008/obJo2bKl0ib1OxETEyPMHHSezp8/j5UrVyrz0DuSVOChoaHCJFISycnJiIqKEvtc+Bho3WU9l3QennvuuQLroOtO15AgMwQtS+ab6dOnK/PQemSHU1oHHSup5DXXYWhoc71U8gzKfL1Ko1mzZop5VN7+hQsXRJv+5+XlCXObJvQckUlHvgZkmtGErkFh80lpx03mEqJFixYFxtF5KOt9V5b7obR+ovCx6hNk1qLrQcyePRsX9+Xhs+9eRdselZvgrCTcfawR5V4D/nFJqEXP6NkM1GttV23bN1aMVhixdLKErbdNqfNZe1gXOa4sy9I2KgIJH+S7UZHlNaEX3rBhw8RDWhjqYMmPoiTITj9x4kR8+umnwgeFXnirV68W/gUyZId/4oknsHXrVmzfvh0ff/yxmKdwZ6xrrKyslLYs1NHLSz5Pzz77rPATKYws6FWUspzL0qD9JBYuXCj8FDTRfHlWFnSe5Be9TGEfF11fLxoXGRkp/DfMzc1LvF40vSzHo7ltefua26ZzfebMmYfOeVEv88o47sLj5H2pLErrJ/QZigDTpN+dgYh87BIOeodjyr52cPYseC2rCvO27sCuJNE++Vcc6rVmp9mKYrTCSN2ZtcWvPLRf2Ra6hL70yPGPOlK5gzpy5IhwciTHteJo27atWI4c9CwtH760FNFAjnJ79uwR2o3CUJhnYGAgPvjgA2UcOQYWhr6c6EcOg48//riICCJhhJxR5a+W0o6PjmfSpEnKOBpu2rQptKGs2yvqPF2+fLncgiBpN3x8fMQ+9+rVSxlPw+R0XNZzSefhxIkTePrpp5Vxx48fL/BVTNshIZIEm6KgdZCWihxf5a9hzXVoA0VyUditzI0bN0Q+El2jeb3oxUwvazq3JGyUdC/Q8VCeE83nSNv8M+QISusl7QQ5mhaFfB01Ke81qOh9V5b7obR+Ql+hiEH5WOja+tn2RaM0laBmEZeGJSvm4tXXXimgUa4qGg53R9ou1cdd/CFy/GVhpKJwNI0eMnPmTISHh+Oll17C1atXRcQIaSDIRKLZAReGogDi4+OFgEAe+aRy3blzp4hyoQ6VOieK8Hj77bdFhANNp4d78eLFirBy584d8QVP08jEsHHjRmX9GRkZIoKHIgnoxUqdIG1HVpNT50ZfXSTskGd+cS+yt956S0QfkImKXnjff/+9iKagiAVtoO2R+v7atWtie2X9iqdzQMICHQu9nGgf6BzTcFmhY6AvSzLF0PYp2onWRVEeZTmXBM27ZMkSIcxRFAVd40uXLhWYhzQrX331lVie5iGzAc1P54wgLRV1vmTGoRf2tm3bRGRIeejbty9+/fVXEX1BEVJkQiqsNdAFha8XmWYKXy+6Fyg6iLQmclQIRdlQJApFj9E1mDt3rtDmaQMJ3SQIksBI9yhtm6JV6JqQdpAgjQ2ZZOi8071E57AsJpryUNp9V5b7obR+Ql8h7ZQcbUbaxh8Hv61M25l/Bq+/8RrGjx+PlJSUKt+XziOdkf4gNbx7SLyoi8NUEMlAMKVoGmL//v3CMc3a2lry8vJ6yFmrOAcz8jIfOXKk8Oa3s7MT3vqvvvqq4gxL5/Dzzz8XTnvkhR8QECB9+eWXyvIUnUMOcOQsS0545PAnO+JRtMqECRMkf39/sV/kTPfiiy8WcJYjz39anm4tzeifwsybN094+dM+NGzYUFq+fHmB6WVxYKVoDYoCoH2l7ZFDZWEnS4IcLOXpMidPnlSWJefhli1bPuQYWJIzJJ3HTz75RPL19RXHQNO2b99eYJmSzqUMbZMipWgeOl6KjijsdLly5UqpdevW4pxTJFTPnj1FRJLMsWPHxDI0neajiJvyOLCSkyY5NtL5aNCggbRt27Zqc2DV5npRtEvh60XngMaRg7Zmt0bOm3S/0jE9/fTTYpnCDqyFn8PC5yY7O1v66KOPpNq1a4trTdFN9IydP39emWfx4sUiooeeuWHDhknfffddmRxYNY+7qPNZ2Cm8LPddWe6H0voJfXRg/eabb8Rx0G/Br79LO+vsFk6kmzy3Sg7mrso0cvglJ+iqZm7bM2L79Dv+78MRf4x2mNEfGAD0RVJYNcswjGlBZhrSynFfYHoMHz4cmzdvFu2TP57C/c9UuVx8x/sgdOAtYfYlJ1/Zn458rUj7U1UsfykMHn9dFe3oYQ0w9Y+6VbYtU4Df7AzDMIzeC6GU+I6gKKa83WqziP9TfiJxHZlx5OgkikQjkxWZ0MjXpCpoN14VTUVknyo5yR1TOiyMMAzDMHoN+b8kJCSIdu/WkxF/VNV2qO8A186qeljk4ExRbJoO4b/88otw9qWUCJVNk672iH3gJOxzLwEpCRVL9WDqsDDCMAzDGExIb7OUR5V2fBffAtEzlI6fnOMXLFig1OoiJ32KiiLH+sqEXAYSWtbCUSdPLPRqhCPnDcLjQW9hYYRhGIYxCGHEwswGjcJUJpocMzN0fPHhvCgknFBSRYr2I98igiKsBg4cKOpwVWbeFp+3G+GLgNbY6uaP3Re5im9FYGGEYRiG0VsoxkIWRmxrDsUyzwa4aueMiLqe8K2vzjRbGCoSSH4kVB2dICHkf//7n3CElU0+FaVvWxJ+VO3/TlXKKk0WFkYYhmEYvYWip2Sfj5qNh+M/V1+8Ubcjas5Sp80vDnJ2pXwwlK9HNufQMJXSCAoKqvC+uTuboX0jVftCCHA3jk015YWFEYZhGMYg/EVs3Dso7TbNLMrs2/HRRx+JhHdubm5KqoiuXbsqCR8rwoAOgGV+PlqmxmPfOlVoMaM9LIwwDMMweosc0ksk5ap8QBzsgLo+2q2HsraSNqRDhw5KsUMqi0GFKCm7dHnp75aKv6/uw1dhZxC/4uHyGUzZYGGEYRiG0VsUfxGbmjC/mw9zSUKLuqTx0L4GDTm00vqef/55ZRyVZCAtSWmFRIujyyAHxXHE9WZcpRc2NBVYGGEYhmH0EoqCuXLlimj3aTwZv988irVX9mL03dByr9PGxgbz5s0T9bmocChB9X3Ij6Q84b+2jha46+Mq2i452YgJVlXbZrSDhRGGYRhG7000TZy7iv+2Uj5q+lW82vBTTz0lqi1TUUsiMTFRjCuPZqP3M+psrOkn4iu8b6YICyMMwzCM3juv1syspbQDOjtVyvpbtGghKhfLfiTR0dGiGrK2+A/yUNqx+1RVoxntYGGEYRiG0XthxFkUc1bRoo9jpW3D2dkZo0aNUoZPnjyp9TocGznA1ttGtOOPJSAvM6/S9s9UKJcwsmzZMgwdOhQ9e/YUxYioKBFBaXj79++Pvn374qeffhLJamQuXbqECRMmoFu3biI7HkmgDMMwDFMUqampSi6Qpk2awzNB9Z6hejDuPqpU75VFx44dKySMUA4T994qU01+Rj5u76mcpGqmhNbCyJo1a0QxIorPPnDggEgmY2VlJWx7a9euFQIJzXP06FH8+++/Yhmqmvj2228LYWTv3r1o1aoVPvzww6o4HoZhGMYIoJoyeXkqDUO3FuNgl69qp9aqHBONJuS8KidFK48wQmQ1U/uN7FrEVXyrVBihG4PCoCilrpeXl7h45PxDBYm2bduGkSNHws/PDx4eHnjyySfFOIJS8pLAQmWeyZOZ4rrJQzoyMlLrHWYYhmFMy0RT266b0rasX3kmGk1TTePGjUX73LlzyMzM1HodvgNUCdUIi/MsjGiLVi7JMTEx4iLt3r0bf/31FxwdHYX3MQkhlNGOksrIUDnnW7duiTbFb8sey4Stra0QWmi8r6/vQ9shTQr9NMnJyeH4bYYxceRIB87lYFqRNE5JngCiRNu9lVOVXH9yYqWPZHrXBAcHo1OnTlot713XGtudnWCZk4ec+i7Iyc6DhaX2uVCMEcqCW+nCCNnx7ty5g02bNiE8PFwkj6lduzbS09Ph4OCgzEttOasd/decJk+nZYpi6dKlWLhwYYFxY8eOxbhx47TZXYZhjBTqexjjhQQCcgcgfHx8IN1WaypqNEoT9Woqm3r16intnTt3Cu2/tnRY44Ua7ioBJCLyTqXunyFTp06dyhVGyMRCTJ8+XWg3SNtBZZmpVLO9vb3iyEpQW04oQ/81p8nTaZmimDJlCiZOnFhgXFRUFPz9/cskYTEMY5zQFzEJItwXGDeU/0P+mO3duzfsjueIdqa5Ofo/WgeW1pWvcaDqvh9//LFo37x5U2Rr1ZpyLMKUQxihi0O+H7KjDyG3SfKhC9irVy8xTCYaWdKsW7cu1q1bpyxDph6qwkjji4J8UOinCW2XBBEWRhiG4b7AuKEPXJkePXpg6orOCD2fhTsXMmBtW7YCedrSunVr8d4hFwHKPcLvmupFKzUDaTj69esnImnogpGfyK5du0S47pAhQ7BhwwYhZMTFxWHlypVinOypTEWJKLqGliMn2CZNmhTpL8IwDMOYNprOqySMkGBQr7Ud+jyldhKtbEgQadOmjWhfv34dCQkVC88Nv5qJ+xEFfR+Z4tHa5vHOO++ItLmUT+SVV17Bc889Jy5g9+7dMWbMGEyaNEn879y5M0aMGKFc5G+//RarVq1Cnz59hHPQrFmztN00wzAMYwKmONl51c3NTXy4Vhea+UZIO1Ie9i6Lw+I6R3Ch2wFs+1LldMuUjtYJ/p2cnIRgUZyvB/2KolmzZli9erW2m2MYhmFMCIpoiY9X1Xehj9zqNJdQBM0vv/yi5Bshn0htqeFpBe9kVbG8tGMU4lu70vfTGKl4tSGGYRiGqSITzfyhVwAzwK1VDYyd5V2lwklFM7ESbQY6Yo2VNZxzsuEVkYDMtDzYOlSNn4sxwaEpDMMwjF4KI926dofnyUgEHruD7KU3q1xLQvmxXFxcFGFEs6RJWbGwNEd8PZVvi21+Ho6tT6z0/TRGWBhhGIZh9E4YodQPLuZNYf8gDXxKrcrPvFoYig6VtSP37t0rdz4bj97qKr7XN3E21rLAwgjDMAyjF1BCTVkAoCAIt3h1srOGPSu/Jk1VmWo6P6GO+jE7y8JIWWBhhGEYhtFLf5HkS8nKcLM+NQxGGAlsZodoJ5UmxzshGTF3OMS3NFgYYRiGYfROGKFImpRLqqgUwqlZ9WhGqEZNRYURIru5SjtCrqtHVrJ2pDRYGGEYhmH0ShixsLAQZprkyyli2NzWHA51iy4fUtlQTZqAgADRPn36tKhWXx4CH3FX2tEHK5ZAzRRgYYRhGIbROZS5+/Lly6Ldtm1b5GfZIO2WqpiqZR1HmFlUXwVc2VRDNdQo70l5aDPEWfwnUSb1fm6l7p8xwsIIwzAMo3PkrKuyv8j5vamUXkRw3bLqI2kq22/Eu64NPmvbCWOa9MVXNZuXK0zYlGBhhGEYhtE759Ww42p/Ecem1eMvUpnCCOHWugayzS2QmAqEx1TSzhkpLIwwDMMweue8etncEWs9auO0ozv8uqtMHtUFFXeVE6xVRBhpVV/dPn+rMvbMeOF08AzDMIxOId+MoKAg0abCeB4eHjiUkY9DtVRCSPyw6vMXIRwdHdG0aVNcvHgR58+fR0ZGhqhary0t69F+q8wz524Cj3atgp01ElgzwjAMw+iUEydOIDc3VzHRkH/F+RDVNP+agKtT9QojmqYaiqahSvPloYVvHsbcD8WbERdgufxaJe+hccHCCMMwDKNX/iJ37gFJD1xGWtbTzT5Vht9IwzpmmHg/BH2S7qLW9fuVuHfGBwsjDMMwjF75i5w/lQWv7HSYSZJBCyPWtha47+wg2h5p6UhJ4BDf4mBhhGEYhtEZOTk5OHbsmGj7+fkhMDAQ9/6OxOIbR7Dm6j60TYvXyX41b94ctra2FXZidWnupLxsM66rI4SYgrAwwjAMw+gM8sdIT09XTDRUOTfrhirzKlXsbdDaRif7ZWVlJZKvEbdu3RJJ2cpD+yHqmjqZ11THxTwMCyMMwzCM3viLEA5Rqpd2tpk5mnSpnjTwpZlqTp06Va511GiqTtimWWuHKQgLIwzDMIzeCCPkV+HxQFNC/hbkd6ErKsNvxOmBmYZIvsSakeJgYYRhGIbRCfn5+UoaeFdXV5Hb48LeVOXFlO1XvZlXC9OpU6cC4cflwdrVGjbeKlNT3LkUcczMw7Awwpgkdy5nYtHTt7hjYBgdcvXqVcUXg6JoKOvp7WNq7YFjE90KI3Xq1IG7u7uiGSlvfZnrlg+cWNNzcetsZqXuo7HAwghjchzdkIhD/Y7DZ+tNLJsepuvdYRiTpXBxPCJJw5Th21G3wgg508qmmtjYWNy+fbtc6zGvp/YbubqPTTVFwcIIY1JEro1CwsxTcM3OEsMWO+5w7D/D6El+EcLstvpl3bxv9VbrrSq/kdoD3RHazAcxYxqhQXfdH5M+wrVpGJNAypNwbdZ1hPxyWylLHu7pgqGbWsHJlR8DhtGlMEJ1X6g4HflTuMepIk4SrG3gVVs3Yb0lCSPjx4/Xeh2DnvUQP6Z4WDPCGD3JMdk4/USQEERk/J72w6Qz7WFjb45/v7mL+YMv4+qJNJ3uJ8OYEuHh4QgLC1McRa2trREdkg3zB34ZSTX1Q4PQoUMHpV2R5GdMyfAnIWPUnD+QiqAng1HzQaigmaUZmn7ZGAHP+At78MqZYfDecgOBAE6vdkTjTqrUzQzDVH9+Ed/6tngsui9uBmXAJ1U/ok48PT2FI2toaCjOnDkjCvpZWvKrs7JhzQhjtGxbkoDrY0+oBZEaVui4vj0CpwYIQYRo9KirMn/SUd2knWYYU6QoYYSwsDRHo44OaN1Xt86rRZlqMjIycOnSpXKvJyEmBwdXJSD8KkfUFIaFEcbooPC72SsljF9ijwQLKzEu2skRdf/uBPfubgXm7TisBtLNVUmV3MISONSXYapZGLGwsECXLl30+rxXhhPrqrcjcKzJXqS+eBIHf+cKvoVhYYQxKjKyJDw5S8K7CySkmlthVkBr3GjojTGnOoqvrcJQdscYX5V2xDknG+f2st8Iw1Q1lFtE1jC0adMGjo764R9SlcJIrWZ2SjvpYnKl7JcxwcIIYzSEnM/A4GmZ+Gu3ety0553w0pEWcPZUaUiKwq69WltyfiObahimqjly5MhDJprUxFzMa3Uavz12DTvm65fmgAQm0uBURBhp0U9tdrK4wzVqCsPCCGMUkB32xMDjeHTfOVjm58PBDtjwuRk+mmwGc3M5mLdomo1QCyNpJ1gYYRhdJDu7sC8VtSPiEHDoNm6titari+Dg4IDmzZuL9sWLF5GWpr0G1dPPGvE2tqLtHp/KJuFCsDDCGDx/vRWOhJdOCTNL04wkzMy4hWPzzDCyZ8lCiEy7wU5ItVB5x7uHJyAvVz+8+BnGFJxXu3XrJv7fOaHWFjg0qQF9NdVQLpSgoKByrSO5lsocZZ+XixunMyp1/wwdFkYYgyUrI0/kB3FZchlWD3IThHm54b31tdGiXtkEEdl7PzZApR1xys3BmR2crplhqor09HScPn1atBs1aoSaNWuKdnMz9XPXfpCjUfqNWNRTm2quHmRTjSYsjDAGyd3bWVjSPgiBJ8OVcWEd/fHM6bblytro0Eltqrm0iU01DFNVUPVbytVROKQ35bJaGGnQU381IxURRjzaqIWRmCD+6NGEhRHG4Aj6Lxn/dT+BwLsqoSHHzAyJzzTF89ubwsZO5WSmLS0ec8NVO2es8aiNg/nq3CMMw1R9fhEKx0+5pNIU2NSygY2Htd6d9qZNm8Le3r5CwkjDHmphJPs6CyOasDDCGBT/fnsPoRNPwiNDZW9NsrKG6y8d8MS3/lqv69q1a3j77bexcuVKtOnviK/bdsSyWg2wPqIGcnPLVyqcYRjthZHMqCzkJOSIdo3m+pPsTBPKukr1cwiq3hsTE6P1Opp0tkeWmeq163CPhRFNWBhhDIrIPXGwy89TtV2c0HFHZ/R8XDtNRkREBGbMmIFmzZrh22+/xVNPPYVbt26hTxvV9JR0IOh6Vew9w5g2ZJ45duyYaPv6+qJ27dqifXqHOu+GVFv//EWKMtWcOnVK6+Utrc1x30V1fNm5ZkhOVPVlDAsjjIExdWMj3KnlitBGXnj8TEfUa61OJFQa8fHxQhPSoEEDLFy4EHl5eYqK+ODBg+jTVu30ui+4SnafYUya4OBgJSyWtCJyWYbrGs6cYXb6qRmpLL+RS+NaYnTjPni2QTdcimB9gAyfCcagIJ+QJw61wfOHW8DRpWzFqqjz+/LLL1G3bl2hCcnMVNWFoCqhMsePH0fftkIygU9WGkI3aa+CZRimfPVoMq+rNSP1ujkatTDSoJ09Mh+kEjh3q9J2zeBhYYQxOGq4W8HcvPRbNycnB/Pnz0f9+vXxwQcfICkpSYy3sbHBm2++iRs3bihZFcnDv4Ef8Ev4SSy8eRQD915AZhqrUBmmqpOdEfucvLHBPRBBTu5o1kN/K2cHBgYqocgkjJBWVVta1Ve3z91k3zQZFkYYvWfvsjhs/Coa5/alIDuzdAGBkhKtWrUKTZo0wcyZM3H37l0xngSYadOm4ebNm0JDEhAQ8FBWRXNflbe8bX4eTvyrEl4Yhqk49OKWhREXFxfhs0VkZknYmO2JxV4Nsb5f23JHxFUHZFaStSNk9g0JCdF6HS3qqtvnWTOiwMIIo/dcmXsHNt+dR+SYo7heQtZC6uy2b9+Otm3b4oknnhBOqTJjxowRhbnIV8TPz08Z36lTJ0WAOXPmDFy7uSvTsoMSquyYGMbUoOi1+/fvK1lXZe3mpdv0/KnmaanxojYEUw1pVLXFxckM4/Oj8FrERYzZcpIzPpdXGKEohK5duwoVG/1efvllMX7z5s2iY5fH00/+IiXoRTBhwgRxE9I6oqP1q/YAo7/Y31M5vGWbmaNh+6IdVo8ePYrevXtjyJAhOHfunDK+X79+Qp26du1aNG7c+KHlZGFE7lgGTlNH5tS4ycnPGKaq/UU0tQOt6pc9c7Ih+430TI9B/6RoNEpLwvUznBa+3JqR//3vf+LGot/PP/+sjKcYbHk8/by8vMT47OxsEcVAwsjevXvRqlUrfPjhh+W6iIxpkZ+dj5oZ6aKdXdMe1rYFVbhkXhkxYoQQcikiRqZ9+/bYtWsXdu/ejQ4dOhS7fk1hhJxY3Rs6wM5fVcwq4WQi8spgFmIYpvzCyM1jKfDMzhDO4y3r6f+Z1OxPyiuMWNZXO+leP8D5RqrNTEPqbysrKzz22GPCeXDq1Km4cuUKIiMjq2PzjAGTFpIOszyVk1eD7uoHmJIOTZ48GS1btsSmTZuU8Q0bNhRaEOok+vfvX+r6ya+kRo0aBVSu7j1Uppr8rHwknma/EYapTGHE1tZWfCzI+G24hj9uHMbfV/ejWS1V4jN9xs3NTTjFE1QwjxzltaVxL3W6+9oZLIwQZYuNLMT3338vftTxv/baayJvA3HhwgWhFqeLNX78eGGnJ8jJR55HvhnJbk/jKfFNYUiTQj9N6IKTXZ8xLVKuqB9UxwYOwvT31Vdf4bfffitwj9B99NFHHwkBhTIlkv9IWT3d6Utnz549iIqKwp07d+DazQURf6kE5fBdcXDt6lIFR8aUB7kP4L7AsKBEg/QBIWsj6Rmla5ifL8EtVvWM51qYo5avary+Q30GOcJnZWUJszD5qWlDm4EOOPSRqp1zM8UgjrkilCX6UWthhHxEKF8Drfzvv/8Ww+vWrRMXg4bJNHP58mUROunq6iqEk4yMDDg4FAzXomGq3lgUS5cuFY6GmowdOxbjxo3TdncZA+f+iVilveboGnz16ZdK0iTC2dlZRMxQFlUScsujbaPKoSSMEFu2bEHPlmqNyrFVsXCeXC6ZnalCwsPVBRIZ/UdTe9miRQuEhYWJdtSNfFEpm4h3t1fG6zuyZoTYsWMH3N3Vju9lQTKXYGZnBilDQsK5RIM57vJSp06dUufRupeVQyGJSZMmiZuMNCKdO3cuMA/5h+zbt08II3Z2dgVeIAQNy0WHCjNlyhRMnDixwDj6avX39y+ThMUYDzeuJyrt+ZvmIy1fdR/RvfPqq6/ijTfeEGGCFWHAgAGYN2+eaIeGhuK55+rjtP091ExPh098Clwd26OGu/6GG5oS9AVJggj3BYbF1atXlfbQoUNFvg7i8pZYyC6rlvWdlfH6zqBBgzBr1izRpqi98ux3dLMYJJ1OQk5kDnzdfGHpZNofPRU++uKEA4rHltXkpEkh7YkMZcAktR2NLwrKjKmZHZMgnxPaFgsjpkXEmTR4PajMG51/V6h3KRqLHKBlB+mK0qVLF6VNviZ0j6U3dEX6+SzE+LkiNiIHLp5WlbItpnLgvsCwOHLkiHLdNMN6755JhfeDedxaOhlM/06WAOqLqNYO1agpz347NHYSwghx7VAqWjzqBlNGqzOYkpIiIg7IVk8+HFTtNDk5WWhCKLQyISFBkYLJZNOzZ08lyoZsa//++69YdsmSJcJxsCh/EYaRyUrPg0eqypQXYWmBfORi+fLlmDt3bqUJIkStWrXUBbtOnxYdzLhlDTE8vA9mBrdD/TZFa/AYhikdei9Q1BvRunVrODmpa89kXlP7hNXrrr81aQpD2n5ynifILYHejdpyQVI75J/9j51YtRJGqJOmFwFFKZCairyjf/rpJzg6OopIBPLp6N69O95//308/fTTYh6CtByU8ZKyYvbp00cUS5JVXAxTHNcu5+CqvTNSLCxxxzxNfH3I91RlI4f4kh8TdZweftYPhREzDFM+rYisJdcM6SXsolUvYdJ8Nuuuv2ngS8o3QsdGEaPa4t9JLXylXGJhRCszDTmkrlixoshpFFVDv+Kg1L+rV6/WZnOMiXMtxQbv1Okg8g9Y3f5EeLBTpFZVCSOkzSNIsKYvOIZhqi6/SFpSLjxTVJrP+04OsHWwMDhhhKL6ZPMuJV3Uhpb9nLCqsTfsGjui5SPqZIumiml7zDB6zeXbigMScjIuCUfTqqJwJtZnn31WGc7KyENqQh7cfQr6MTEMo50wQppzmUsH02ABlcYky9dwTDSVlYnVzcsKLxxRmXoYrk3D6DGXbmvkCUm/jIEDB1bZttq0aSMc0jSTn106nIr5LU9ja8A+rH1W+4JYDGPqUFoH8sMiKC8V+WfJ3LuZiSwzlaeAfSPDE0aovAS5KFQkEyujxjBclxmT5HLog0Z+Nhws7hYIH68KhzQqU0BQduCkpCS4+1khMDJOVPC1uMx1ahhGW0iwlzOUFvYXGfZaLQyL6oeAf7uh/1tyTI3hYGFhoWSSpXBzrrdWMVgYYfQSMo28+d8hfHH7DEbfPYN+fXuJ8O6qRBZ2yCGNwvW8atsgqobqy8c7MQX3IwpmBWYYpnz+IjKW1uZo3t0R/o1V9aAM2VRDfUZ5SEnIxZF1iTj+r2mXnmBhhNFLrh5PR82cTLROi0e99Lgq9Rcpzm+EyGnqpjwoR1epQtcZhqkcYcTQqajfyI2gdOyvvwdJz55A0Kca5YtNEBZGGL0k5Hiq0r6TH12l/iIlCSN+/dTRO1F746p8HxjGWKBUEMeOHRNtHx+fMqUENzVhpG5LW2Sbq6KIHO+ZdngvCyOMXnIvOFlpJ9rdK1BosaqgbVD4uiyMkLmm63hX5D2Ybn2FNSMMU1aogFxqaqoSRUNZuWX2LY/DvDZnsGDMdZzaarjmCSr46u3trZhptC14Z2FpjlhXlSnYIzMTcVGmawpmYYTRS9KuqV/8vm0sCnRkVQVtQ/7SiYmJEcWr3H2tcddVVe7bOyUVUbeyqnw/GMbYTTSh+5NQ+04s/PeFIuSYWgtqaGj2GYmJiaKSr7bkBagjic7vMdxzUVFYGGH0EqfYTPE/B2boN7pRtW1X01RDpQ+I/GbqhETHV3NUDcNUVBjJuq6RBr6r4YX1VqapxqmZ+vjDT5iuqYaFEUYvI2lqZarUlZFWFhg0uG+1bVszfFj2GwkYoPYbubufhRGGKY28vDwcPHhQtJ2dnQtUeyeaQaUBkCzM0LyXYaWBr2xhJLCzWhhJvczCCMPoDce2RcLqQWbGu7a5VZYCvrSORRZGuoxzRe6DQudZYar01QzDlKwViY2NFe1+/fqJnBwyeVn5SLuRJto1GhleGvjCyLlGNPsMbWjRT10wz/IOCyMMozcc2XhDaed4Vb2viCbu7u6oX7++aAcFBYkq0y41rbC+W0s806A7Xvdqh6hYjcywDMM8xNq1a5X22LFjC0xLu54KKVf1DDk1NWwTDeHi4oJGjVSm5LNnz4oK9drgWtMKsXZ2ou2RlIrcbO2cYI0FNtMwekfsRdVXE+HTtvoLSMl+I9SpnD9/XrT9h9XEPWtVh7E/uNp3iWEMykSzYcMG0baxscHQoUMLTE/WqFBbo7nhCyOaGlX6eJH7DG1I9VKdB9v8fFw9aZraVxZGGL2CQuN23J+Lb8wOYq3dPfSbVH3OqyU5sfZpq9bQ7A1izQjDFMfRo0dx9+5d0X7kkUfg5FRQ4Di6WS2MWNZTmyhM2W/EqoHqHN2zssW186YZ3svCCKNXXLhwAVej/sOBuC8R22YtmnZShdVWJ0U5sXZtDlg/yEa/jzUjDFMs69atU9pjxox5aHrcObUwYlbXuDQj5RVGPJ/0x7jGvfFMwx4ItnKBKaIqU8owesKuXbuUdnVkXS0KKphH6mUy08jCiJ2NGUbVSoT96XtoeSseN4Jao0Fbe53sH8Pos2Zz/fr1ok21pIYNG/bQPC6xqkiaZCsr+Da0hjFAfQYdLxUFLI8w0rKNNdIsVBrXcyaaFZ41I4xe8d9//+lcGLG2tkabNm1E+8aNG4iPV4Xz9pXiMDouDA0yU3BmLYf4MkxhSHiPjIxUnl8K69Xkbmw+/vCsj3/d/HG9gQ/MzY3jFUQfL61btxbtq1eviqrf2lDbC3B68G1znoURhtEtGRkZuHEyD53dXkbLgOGoW1sV1aILNP1G5C+d+oPVIcZxh1kYYRhtTTTnQ8zwn6svfvdujKTxDY3qBGqaak6fPq3VsubmZmhZT9W+cw9ISDE9vzTjEEsZo+Dw4cPobDsOH2IIvkqdic1zYnS2L0UVzes80hm5lqpHpmFCgqhdwzCMCnoeZGHE0tISw4cPf+jUaH71t6pfvWH7+u430scyHi9HXsIPt04geFMiTA0WRhi9MtEEmKuKThF1u+jO076oiBo7JwvU6qYKNc6JzkR6qGmG4DFMUZA24M6dO0qis6KSFZ4PUQvwsibAWKioMNLIPAODEqPQMDMZ4UfVhUJNBRZGGP0SRjJVD2GeuRmadNadgyiVO/f09FQ6FlkL4t6dTTUMUx4TDZF4IgGuOVmwNJfQJNC4zmPDhg1Ro0aNcgsjtTU+vkwxLTwLI4xeQHkJLp6/CD+oHN6cGzrAxs5Cp9U4Ze0IObDK1Tjde7AwwjAlmWgo9ftjjz320DyZaXmYevQM/rx+ED9EnoaNtXGZacgZt0OHDqIdFRWlOPKWlZb9HCE9OCVNJRZGGEYn7N69G97mPrAyU4X6OTbSffGsovxGnFvXgPmDWhph/8WLUEaGMXUoDXpISIho9+nTBx4eHg/Nc/FQGqweaBjNPG1hjFTEVFPD3QoOdVXa4KybqZDyTMsnjTUjjN6YaAIt1Hpbp8aOeimMmFuZI9RVlZTIOiUbFw+oU9czjKlSFhNNyBH1175dI+NIdlbZfiM1mqnOS35GPtJCTMsnjYURRi9UvJTsLMC2rTLOsZHuhRFZ5arpxErYtFebas5t5BBfxrSh51cujEemiqJMNET8ebUw4t2ehZGicHogjBApGjV8TAEWRhidc/HiReEzEuDYXxkX7+KgF9U4mzRpItrnzp1DZmamaLd53BNhnQOQ935rDHlXHf3DMKb6/FJyQKJnz56oVatWkfNJIarMq0TT3rr/2KgKfHx84OvrK9qnTp3S2ozroKERPvufaUXUsDDC6E3W1YB8lb00F2ao114/Uq3LphpK8xwcrCpK06a/E57f2gTD3qgFdx/jSGfNMOVF1oqUZKIhXO6rvvSTLa3g38TGaE+43GekpKTg2rVrWi2b6q3WjIQeZc0Iw+igHo0FUqwckW5ugVhHe9g+cBLVR78RhmEe9hehCLSRI0cWeWoib2TCOUdVjTbBw8lo0sBXtt9I/Ta2SLNQlYyrEaPWJJkCXCiP0Slk+jhw4ABgVw/v1elIBmg80SUXz+jJdWFhhGGK5/Lly7hy5Ypod+vWTZgpiuLSPo0Xax3jNNEUJ4xMmjSpzMuam5sjsW8AkqzNhV8NmXmMWXDThIURRucp4IUvhntT1QgzMzRobKU3V6VFixaws7MTdXMKa0ZuBqfj9Jp4ZCXkYtJvtXW2jwyjz1E0ROTJFMieJK4tjNN5VaZdu3ZCS0SOveWJqJm+ugFMEdMQuRj9r9Jr31Tt3FZbf5IhUY0N6lyI0NBQxMSo6uXQF8vpR46jxu+XYL/hFnKzOd8IY9rCyKhRo4qdLycpBzlmque6blfjFkYoC2tRju9MybAwwuiBv0hBYaRZHegVnTt3fjjfiLk54gJUdWoc8nJxertpOZsxDDlnXrhwQXlG/P39iz0pM9Y2xCPh/eD9d1e07GvcZhpNUw05vlNCOKZ0WBhhdMa9e/eUB/XzdH98FhaEZ2JuoIGffl2U4vxGanRR5xu5sonzjTCmxfr168tkopGh8g4UiaYvzun6nPwsIyUPJzcnYfOcezAV2GeE0WkKeMIcVmiWngVrKQN+yIS1VSODEEZajnRD5EpVO+N0HHnm6WL3GEbnJprRo0fzVahEYWRV82PwSk1Dnpk5sl/oC2tb4xfgWDPC6NxE42XfAdaSyucivZbuk50Vxs/PD97e3krHIicyatHLAYlWqjwjtaISkZWRp9P9ZJjq4tatW0renfbt26N2bXbgLuz4bmNjU37NiJfKlEX94uWjppEWnoURRieQp7nsvFrPqZsy3koPw/40K/gmJyfj6tWrit9IQh2VqcYuPw+nNptWxkTGdNHGRLN0WijmtQvCwgk3EHHdNJw5ra2t0aZNG9Gm7LRU+VsbbBqqnXxvHjYNfzQWRhidcOnSJURHR4t2Cw+1StOjhf4JI8U5sRIuXdV+I9e2sN8IYxqUNaSXyDwZh9q378N3VwhysyWTNNWcPn1aq2VrtVX3g3FnWRhhmKqPogHgL6lrWdTuqH9mmpL8RtqMUQsj2UEsjDDGT1hYmKi7QtDXf7169Uqc3yVW9TJNsbRCQFPjTQNfkjBy8OBBrZZt0lutGcm7xcIIw1R9fhEA7mmq/AN5MEPTbvopjJBdXM6EqCmMNO5kh3gbW9H2upsovOAZxpjRxkSTFZsN5yxVGnjn5o4mk02U6N27t3K8ixYtQlZWVpmXrdtKnRbe2UTSwpvOncHoXwp4AL4+gfBMzRDtWAf9qUlTGEdHRzRr1ky0KbdCerrKqYw6m/hGHgh2cMNqz7o4dZGTnzHGjTYmmpRL6q/6gE7GneysMFS9V04ER2kMVq9eXeZlzalfcVeZalyzs3A3tOyCjKHCwghT7Rw9elSkVycGdHxGryNpijLV5OXl4cyZM8r4Gm83xf9qt8MazzrYd5Wj5RnjJSIiAseOHVMiRho2bFji/MkawohTsxowNV577TWl/cMPPwjH/bKSX1stvF3YY/ymGhZGGJ2aaBq69FDaVnUMQxghjh8/rrT7qJzmBfuCTcdBjzE9tE10pqkZqdFMP53Tq5IuXbqgQ4cOSmp4WSNcFpybq4WRyFPGb6rRWhiZMWMGunbtih49eojfyy+/rEz7448/0L9/f/Tt2xc//fRTASmQoicmTJggKjvSOuRICsa0hZFHnmmM5BnNcKdHbTQY5gF9priImkAvM9R9UKz02CUgI4sFEsY40cZEQ1zZrxJGJHPAsZHpCSOUFqCwdqSs1HlQwyfW0gZRsSbQp0haMn36dGnr1q0PjT906JA0ZMgQKTw8XLp//740btw4aePGjWJaVlaWmEbDmZmZ0q+//ipNnTpVq+2GhIRIeXl52u4uo2fcu3ePnirxa9u2rWRI5ObmSo6OjmLf/fz8Ckyb+nWeZN49V6rXPkHatSVNZ/to7FAfwH2BboiMjJTMzMzE/d+kSZNS589Mz5X+cd8pbXXbIS32PySZKtnZ2ZKvr684b3T+bty4UablUlNyJZduGRJ65EltnjH+d1+lmWm2bduGkSNHimyVHh4eePLJJ8U4guzrVlZWeOyxx0RWuqlTp+LKlSuIjIysrM0zBsKePXuU9oABA2BIWFhYKCpXsp1HRUUp0wbYJmDV1f34OeQEbi2N0OFeMkzVsHHjRkXbXRatyOXDabB6MH+Gj+lpRWTo3ffiiy+KNp2/n3/+uUzLOThawKu2KsPzpdtAbq5xa0fK5W33/fffix85L5EKqkGDBqK8+qBBg5R56tevL1IGEyEhIWIeGVtbWyG00HjyOC5Mdna2+GlC1Q/lNNyM4bJz506lTSY9Q7umlDtg3759ok2OfCSAi/H97HHls1zRNjsfb3DHZSjI55XPr25NNBQlUto1uJxkjT+9m6BuZgqadXQx6Ws2bdo0zJo1S0ThLVmyBJ988glcXFxKXa5lPeDqHSA7B7gSJqFZHcMUSMoS0q21MEI+InXr1hUr//vvv8Uw3aR0kh0c1A6I1JYjJui/5jR5uhweWZilS5di4cKFBcaNHTsW48aN03Z3GT2Cvgp27NihCKR2Zr74a9ZN+Lc1h29jc1hYqvKN6DN16tQp4PvStm1b1YADcM/eDrXSM+Adn4yQy6GwcGD/8KoiPDy8ytbNPMz9+/eVxF1Uh6ZGjRoi+VlJHLrlgh1uqhLcC/vElDq/sUMfLitXrkRaWhq+++47TJ8+vdRlAtwpAslVtPecuA9Hc8OsU6PZb1aaMNK8eXOlPWnSJGzatEnkXbC3txcnWYbadnZ2ok3/NafJ02mZopgyZQomTpxYYBypxP39/U0qaY6xcfnyZRFvT/Tq1QuxQa5w+/kc6M7Y278upq0qOZOjPvDoo48q7WvXriEwMFAZbjQsHYl/R8BCkuAU7QTPfvrtkGuI0Nc1CSLcF1Qv9BEhazYoEKEshfFu31e3B3SpCf+aMGk++OADIYwQ9J+0I5aWJb+CewZkID3qitAuWW90R+AE/e8jy0uFkyLIwgFJPjdv3hQvGYJMNHKaYNKkaKr4KOkV2dxpfHFFhuhX2O5G22JhxHDZvXu30iaT3v3gNDwIQoGbgWRnJLNiQEAA7ty5I+pNkLaHfEmIOoPcEfy3yl8k4UgCag0w8d63CuG+oHrZsGFDAS11ac/q5XNZOHqBXi9mcHEEAmqZicgSU6ZJkyYYMmSI8KWk/uPff/8V57IkmtUxh0WCqk8Ju2ZpEH1kedHqyFJSUkR+BfLnIB8Oku6oiilpS+gk0w1LQkZcXJyYRuOIdu3aiVS4dPJpWbKZ0YUpyl+EMY2Q3oEDByIwS60ta9hFv3OMFJVvhLR7FLIu49ZNXacm7hDXqWGMg9jYWMVPij465Wq0xUGVeU8PPYHJt67AXMrHiO6qEFfm4SRopVG7hQ1S5bTw94078ZlWwkhubi7mzp0rHA/py/bQoUMinwilyu7evbvwsCbTDf2nnAwjRowQy5GW49tvv8WqVavQp08fBAcHC2cexnQgYVRO+OPj44OmTZvC7p4qkY+ZhRma9TAcb/viiubZeFjDqanqOJLOJyM9vqATNsMYIvQRSVmHCerbSxIsUhJysW1IMDwyMvBIQiTeybyBn19hQUSmX79+iqsDOcBr9h9FQZoQqwaqfCMu2dmi1o+xopWZxtXVFStWrCh2Ovl60K8oqK6HNrn5GeNLAS87LIuQ3nwg9YZKM2Jfxx4WNuYGK4xoOqKlN3QDLqeK49vzRwKGva6uSMwwhoimib0ks0Judj5W9D+P2gnJYjjB2gbTFtdGDQcWRmRIkHv11VdFdA3x448/io/0kmjUywm3ryYoGW1ternDGDGcNwBjVCaa9LB05GeqHOIcGxuOiYagCBrZT0QzLTyR1VhtqonYw6YaxrBJSEhQfL3IV4qqVxfHwhFXUfuB12q6uQUaLW2Lui1VQQyMGgrO8PT0FO21a9eWGhnm1MypyFo/xgYLI0y1sGvXLqVNZr5wjVoLTgaWJpqiwFq1aqVECJHflEyXx11JKYJEK2uY2+lnBWKGKSsULUnm+dJMNH88exuBJ1Uv1VyYwXFWa7R/xPQK45UFSmvw/PPPizaZv3799dcS56+hIYykXGRhhGEqlKMgKChItFu3bo2aNWvi8Fa1MHLTwrA0I5qmGoqmoagaGU8/azTY3h0Tonrh2XUlVzRlGGOoRbPxq7vwWHdNGU6b3hSPPMdh7SVBwogcMfr7778/lPpCE8fGjoCFSggMOcrCCMNUKAW8nEaaTDRE1i21MFKzlWFpRkpyYiUadXQw6hA8xjRISkpSzKsU+ah5z8scWp0AzLmgqNgj+tfF41+rEp0xxePl5YXHH39ctBMTE7Fs2bJi57WwtcBdO1VOLvOIVGRlqJyJjQ3uMZlqNdHIwkhSKpBpZg56rJp1M1zNCFGaRzzDGCKbN29WynKMHj36IQGbkqBd/ugabCSV71doU2+DSFyoj2G+P/74Y4np8jN8VKYaqvVz8WDxWhRDhoURpkohjYj8dUWZeLt164a8PAmzPFtgTJO++LxXD9g5GZ5vBdVlcnZ2VpxYZc1PYdKSVPZ2hjE2Ew0JJ8O2t0GEuzPCvNwwdUcz1ghqAfmdUaoL4saNG9i+fXux8/qN8kLkoHrIebc1arewhTHCwghTpVy9elUkwiN69uwpnLdCo4HMbFFPG75NDPPBoo6YiuYRlOKeMipq8udrd7Cg0QnsrrcXd29n6WgvGaZ8UIJLuY4UmRS6du1a5Hw+9WzwxMn2GLerFWwdDO+jQtdQmG9ZkqCNeKsWpv9VX/x39ymYndxYYGGEqdaQXuLybfX0ZqXXT9JbKLFfcaaa1Jvp8I9NFGrV43+rcgQwjKGwdetWkahQrtArh7Ln5eYjI6Wgz4Kji6XRviCro9YVVbiXfevOnz8PU4WFEaba/UUuaQgjTWsbbkKkkvxG/Pqp841E7+d8I4xxmGgWjryO5R1OI+aO8WYCrW4N6yuvvFLAd8RUYWGEqTLoy0quaeHt7S2y8BLWy6/ho7BgTLl7A008cgz2CshmmqKEkS7jXIRzLmF9hTUjjOFAYaZUzI2g5Fw9evQQ7RUvhSHgaBj87ydiS8+TyEwzzqiO6mby5MmK/xnVdIuJiSlyPoqiCfovGWs/ikJshPEJgyyMMFUG1V7QTAEvJ0yqcTMenVJjMTLuNhrUMdxbkDpqufL0mTNnRPFIGVJb33VVJX3yTklFdAj7jTCGATlSZmRkiPbIkSNFmft722PgvvqqMo/NqED2EakkqLbb9AclJSh6af78+UXOt2Tsddx9/Bgc5l7Ama3qRIvGguG+CRiDNNHk5uTDI1kVmhZnbw8HZ63KI+mtqSYzM/Mhe29eU1elfXwNa0cYwzTRJAYlIXj6OVFviYh/pA4mfu+vux00Ql566SXFL2fevHmiPymMawt1Jtaok8aX/IyFEaZanFcpBTxx40yGkpcgvabh5RfRxonVvz/7jTCGBWlEtmzZItpubm7oVKcTTj8RhPwM1TPrPdoLE1c00PFeGh8BAQEilwtBZpqiisrW7aoWRtKvsTDCMGUiLi5OmC7kePpatVTVa28eVWdetahjeJlXtXFi7TzWVfEbsXlQdZNh9JmdO3cqqckfe2Qydg8/j+z7Kv8Et66uaPlLC5iZG67TuSGF+UqFche16O2IPKjOvW0kCyMMU+4U8ETMOXX2QLdmhi+MUK0ducZEYWHE3duqgN9I1C32G2EMw0RjaWaPNidGwfae6nm1r++Atstbw8KGlelVRZcuXZSPGzL5ys7/MpQc8r6TKi28R0qa0TkQ853FVFt+ESJToyZNnU6GL4zY2NgIgYS4du2aKLmuSV4zDb+Rf5Oqff8YRpvoN6rSC5hhVOBK1E1QPatJVtbwndsG1q6cS6S6U8SXmBb+gHGlhWdhhKnSFPCUcbV79+7KNOtoVQdHMn2Tbiop35hMNSdPniwwLWCCD77ya4knGvXCXjOuZMrot8M5ZV5F4Cys93sUu1x8kGlujsB5bdCgveH7dxkCo0ePhr+/yjmYfHcoTbwmdo3VfiO3jhiXqYaFEabSuX79OsLDwwukgJezN3okGU8kTVn8RroPd8Ixt1pIsrTG/rM62DmG0cZE4zUdCHgPeWbm+NmvKSx/6YKuo1z4HFYTlpaWePHFF5WPup9++qnAdJ8OamEk4TwLIwxTLhONsUXSlCWipoaDGdo1VLUvhQIxCUUX1GMYXUL5LdbvTgXq/6qM+/kVcwyfYPimVENj+vTpsLdXaY2XLl1awPTbtJdaGJFCWRhhmDILI5TsTMbN2wqJzzRFWJcAuA2saTRnkRKfeXh4KMJIYS/43iqXEsEB1o4wesjS2cfwTd7LCMhS5bd4YzzwwiiOmtEFrq6umDJlimhT0shFixYp0/waWyPZygoJFtaIzrEqtlq4IWImGcjRhIaGIjAwkEtUG8AXFuUnoPBACueNjo5WMq8aM0OHDlVSaN+8eRP16tVTpm07kIuvX45By7R41G1lh9fXq6cx2pGfn4+wsDDuCyqRG0HpODH4ONxyc5BqbolVPQOwfm19mHMIr05N3Y0aNRJt8iEJCQkRJhzi0RezsPW8lWiHrDZDHR/j6F/ZZ4SpVI4fP67kKSATjSkIIqX5jXRpIuGtiIsYkhAJl9PROtg7hima8KuZODritBBEiDtW+Vg4z5sFER3TsGFDUdGXIP+79evXK9O6dlJHNW08BKOBhRGmWkw0piSMkECmiWtNK0S7qfKNeKWmIfLmw6meGaa6ocq7/z1yGp7pqjo04VaWON3hH3jUYj8RfQ7zHdNbPc/a/QZh2CgTLIwwlQZZ/NasWfNQCng5kmbH/PsIOZ8hVO3GRkkVfAnHTurU8DnBnI2V0S1xd7OxvucJeKeotJj3LC3xQeKrGPt0X740ekKfPn3QsmVL5QNH/shp6G+GFqr6nLh8Lhu3bxhHBV8WRphK48CBA0pcPD1I3t7eyrSbQRnI/18QrvY5iPldCxaUMxanM9nGe/bsWZFASpMBz6iFkdQTLIwwuvtg+GfdTixpfwiBKaqK2vEWlvgg5X8Y+VRnUaWX0Q/MzMweShEvM6l+Cr64fQZ/XjuAA3OiYAywMMJUGr///rvSnjFjRoFpN46qswVa+hlHsrPiTDXkxEsCiSauHV1gZqnyn4k/Eq+T/WNMm6NHj6J3j4E493I+mmXkinHJ5hZYXW8L/tn/ExYuXMgBAnrG448/jpo1VZGH5Ddy584d0e7fzRyt0+JBdX4z992DMcDCCFMpxMbGKk5W7u7uD31huT5ILU34tHY0OSdWS0dLOLdxFu3U62nIiuE6NUz1cPHiRYwYMQLdunVD7pWW6JCl6vbTzS2Q8rItNh/9voCZkdEfbG1tMXPmTNHOy8vDr7+q8sC06uOEu46qXE3+sYlIuq3y+zFkWBhhKoXly5cLjQAxefJkUbNFE8f7as1IrxGOJufESrh3U9epOfk3a0eYquX27dviWSS/A1XNGeBo/Pf40yUMWWbmcPmmNaZ/2N1kIt4Mleeee04pxkna59RU1Yed/0hVJXQi4b8YGDosjDCVYocmFa9mBsHCpFx9oBkxBxzqG0/2VU2o05dT3xflxBrhpRZGLvzLwghTNcTExAhfA/JhWrZsmZIYy8fHR7zMll2dgrYHuqP/FK6VZAjUqlULEydOFO2kpCT88ccfot35WS9lnrubDd9Uw8IIU2EOHz6Mq1evinavXr0UR04ZKV9C2o0Hpchr28PCjiydxoeVlRXatWsn2pSk6P79+wWmt3/MBblQfYXaXWcnVqZySU5OxieffCIS7lFNE1lTWd+zL7755huRjI8+FOg+DWxmx6ffQMN8f/rpJxGR6NjYUfmwiz+WgKx7hm36ZWGEqVLHVSLuRjry0qlOL+DY0Di1ImWp4OvsaYWI9n6I6F8X/p800cHeMcZIZmamyENBQsinn36qqPHt7Ozwdret+C7/HTQye1oMM4ZJixYt0K9fP9EmoXLr1q3CvOY1/IGpRgLCNtyFIcPCCFMh4uPjsXbtWtGmNPCjRo16aJ7jO9T+ItfMjNNfpCxOrMTMnU0x4+8G6P+MezXvGWNskEMjqexJE0lfzuRETlDacHJ6XP5iEHpdsYCVJMHsq3O4cFDtRM4YHq8WEebrMVTtN7L3F8M21bAwwlSIFStWKDk1nn76acVnQpOYc+pO0KqO6WhGDh48qNN9YYw4V8g//wgfJSqoJod7yqGgZDL9oN//YL8kTBl/d1BdtOhp3B8Cxs6QIUNEmnhi3759OHfuHFxbOuK+vUrj5XsvwaCzO7MwwlSoU9Q00RTluErE3c1FtpnqVqvd0bg7xICAANSvX18RRjRfFAxTUYKCgtC1a1cROn/58mVl/ODBgxEcHIy//voLjjeccO75C0J1T+QOC8TUPx+k7GQMFnNzc7zyyivKMJnmaFxmB5V2JMrDBXdvGW42VhZGmAolUZI7xO7du6Np06ZFzrfGrz5GN+mDGQ26ollv4xZGyI5LGiJZWPvzzz8fmoecz4J3p2D5S2EG/SXDVC/kEN23b98CYeNdunTB/v37RcXo1q1bI2Z/LIKfOQcpVyWJ+D/li2FLG3EyMyPh6aefhouLi2iT4JmQkIDBnwei6YGeePZaJ7QbpKqBZYiwMMJUmeMqkZ8v4fJtIN/MHLZ1HODgZJyRNJo89dRTBfKvyKGVMoufCkH0+KPw+Osqjq3kEF+mbHz//fcitJNo0qQJ/v33Xxw5ckREsBGH1yTgyLizyM9S1X7yHuWF5nOacR4RI8LR0RGTJk0SbYqWosKkAU1tUbu54TsnszDClAuSyOWieCSpjxkzpsj5wu4C6Q8+/pvVNo2TXbt2beUFce3atYeiagJ7qb5siJiDLIwwpRMXF6dk36QEWPQSGj58uCJonN6RjOgXg2CTp4pas+/hgVbzWsDMghOaGRvDhg1T2hRVYyywMMKUi5UrV4qQQll1WFzY4GW1Dx2amogwQsimGlk7okmXsS7IefASsed8I0wZIP8AOWT3mWeegZ+fnzLteriED77IgHW+ShC5U8sVHf5oBXMr7t6NkR49eggNCbF9+/YCVdCpfX6/YUZN8d3KVJnjKhH5VyQ+uHMWT9+7iRYOhl8/oayQpkgW0FatWlWgiq+TqyXueqjq1NRMT8fti6ZzXpjyaSF//vln0aaEZe+9954y7c49Cf1fk/CfmSc+CWiD0JpumLC/DRxcLPlUGynW1tYYMGCAaFM496lTp0R78eQQ/OV3CLdHH0XMHcNzZGVhhNEayp9x4cIFxYGuefPmxc6bcy4eXVPuY3xsKOo7qyqFmgI1atRQcq7Qy2TLli0Fppu1UKeGP7WWs7EyxUOCCGVXJajWDEVsEffiVYJI+IOyJPmt3PH4iXZwqWnFp9PIGTp06EOmmuzYLLhlZcISEvbMM7xaNSyMMFXiuCpjHaVKeEaKxCbdjTvHiDammjqD3JR2zCH2G2GKhhxWyURDWFhYKFqRmPBsvDMuEjciVPM18AP+m2MGtxrcpZsCgwcPVtoUSUU0f0pdqyZhu+ElQOM7l9G6c1y9erVoOzs7Y9y4ccXOm5ebD/cklTASZ2cnzBOmBKVvpuJkcoehWaum82i134jjDRZGmKIhp9XExERFuK1Tpw4SYnLwT98gjAu+hAkxIfD3lLD7BzPUcmNnVVPBx8cHbdq0Ee0zZ84gOjoaXUc7I/5BtXTfyDjERhiWqYaFEUZrx9WMDJWPw5NPPgl7e/ti5711NhO2D5zq0jxNSysif8nSOSJyc3OF70hRfiOe6RkIOc9+I0xBUlJSRDgvQcmt3n//faQl5eLv3sHwi1eF+A5PDMfOj3IRUIsFEVPMyCqzY8cOWFiaI6W1KgEalQDYM79goU6jFUbOnz+PDh06YNGiRWJ48+bNIhU2efrKv7t31YV7Ll26hAkTJqBbt25CtU+SHGO8jqvEzaNqr26LOsad7Kw45JwABJVz18SsldpUc3od+40wBZk7d66o/URQCfkAvzpY1uc8Au6p7pU0C0s0+KMdmrRSfQ0zpsXQIvxGmkxU16qJ23bX+IURCh8iib1wxk0qn37o0CHl5+XlpSRnefvtt4UwsnfvXrRq1Qoffvhh5RwBU22cPn1a1EMgSPCk61gSdzVq0rg2M01hhJ6R9u3bK6m8L168qEyrM9ANyRZWOOJUE8Gx7HTIqKEw3jlz5og25RJ57733sWjIFdQOU33tZppbwHtuW7R/xHAzbjIVo2PHjnB3VxXcpLwz9J7tMd4FCdYPTDXhcYi/m2Mwp7lcRvwNGzaICAo57r00yKZFIWmPPfaYGJ46daqwp0dGRsLX1/eh+emk0k+TnJycAvHUTPWzYMECpT1t2rRSr0fGDXW1Xv/2DiZ7/SgjKwlysnZk9uzZot1lvAs8VvZCVq4Z6sUDX5jo+dEG+R4y9ntp/vz5ShXe8ePH4/Dnlqh9TpW0h3yNHL5oJXwEjP08MMVDQuqgQYNEWngy6ZECoE+fPkhqVROup8KFqWbX3BiM/dQbuobMjJUujJAzFdm+qXS1LLnLULgnCRlUSp4eIDkrZ0hICBo0aKDMR5VdKWkPjS9KGFm6dCkWLlxYYNzYsWNLdJZkqha62WWfB0q4QyG9YWEaGc2KwDIiRfyn7tIpMB5hYaZpiiDTJJV1J78RiqohMyUNE63q1cLJa7a4FQUcC4qAj7vKx4YpmfDwcKM9ReSTJQus9MJpZ/EqfLffUqbHPh2AvgNSERZmmMmtmMrVjvz111+iTYEFdevWhecgK0CVegT3Nkch7BndO7KS43WlCyPz5s0TZaqdnJwKjG/bti3+/vtvYZqh4mlvvvkmXF1dhXBCD5eDQ0EHRhpOT08vchtUFptspJpERUXB39+fCz7pUCsiXy+6NlQboySoJo1nyi0lkmZISxNKv1qIwMBA4Wy2adMmxMTE4ObNm+KLhhjUGTh5TTXfzVg/dGmr233Vd0gTQIKIMfcFP/30k0j/TjzV/Sc02q5yViXujmiAKd+Z7rPEFIT64tdff108F1SniPoa3+clrJ8dAYu8fNxMt4ebZyCcio8z0Bu0EkauXr0qBI133nnnoWmaGg4y4ZB/yL59+4QwQpko09LUKnuChouLxKAMc/TThMw81PkYawek78iOysSzzz5b6nXIycpD+sSGuHctFRaOliZ/3ShZFQkjxIoVK5Q8AX3aSJi1TIJlfj6C9mVg0iMFhXymaIy1L6APt2+++UYZfnR8H6TOug/nnGyEdfTHs4tqG+VxM+XDw8NDaKlJELly5YrQVpMWIviZdvjhoD1yzc3R9YQZJvTT/2grre5qcsCjg6WvPPqy27Vrl1A7f/rppw/NS+pFuVopqY7oa1CGappERESI8Yz+Qz4/dO0JcsaU49tLwsbOAk/+GIDntzfFjLUNYerQM0PmS2Ljxo1KRs3OTSV8Fh6MNVf3oe3KYB3vJaNrFi9erEQhUgbfsS80R9tNHRHWJQDT/23MgghTpqiawWOchCBCrNtfsGq4UQgj9HBQR0q5JujXs2dP4ctBaqKjR4+KtNeyBoVMNjRdjrKh2hxU8pocU5csWSLU/EX5izCGnXGVKRobGxth3pSF8bVr14q2na05PG3zYCPlwzMjAzeDizZdMsYP9ZFff/21MixHHDbq6IDntzSBpTVrRJiS843I2Vh7tAQ8HxQH33YcSMvQf4FEq7ubHE9JLST/qIMlEwz5j1C9EnIw7d69u0jOQ9kCZbs4mVy+/fZb4QBJ3r7BwcGYNWtWVR0TU4lQxJTsIEWOq2R+Yyo354h5K3Wdmtu7TdPJl1E57sdGp+Kxmj9i+KMj0bp1az4tTKm0bNlS+bAn1wjy7bO0NMPIHqrpZuk52L5Z/5MqmkmyLUXPCQ0NFc45bC+tfl8RObkZaUU0w3tL4uiGRPg3tYVvQ2u+Zg+gR43yjpDmkLh165YwVV7dEoeQSarQX78nfNHyl+ILD5o65KhHpmJj6wtIY9ygfmM8lfsLumZZ4rqfC6YdaAdHrr7LlAHqm+UIVCrKSaabXbsycWTaJbRJi0NEvZp44YR+C7fG8zQzemOioRfG3WdP40K3A1jc4DhfGQ0/Kk3tCDmyEg36u8DcRvUoxh3hOjWmyLI/lmFo8hQhiBB+USm4cVr/v2YZ/fUb6dnDCk0yk0S+Ee+QWKQk6HfVdBZGmGIhc9qpU6eU0G3y/SkLIRo1aXJqcKpqTahWDQklBDl/k7bEwtYCLh1UdWoywjKQEc4vIVOCEjqe+uQMHrXoKIZzzczg9HlrtOnPkVVM2aCoVTkClYQR6ldsbC0Q27SmGEf98dWNqiR6+goLI0yxaCaeK60OjSbZIepkTA4NTDMNfHFQsj/qOAhK+kcheYR7N3WdmtjDqhwTjGmw7rX1eCxrpDLc9PtmGPSsh073iTEsHB0d0atXL9G+c+eOSMFBdH1WXavG8vg96DMsjDBFQnlg/vzzT9GmfDBPPPFEmc+U7V11Tpl+o1gYKQw5dxd2ZLVpp3Zi3bqAnVhNhav/xMBxlbq+jO3T1qj/NEcZMpVjqmk12h1WD/yOYnbcR16m/mZ4ZmGEKRIKzaYU8ASFpNaoUfaCXKnX1MKIU2MWRooKkacvGWLNmjUi0ZV7e2dkmakeR/sb7DdiCpzamoSL08/DAhZi+KxHMPp831vXu8UYUYivuZU5ag1RaUfy0vIQu09/ta4sjDCVnlsk5aqmmaZgGQBGVQpBrttEyc8o/46DsyXu1VT5jUjmZoiN0H09CabquBGUjhvTgmD/wLfqmFkkuv3WRfEnYhhtofpvcg24w4cPizpyhNdwtakmbJ0qoZ4+wsII8xDnz58XeWOIVq1aoUOHDmU+SxRJIwsjdoF2sHQoV2FokzLVkCMr0eGHxmi8rycmhfeEh1/BcgiM8RCfLOGJr8xw31zl3H3F2hyHm6xHrz4qmz/DVNRUk5eXh//++0+0PXq5I89O1Q/f2XwfGSn6aaphYYQp0XGVtCLafK2FnMtEfrrqZg+3Ya1IcZCzWUBAgGjv3LkT0dHRaDeoBuq2tOM70ojJzJIw4n0Jp+/Z4N3a7bHVyRGfxU3Hh5++oetdY4zVVGNtjjt1PEXbPi8Xe5fqp6mGhRGmAJS9T85/Qdl1C1dPLo0bR9X+Ium12F+k2AfP3BxPPfWUok2i8gqMcZOXJ+HJzyUcPq8azsyLw7x7T6FFRz+RmZphKgqVYCEzMLF9+3bRtxABo1SmmihnJ0iqUXoHCyNMAahmSlKSqmT5+PHj4eys8mMoK5HXspALlSbFpSkLI9pE1RROhix3JIzhQ9fyh8l3sGNvjhg2l9KBS48CmaH46KOP2FeEqRSoREv//v1FOyYmRhQ5JfpP80Cdrd0xLaQrHn1VlXtE32BhhKk0x9X7iRKW5vpgVNO+eK5+F9R9TKUaZIqmYcOG6Ny5s2hfvHgRZ8+exfn9qZg/+DIW1zmCNR9E8akzEpZND0PTbVfxTehpeOamI//SWCA1CJ06dcKAAQN0vXuMkYf42jlZoElnB50Uf3zzzTfLNC8LI4wCvRCp+jLRvHlz5UVZlq++v3fmoelTEo5eBPLMzBHj5IhmLaz47JaCZnp4cmRNiMpG4MlweCenIu4wh/gaA+s+jUKtf66Ldu2sVPRIWAIk7BDDrBVhqtJvZOsDYURXkMZ3zpw5ZZqXhRGmQo6rdy5nYn7Hczg28zJiVdYduNUA/vrQDA52HKZYGmQKk9M4k99I2yEOSr4R51sJbKoxcHYviYPVLxeV4XPtnLHh6iui3b59ewwePFiHe8cYI76+viIKkjh9+jTu3bv30Mfj6R3JyMrIq/IyB19++WWZ52dhhBFQ4i05xNTW1lbUUCkJuqFXvx+J472PoE5oDAYmRqFtaixG9QQuLTPDqF4siJQFV1dXDB8+XLTv37+PA4d34a6Xixh2y8rE9VNcp8ZQObMzGYnvnhWFyojQVr5YF/eiMp21Ikx1mGq2b9+utDd8Ho3lgUcQM/EY9i+rWs0rBUJQhe2ywsIII1i3bp2SJGfcuHHiJVkct85m4Lc2Qaix4CIc81SVIJOsrPHBRGD95+bwcmdBpLymGlJrWrVR16kJXs+p4Q01qdnVyUEilJK47e+BgFfCERSkcihs3bo1Hn30UR3vJWNqphozCzPUTE8X7Vtrqq5WTW5uLr744gutlmFhhCnSRFMUIgT19XAEDziC2hHqWPXQxl7ofbQrRr2hn17a+s6gQYPg6aly9t20aRN8e6krHccfYb8RQ+PwmgScHnICrtlZYjjStQYm7m6JL776VJmHtSJMVdK5c2e4uak+aij5GZlMiP7PeSDTXPXad7sUg+wqqlVDJmcqBEqU1UGbhREGV65cwaFDh8SZaNq0Kbp27frQWbl6Ig0LWpyB67LLSgrrBGsb5P2vNV440greddUvUEY7rKyslHwu2dnZuJW2TekwnEPj2W/EgLh0OBWxM0/DOUeVzj/G3h5DdrTBiaB9SlbjFi1aYMSIETreU8aYsbCwwCOPPKKUnJCrgzu5WiK6rurDp0ZuDg78mVDlWhESvMsCCyNMAa3I9OnTH3JcDd6dgsuPHkXgXfVX+u0WPhh0qiuGvaaue8BUjqlm5eqluFdL9hvJwrWT7DdiKDTr7oioNj6ifaemKx451BE+9Wzw6adqrciHH34okt4xTHVnYyW8h6n77Bur71VJkdUbN26INiXz6969e5mW4yfCxMnMzFSXsbexUbKCatKqrwPu1VS9HONsbGH+eVvM3N+C66dUIuT9Tl/MxPHjx5HTyFaZFryeTTWGxNRNjREzphEmn24Hr9o22LdvnxIyT5rH0aNH63oXGRPgkUceUT4sNf1G+j3roUTsuV6MQW525SVXpJo4n3/+udZaEYKFERNnw4YNiI9Xveyokqy7u/tDZgH6iuu7tCnCOvrj0bNd8cjznMyssqFOQ1M7EmatcnQkEo6yE6u+EnI+A7sWxRYYZ2NngckLasPWwUIMf/bZZ8q0//3vf6wVYaoFd3d3JVfU5cuXcfv2bdF29rRCVG0PVTsnGwf/SqjUQIirV6+Kdo8ePUQNrrLCwoiJUzjjatB/yVjc8MRDHWyjjg54fntTuNbkRGZVxRNPPKG8qDYc+RIbvGrjw8A2+N6j8UOp4hndc3RDIo4POo6U986KvA1FceDAAfGTM+5SpBrD6CLEd5uGqaaWhqnm6qrKMdXQR+ysWbPK7aTNwogJc+3aNaWjbNqwKaQt3gh/4jh8E5IR/cllJN1XeWAz1YO3t7eIrCFuh9/AuY7uCHL0QEiCJW5G8FXQJ6L/uYu450/BJTsbtvl5OP266muwMIW1IuRYyDC6TA1P9HvOE9kPTDUu5+4hL6fippqNGzfi0qVLok1BEP369dNqeRZGTJhFixaJ//Us6mOW+ZdIWxyiJGjKszBHxDVVaCKjm+J5+fF7lfb+s3wV9AHSUF2ffRPBU8/BIlfVgYd7umD4ZlXGS00OHz6MvXtV17B+/fp4/PHHq31/GdOmVatW8PFROVTTvUjJLQnXWlaICnBHhrkFztm54ugJVT6cimhFNAXv8oSuszBiolABoz+XrsLTdpPwQ42fYBvzwGHSwgwRfepg3PnOIjKAqV4o5FOulHz52Hxl/P5gNtPomryMPJyddh43v7mljPMY44OnT7UXETOF0VRZf/DBB7C0tKy2fWUYggQCOaqGghXImVrG+a0meKJRL3zj3xLrzlTs3ty8eTPOnz8v2h07dsTAgQO1XgcLIyb6dTdz2EJ8YrkM4+0eh4WZSnXs1MwR3XZ1xox1DeHgzB2nLrCzs1P8CjJjDyMgLxkDEyLgs+YK5xvRIWGXMrC89UlhnhGYAY0/bYgOvzUXFVELQxFRlGyKqFOnjpJHhmH0JRvro8NsARvVvbv+IGk3pHK/TyqqFSFYGDExYhIkzOx6DKPPNIB/zgPVnCXQ4L366La7C5xb1dD1Lpo8iqlGysXzEWfwStQV9ImOwOWjqjTOTPVy4t8kHO5/ArViVU6q5g4WaPdnG9R9sU6RnS6pwp999lll+P333xeJ7RhGF/Tv31+5/8iJVXaGd3Y0w8AOqnki7wMnLpdv/STgBAUFiXbbtm0LCD/awMKIiUBS74J/JdQZm4WNUislzvx2DQfUX98FDd6sB3Nrvh30gW7duqFu3bqiHZR1TRl/boNph/ieOnUKb7/9Nk6ePFlt21y/X8IrX2ajRrYqo2qcrS18l3ZErUeKL33wxhtvKCpryiui6QfEMNWNk5OTEmJL4b2UcVtmzIOCpjb5edi+uuiIsOrQihD89jEBgs7noutMCc/NkZCebY171nZY6uGLw+0lPHujKxp2Z22IPkEPs/wCO5++SxnvG22ayc+io6MxZcoUYYueM2eOSMwnJxGrKqiT/XyZhDEfSThh444F3o0Q7u6Mvgc6oUW/4p+X9evXY/78+Ur1a8pGaW1tXaX7yjDlzcY6rJuEtyMv4K+r+9FwyVnk52kXVbNz507xkSA7y8oVyMsDCyNGTPzdHMwfcgVnBx7F2YsaBZHuLYdz18X4YscgWFjyLaCPyJlwb6ZsRpaZKqop71yCSeUbISfrb775RuTn+OOPP5TxVPRr7NixiIqKqpLtpiXn4cnP8vHhYvW5dn/cH08Hd4BvfXVm3MKEhoZi6tSpyvDPP/+M5s2bV8k+MkxlhPi61TBHoGMObKV8uGVl4tiGpDKvk/qiwmUOyqsVIfhNZIRQmNWGz6Oxvc0RBJ64A6+cDDwREwKkXwbO98HA2quwZMHXFbpxmKqFzDSUwTAPebiQpVL5Z93LQtpN4/cboU6OvPPpRf7OO+8gNTVVjHdxcVFS5t+9e1dkDKbCgpVJ+NVMrGx3CtmrVdkq6RH5+lkz/PG+GeweZFQtCtqPCRMmIClJ1ZmPHz8e06ZNq9R9Y5jy0qBBA9SrV08JOZfvU8J1kJfSjt9R9gRoe/bsEY7aBD2rI0eOREVgYcTIuHw0Db+1CoLtD+eVEubkH5KUvBsIaosWAQlYu3YtO9QZAHJ6+Au5KmGEiD9i3KYasmdTTQ1S9968eVOMo6y0zz33HK5fv45du3aJ5HDEsWPH8Morr1Tatk9tTcKBvifgF5+ESTE30SszBhs+N8M7E81KFdwpdFf2ZSFBkjIbs7DP6AtmZmaKdoSq6tJzJNP/RU+R0oFwDIopk/a1KK1IRYs/sjBiJKQl5WLh4zdxffhR1I6KU8afc7bC82nvYsO9F+FVyx1btmxBjRrsI2IIkCmC/A4u5KiFkUubjFMYSUhIwKuvvio0H3JILEGOd2fOnBF+GJ6enuL322+/iaKOBLUXL15c4e3/++09hE8+KVTVRKKNDb792A6P9Shde7h9+3Z89913ok1RC+Qnws8YYyimGs8AG3j0dBPtjDsZSDpbuiMrZe4mDQvRpEmTSin+yMKIEbBzQSzWNj8G3/9uwVpSOSDF29hid5ckvB/aD/cyg2Bvby8EkYCAAF3vLlNG6IVGqs8beTeQ/uDLPOFovFHlG6EqnwsWLBB+IT/99JMYJug+XbNmjUjS1Lp16wLLkMAiO4kSM2fOLHeETVZGHhZOvAmrr8/C9sF5jXBzRq+9ndFhqCr5XElERkYWiJYhH5f27duXa18Ypirp2bOneA/IArRmP+I1XF2r5sioM5jb5yK2/RqDzDQNX8MqLnPAwoiBc/d2FtL+F4ya6SpfglyY4U73QKS8ewc/bB0vxpH6bPXq1WjXrp2O95Ypj6kmH/m4ZK3qFFxysnHxkHH4jdDXFd2TZIKJjY1Vkr6R+pcqf5JmqDhTB52XF198UfHXGDVqFO7d067g177lcfizyXH47lBnVL3d0AsTT7WHf+PiHVVlSHB68sknlX0fNmxYpZqNGKYyIS0r5Rwh6FmRc4MQtYbUgrmdShwwS85BnfORwMfBOLTq4XQChw4dUjK50kcE+UdVBiyMGDhetW2QOKyeUiPDb1Vn1H8pAi+/8Ywyz48//ig6SsbwoM6DfCTO593AHStLJMxsgGbdVF83hkpYWJjIMtu7d2+cO3dOGU+1W6h4I+UqIKGkNL7//nvh5CtrKEh4oUib0khNzMXcbueR8dppeKeonGPpGzFqcH08d6QFHFzKln34888/x/79+0Xbz88PS5cuZT8RxiCzsdp4WKPj2vaimm/WA9+PFEsr9HrStcDyVM19wSsXYGfhofhKVVrxR8lACAkJkfLy8iRT58j6BCkuOrvAuMz0XGndZ1FSbk6edPHiRalGjRrkgSR+L7/8ss72lakc3nrrLcnG3Fkyh6X0888/G+xpTUtLkz766CPJ1tZWuT/p16ZNG+nQoUNlWgf1AZp9wd27dyVfX1+t7ndadn6TE9JWtx3i93u9o9LhtQlaHcu+ffskc3NzsU36f/DgQa2WZxhdcOfOHeVZ6dixY5HzJMfnSP/MjpZWvnHnoWk/NT4qnpmN7julT/12SCvfDpPuhWVVyr6xMGIgxIRnSXP7X5Q2u+2Q5g25XOQ80dHRUmBgoHKzDR8+XMrNza32fWUqlwsXLijXtF27dgZ3evPz86VVq1ZJ/v7+BYQQT09PaeHChVrdo4WFEeL48eOStbW1st5ly5aVup7gPcnSX7X2SiteCZNysrT7yImJiZG8vb2V7c2aNUur5RlGl7Rs2VLct2ZmZtK9e/fKvNz98CzpX7edihAv/2jcvGYnxbN050pGufeLzTSVTGJiIlJSUip1nTH/3UdQnyOoHRQh7Gp+x+/gzM6CHs/p6ekiHJJU4HKNgL/++qvyVGiMzqAYfrqeBEWWXLhwQXG+1HeCg4OF4xyZYMLDw8U4ql77+uuvi1BdysVR0Xu0U6dOmDt3rjJMdWFke3jE9UzM7XkeO+bfL7BM675OGH6tB578MQCWWpRBIKc/8lehrLBEv3798N5771Vo/xlGF6YaUkbs2LGjzMtdux2MD/NWYrNNIuIs1KZMS0gIjI6H24orONftABY0PoHf5iThzj3tEjSyMFKJXLp0Cb6+vvDw8BBOeZSRsaJEbYjGmSeDkRevSu6UaW6B2JEN0bynQwFHOqoKKqfl9ff3F5EzDg7qeRjDZvLkyUr7x/d2YF7rM1g04BL0lZiYGMyYMUM4qMohgMTgwYNx8eJFkdadkphVFiTUyMXpqFT66MdGY/+nV3Cs+xHUuRSNe19eQUZKQeGtPJWpyU+FIhGImjVr4s8//2SBnzGKEN/S+Hr25ziftBy/RU9A2qe34PhrR9zpGohYW9sCAoX//UR8tNYSgWMldJyRj9kryyaUmJF6BAYAvdgDAwMrnFilKiHvfs0vNPriI297+nJq1KiR1uuLWBWJ8y9fVHnXAfAY6AmPd5ugbquCzn30lfnDDz8oRZGOHDmiZKpkjIPk5GQR7pqenIdl7hvhnE+5WYGAdV3Rqo8T9AnSgHTo0KFAdAt53dM9Wt6KnpqaCdL+FdUXUPr4Pn36IPFUIp63fwH1LOsr09IsLOG3oB26jCy/AHTixAl0795dJI2S63IMHDiwAkfDMNVPbm6uEKQpt4+zszPu379fahJM0jTK0Zj0sUsJCeWaS/RMntqSgnPL78H65D0k5lnitXqdlGUtLYCcfaW/t/X3zW5g0AXZuHFjgXGksVi2bJlICkPhT3Ilz7Lw52t3cP5FtSDi/7QfOqxs85AgQsKPLIiQ8LNu3ToWRIw05whp23KkVGywUFXyJePG4XfVYan6AkWZyIIICceUEIxMSxUVREoj9Z6E75v8iO9q/FBAEAlt7oOuR7tVSBAh8yule5cFkXfffZcFEcYgsbS0xKBBg0Sb0sJTJuPSmDVrltKmj2vN4o/0UdBpuDNmrGuIyXd6oN+Odpg11QytG6im91VZmEtHMhD0PZrm6NGjikNbv379pE8//VRydXUt4LAnO5WeOHGixHUtnRFawEHo4juXhRNgYbZs2aJ49NPv999/r8IjZHRNZGSkcNS0MXeV/vTcrdwfp7YnSfpCRESE4kzq5OQkhiuTohxYyQF1+cth0hqNc0K/X2rMlZpYNpH++uuvCm2Tnr3Ro0crz1mXLl2k7OyCEW0MY0isWLFCuZ/ffvvtEuc9e/asMi9FrmVmZpZ5Ozcj8qWzNx5+dxVFuTUj9JVPqthFixYp46iyJuVF6Nu3r8imqGkBIn8K+rLo1q2bsCXLDmDGApUOlyHTDOVKIHXy7NmzhUpMZtOmTcLhjtS7Bw8efGg9X/+Rh9TNkcpwRM/aaPpV44fyF5BjIGlb5Cx6VFBs+vTpVXR0jD7g4+Mjqvlm5SdgrZlay3byA1UNF32AtCBy8boXXnhB+FBVJScuS/ik+zW4/3kFDnkqrYWFkyXih8bileSXcCX3iqikq5nPRFso5bz8fJOfy6pVq7i2E2PQDBo0SHmnlOY3QppOGXrPyKUYykI9XzO0ql/GgqxSOaCvkkmTJklPP/20CM0jKE/AkCFDpPDwcOn+/fvSuHHjpI0bN4ppWVlZYhoNk1T166+/SlOnTjUazQh9OdWuXVtIjpaWllJcXNxD+RUoP4RmPgT516NHD2nHjh3i2D5clCehR57k3CVD+s3rkLRwwvUij5nOsY+Pj7IOOtf6em6YyuXKlSvimluZOUrLa6o1AUc3aJcnoyqgkFc7Ozuxf/Rfm7BBbTUj9+LypGmzVc+Ld8cU6R93Vcjhr93PSTEhGeKZfOaZZ5RnpE6dOg89l2WBvgptbGyU9ch9GsMYOp07d1bu69u3b5eaVsDLy0tKT0+vsv3R3p0cwIYNG0S4oVzam9i2bZuoo0GZCGXtAJUBf+yxx0Q4IjnIUJugLxUKiaOsiUV9OdGXVeHS4JRZUV9rcpBzz+3bqpLjlFWSvp4095XS8NJXInn8L1++XGhL5EgbSq1LVUprdV6Ge1ZPinFJltZI/qIj3pisujya66Kw4UcffRRRUVFiuEuXLliyZMlD8zHGCTmCUjZderZW4zRegKpuS/DHN9FpRFmNs1UDRZpkZGSINt3rFFVW2fdkdmYe1q+3wlf7JcQnq764om3ssblFYzwxxQHPP8gYSVrZX375RfiqUJQZPW+kmaWvwLKGElP/RtpHcoyVHdQpfJ6fM8YYGDx4MI4fPy7aFH35/PPPl6gVeeutt4RWpDz3f1kCTyzL48hFakoyyVB4ngw97LJTDFG/fn3cuqVyrgsJCUGDBg0KvJxJaKHxRQkjlFZ54cKFBcZRqmdKIa2P0LnQrDIq5/ooCjLPkBmLLj45n4bcCsUI3z+w01yd339064MY2dMPYWEFO01yniNTjKxypuiKn3/+WYRRMqYDmWpIGPnv/qcY47kFtXJzUDsyDht/vYW2w8r1fVEp0T6//vqraNOHB734S3oOysPNk3kIfe8e3NNzkVa/FmBuAUfbfLw6KhFP98+DpUUywsIK5t8h5+4RI0YgLi5OlE2n2jHUqZYFmo/S0xPNmjUTHxSVfUwMoyvatGlTQMFQ2MGcImaoWCXh7u4uPprLe//XqVOn1Hm07rnmzZsnEhiRl3zhpFuaeS2oLX8l0f/COS9omJYpiilTpoi8GZqQJoBCivQxtHfPnj3iP9ngnnnmGXh5eZW6DHWKzz/7In7seRotQ5PR5U4wPgpojayQF7H+0CJc2NlQ2OfoPFDnTl961BlScTHC1dVVJKwpT8gwY9hQWGvXrl1x9OhRrJKO4FV0FOPv/5aAwBd1UzH2iy++UDSlVMW2c+fOlbr+a6cycP/Vk/B7oDEdGxuK/Cfq45vnzeHtTuXPVSXQizpXa9euxYABA0R0G1X7Je3lmDFjStweaTBlPxFHR0fR1vygYhhDJyAgQNS9Iv9Niqgh30bNmlBUjVf2+3z77bfRuHHjKt0frYQRqqR5+fJl8ZIsDJUmTktLU4apLR8Y/decJk+XyxkXhsKGNEOHCHohkyCib8IInQ86LwTlICAnw7KqmxcPuCwEEaJJeiL6p87H1rsqh2DKTknmLCrVTOebQrCo1Lp8LiiMmEKGGdOEvtrJLLrn/iyM99qBVHNbrLCpjQZBQL/21fuMkBBCDusEPZ8U+leZz2nkzUycHHMGng8Ekbv29pj0jhv6TynbNij3CJmQ5Iq69MFAmg76FQVpQ+SKwLIDKwv9jLGaapYsWSIUBhRQQcPy+4cqvRNkbp05c2aVv3vNtfWNIDUNqXPIJENqT/qCoJLfpIYhtY4MmWjq1VNVk61bt26BaZQhMSIiQow3piia0aNHl2mZzLQ8LOxxHnWu3hXDuTBDzustsfnsK9i9e7f4cpOh8003gmbKabp5yBzEmC7ku0D+I/nIwTu5q/Bq3U444+SBj5ao/CWqk99//12YQQjSmsrPfWUQfzcH2wYFwTNdpWW95+iAlqt80XdS0ZqQ4njppZeEH5v8IUSCHJmcC0N9E5mD5Y8nElwKa2kZxhizsW7btk1pf/nll4pvyBtvvCG0g1WONt6uGRkZIlJG/r377rsiSiQ5OblANE1sbKw0YcKEAtE0gwcPlv755x/Rnjt3rtFE07Ru3VrxNg4LCyt1/tTEHGlu69NKFARFAWz67u5D8x0+fFics8LRN5988kkVHQljaFAkm+q+MJeceoeJyBL6bT9etrj+yoD6BPKyl+9PqhpdWdCzolldd4X3PulGUFq5+wKKaqMKwfK+Dh069KH1zJw5U5nepEkTKTU1tdKOh2H0jaSkJMnKykqJOKMotJs3b0oWFhZinJubm3i/VwcVSnr28ccfK6G9xJIlS6S+fftKvXv3ln788ccCibqokxo/frzUtWtXadq0aVJUVJTBCyO3bt1SOq4OHTqUOj+VZqbqhnLnusH9P2n7vJgSlzl9+rQ0cuRIydHRUXrttdeKTH7GmCYFBAGPMYow0n5abrU9K/PmzVOeAbpPKwtKZPZr+yDlWVldc490dm9ykUnPtCE0NFRyd3dX9vmjjz5Spq1bt04Zb2trK8IaGcbY6du3r3LfU+oAUhTooiI1Z2CtAN98841y0b7++usS542/ly3Nb3xc6VzXe+ySdi+JrcjmGUb68ssvH9yDZpL7gDCpWdtY6Su/E9K/3z6sbatsKAtpYGCg8gyQ4FwZkKAxt98FjWflP+nQmnhlWkU/THbv3l0gczFpbGmdzs7OyrgFCxZUyrEwjL4zZ84c5b5/6aWXRK4satPzkJiYWG37oV/eoAbsLzJq1KgS5137QigCYlQ26nQLS3j83A79prhX+T4yxg3Vq1HZcyV4n/0a39w+jZbpCbg/9ybycqs278xff/2lhPpR2J9cSKuiZGdIQFyW4k9l90lrdB+ryh9SGVCOI8r1oxkqTc8vOYkT5DPC2YwZU2GIRkgv5eaR6y+9+uqropBedcHCSDkhB1yq4klQhdzSwv6eWlIPt/3ckWphCd8F7dDz8crrXBnThUK8qbwCcfH+fIQ4qMp5eyen4tB8ddXcyobCZL/66itl+IMPPqi0dds6WGDq0daiwF3Wi80x+AVPVDbklEcJzeREgmfPnhVtcqonh9zC5RcYxlhp1KjRQ8EklLpDjj6rLlgYKSeaFXrLEkVj52SBpw+0RuM1nSpUPZRhCkNfMFSJk1idq9bWmf91C1Je1UTWUJIkOSFYz549RVh7ZWJjZ4EXDrTA2E/LFiqvLSRsLF68uECFawqZp3DG6vwaZBhdY2Zm9lDCs5dffll86FQnLIxUUUjv7YsZuHqiYG4VRxdLtOxdDSFSjElByQAppJY4Ev0LMgJUyQRTr6chan3lF6QkXzNKclaZWpE9S+NwM7joJIhVBSVe/Oeff5QkhZStlYp/Mowph/g6ODjgtddeq/Z9YGGkHFD6daopQ1Cuh8LJk26cSceBR07h1KjT1d7BMqaJZorz3+7PV9o3vrmJ/JzK9R2h+i5ySYL27duL7KYV4ci6RCS9HYwTQ04ieHcKqhNST1+5ckXkRaIMxwxjivTu3Vt5j33yySci/Xt1w8JIOfj333+VhDDk+KZpX067lYagkafgmZEB98xM7Jp0ufKuFsMUA5kb5OyJuyN3Ibdhjminh2YgeH5klWpFKuJfkXI9FdEvBcE2Pw+u2Vk4OktVcLI6ocKWxpCAkWHKC9WLO3LkiMgo/uabb0IXsDBSiSaahFOJOD7sFJzSMsXwPQd7DP6r6JTTDFOV2pFFSepCk5e/DkFGSl6lbGPfvn1KpU+q3E2ZYMtLRmQmTo05A/tsleB0p5YrJm/iEgcMowvIV0qXJUZYGNGShIQEpTAeFeGicEb6WgyZexvHHz2JrHuqkETbBo4YsLsDajdXFx5imKpWtZLZhNh8ZRNu1Kwh2u5ZmVj3QUSlbENTK/L++++Xu15Fdnw2To05jcxIleDu0NwJ4/a2gYOzbqoOMwyjW1gY0RIq3S7HYZOJJuZONhZ3DMLVj65BylVFLrh2ckH3rR3g11AVZskw1QGZS6i6psw+183i/52aLgjsohJMKgJV9ty7d69o169fX+TjKA/JcTk4OSFIONgS9nXs0HltO7h5WVV4HxmGMUxYGClHSKNMc/cJ2NXlOHxCYpVxdV+pg07/doC1e8GqwwxTHZCALPs//HvsK6R+6oUZlzpUSl4bTa3Iu+++CwsLC63XkZWRh5V9ziH5jCrBmE0ta3Rc1x42NW0qvH8MwxguLIxoWSp9586d9A0Kp8afYOn6ALhlqdTMKZZW8PqlDRp/1BDmVnxaGd1AAgIl9JL55+jsSin9TUnBKIpGDiWmrKXaQhlhF/W/iMBIVYXfTCtLtF/TDva17Su8fwzDGDb81tQCKrGcmWsPNP0XKZ4f4rBjTfzr5o9wTxd03N0FbZ+oWXVXimHKyOTJk+Hh4SHaa9aswe3bFY9QoZLiMmQKsrbWTvNHflVvzpNwMlblQ5VlZg7Xb9vAuXnFzUcMwxg+LIxowZrFN4A2ZwB3dYIYz9cbYsrZ9qjTgh1VGf3A3t4eL730kpK2nZJ5USj69rn3Mb/5KcRFZWu1vqtXr2LdunWiXatWLUydOlXrfZq9EvhxnRmW16qPhd4NYfleS/R5yk3r9TAMY5ywMFJG9fLCSTcw6XQH9M9Q2ck9XSTs+M4Mnz9vCWtb7W3nDFOVUAIvEkqIRYsWYcHj1yB9FITA6HhseOOOVuv6+uuvhWaDeP3112Fnp53gvWiLhPd+V6elHza7Noa9UUurdTAMY9ywMFIK0SFZWNAuCL5bQmABCc9HX0UrXMTZJeYY1JGLaTH6CWVQfOaZZ0Q7PT0dER4HkQfV/eq6J0xEgZWF0NBQ/Pnnn6rlXF3x/PPPa7Uf/865h58+jVeGv37WDM8M5eeGYZiCsDBSAvtXxmNvt2OoHaFyuKOcqxutwvHZ6xHw8eAOldFvSIshO68uXPshwlp6i7Z9Xi42vhZapnV88803wtQjF8+iap5lZe+yOEhfncdnoUHolByD18cBbz9RrkNhGMbIYWGkGLPM4kkhSHn5tEhRTSRaWOLD/LXYlP4aBg3uV93XiWG0pk6dOkoukPv37yOjx3nkPEjd7nkwHJE3Vfd2cURFRWHJkiWi7ejoKISRsnJqaxLi3zoLaykfNlI+nqxxH9/ONKtQ6niGYYwXFkYKEXUrC7+3DYL3lhvCLEPccnPES0kv4mziYjz66KOwseGcCIzhpYj/fdUniGznK9pUC2ZTKdqROXPmIDtbZc6ZOXMm3NxKdjilStWr3o7A3E5nETb5lNDAiPF+Hpi+synMzVkQYRimaDj3sgYnNyfhxoxgBD7QhpBZJrp/XZyvMQfxi64qSaUYxlBo27Yt+vXrJ0oY3Lx5E7YvhyLrjI3QVngdC0fYpUAENnvYITU2Nha//fabUkSLTD7FJTFbOu4GrC7EwTslFc5U40Jjeri7M57a3wo2duzkzTBM8bBmRAO/pur07UlW1rCZ3Q7P/FUXmzZtFOMoiuCRRx4p4XQyjP6hmSL+txWf4W4XP9EmgWTrG0VrR3788Ufh+EpMmzZNhPRSeHBhx1cSMuyCY4QgokmahSVCm/lg1N62cHLlbx6GYUqGhRENfOrZwPe7lgjzcUf3/V0wYJoHDh8+jJiYGDGdSrQ7ODiUckoZRr8YMGAAWrVqJdqnTp2CzxNxyDRXaSp8T0fgZrBK6JBJSkrCr7/+KtrOls6Y3vpZzOt3ESv9DmFTr1MPrT+tqbvQIka41kBEvzpw+KUDRtzpjRcOtoCnH5dFYBimdEz6k2Xf8jg07OoA3/pqjUjviW7o+biLEoWgWYtm9OjROtlPhqkI5DRKviNPPvmkGF648msM6zkH/vtv46yDG/avycMPbVTz5mbn4+e31mBI1lC0dWqHxtZNEPF2JGrLK8sCwq9mwr+x+pkZ8n1d2DrWh1dt9qViGKZ8mElyNiM9h/IdBAYGVkqdjYTLqVj1+h34nwpHhI87ZgS3hYXlw+sltTRtMyIiAlZWViIiwdlZ0yLOMIZBTk6OqLR7544q4dnBXefx2ie+OGPuAqp399PjWcDia/C4HQ+n3Jwi15FtZo5oLxd0+bkxWvcte4hvZULPZFhYWKX1BQzD6Acm8zTn5+Qj+t+7ODHiFI71OILap8JBiurAqDis+yS6yGVIpU2CiKzqZkGEMVRImNZ0Ql385xwMn6aq5EtpRN5cZgG/WzEPCSIODRxQ+9kANP6jLfrd6IPnL3bQmSDCMIzxYvTCCNnDV0y8jn0tDyD4mXOIO6zOBknFuqIG18foj1TJoAqzfv16pc0mGsbQoZoylEWV+OuvvzC2axTcHtSpy7SwxBU7F6SaW+CwTQ5+zlkDnzW10Ot4dzT9sgnqDvNkR1SGYaoMo/QZyc+XsOO4hJCXziHwdgzcVaZuBYd69vB+yh8uI3xQM6BoBzuyXsnCCJVlHz58eDXtPcNUDZS4jPKFfPHFF8Jss2Thj/jni28w7x8JDf2B1OuReHz2eOQjByNGjEDrfq35UjAMUy0Ylc/I/UQJS7YCCzZJCI0G3gs/h+7JqkiYfDMz+DxaEwFT/OHe063UTJDnzp1D69aqzrhv374iTwPDGDr37t0Tz1FWVpZI7R4eHi7Mj7m5uWjYsKF4zoiTJ0+iQ4cO0DfYZ4RhjBODN9NQ50Q1ZH7qdRG1R+bh3QUqQYTY6uqPBGsbRA6qhxYHeqDtH63h0cu9TCmp2UTDGCOUL2Ty5MminZKSggULFoj2qlWrFEFk4MCBeimIMAxjvBisZiT+bg62fhmF7E0RSsKlb3yb44CLyv9jYAfg+RHAkI4SrG21z/7YrFkzXL58WQgukZGR8PYu2q+EYQyNGzduoFGjRsIUSff1rVu30K5dO1y5ckVMP3DgAHr27Al9hDUjDGOcGJzPyKltyTj1/R14nbsL93xVNVGZgel30eE5bzw73Az1/cpfB+Pq1atCECG6du3KgghjVDRo0AAjR44UOXSio6MxYcIERRDp3r273goiDMMYLwYjjOz5MQt520/CPy5JnYBJo/6Fyzh/vPJWLTg4V9zypJnojGvRMMaaIl6+zzdt2qSM/+CDD3S4VwzDmCoGY6bZ5r6zwDCls77bygsdXw9A+yEP4hMrCVJZBwUFKeah2rULiz8MY/j06tULBw8eLHDfU26dsvhU6Qo20zCMcWIwmhGqfUE6j2gnR1gP98PQ933g5mVV6dsh4UMWRKhzZkGEMVYoRbymMEJaEX0WRBiGMV4MRhi51M0FHcfWx5SJrlWaBppr0TCmwpAhQ4TAfebMGbRt21bkFmEYhtEFBhPa+/m+/sipdabK61GwMMKYCvQs7dixA8uWLcPOnTu51gvDMDrDYHxGSH1saWmJhQsXKnkSKpuoqCj4+voqob0XL16sku0wDFM+2GeEYYwTg9GMEJQlcsqUKfj4449FjoTKZuPGjUqba9EwDMMwTPVgMMLI008/rbQ/++wzoR3Jzs6u1G1w1lWGYRiGqX4MxkwTEhKCf/75B2+++aaiFenTp4/w8XBxcanw+mNjY0WqbFID169fH9evX+fIAobRM9hMwzDGicFoRshn5NVXX8XatWtha2srxu3btw/dunVDWFhYhdf/77//io5OTnTGIY4MwzAMUz0YjDCi6cuxd+9eeHh4iGFK2965c2cRnlgR2ETDMAzDMLrB4IQRokuXLjh+/LiosUHcvXtX1NPYsmVLudaXmJiI3bt3i7a/vz9XLGUYhmEYfRZGvvjiCwwaNEikkh4/frySwXHz5s3o1KkTevToofxISJC5dOmSKMhFZpUZM2aIAl0VoV69ejh27JhYH5Geni6SNs2bN0/rdW3duhU5OTmizSYahmEYhtFzYWTixIlC8KAy4x999BE+/PBDoVkgKJvjoUOHlJ+Xl5cYT1EvVJiLhBEysbRq1UosV1Hc3d2FRmPcuHFimHw+XnjhBZHmWvb/KAuaJhoujMcwDMMwei6MUK0Wa2tr0SYnT8r9cf/+/RKXIX8OKysrPPbYY7CxscHUqVNFyfLIyEhUFHJmXbVqFd555x1l3HfffSe0NhkZGaUun5aWJrJQEjVr1lQ0LQzDMAzD6HFtmq+//lpoR7KyssTLm0Jhr169igsXLqBfv35wc3MTwsCYMWOUsFzZv0MWIPz8/MR4OeOpJqRJKZxDhMwoJWk7vvzySwQGBuLFF18U861bt05kVKVEZrKza3EmGlloIWGJBCxttCoMw1Qf8rPJzyjDGA5lKeNSLmHk3XffFaYQ0njcunVLvMCp0Nbff/8tTDMU4UL5QFxdXYVwQi97BweHAuugYfLzKIqlS5eKtO+ajB07VjHHFMcjjzwilnvppZfEuo8ePYqOHTtiyZIlqFOnTpHL/Pnnn0q7ssKEGYapWsLDw/kUM4yBUNz7t1Kq9lpYWIgXPZlIKAKle/fuyrTmzZsL/xDKA0LCiJ2dnTCHaELD9vb2Ra6bUr6Tb4ompOWg7ZQmYVFmVvJJGTZsmHCSJeGChBhKmNa1a9cC85JmZ//+/aJNghNpc8icxDCMfkIaERJEytIXMAxjOJRbGJHJy8tDRETEQ+NJWyJnSq1bt64wm8hkZmaKZWh8UZBPiuyXIkNCAnU+ZemAyJGWQn+HDh0qit3FxcWhf//+WLFihdCwyOzZswcpKSmiPXz4cOHPwjCM/lPWvoBhGMNAq6c5NTVVOHuSCYQcVymS5fTp02jTpo0wiSQkJIj5yH+ETDaU+0MWDkgLQVlOyReEzCZNmjQp0l+ksggICMDhw4eFEELQ9klDQs6tspDEic4YhmEYxsBq05Aw8sYbb+DatWvihU6q0meeeQZ9+/bFDz/8gG3btgn/EIpKoRc/mWo084zMmjVLqFibNm0qit15e3uXeUdDQ0OFg6q2X0Mk/Dz77LP4448/lHEzZ87EnDlzhDAUHx8PR0dHEREkp5lnGEY/4do0DGOcGEyhvPIKIwQd4ueffy7yosi0aNFCRP8Q5CuyevXqSt1fhmEqHxZGGMY4MQmjK/mvUJK15cuXKw6qsiAi17thGIZhGEY3mIQwIvPUU08JnxdnZ2dlHJlmBg8erNP9YhiGYRhTxqSEEYL8W44cOSJMPsTTTz8tfEYYhmEYhjHQ0F5DpFmzZiIx29mzZ9G+fXtd7w7DMAzDmDQmKYwQlHCtcBI0hmEYhmGqH5Mz0zAMwzAMo1+wMMIwDMMwjE5hYYRhGIZhGJ3CwgjDMAzDMDqFhRGGYRiGYXQKCyMMwzAMw+gUFkYYhmEYhtEpLIwwDMMwDKNTWBhhGIZhGEansDDCMAzDMIxOYWGEYRiGYRidwsIIwzAMwzA6hYURhmEYhmF0CgsjDMMwDMPoFDNJkiTd7gLDMAzDMKYMa0YYhmEYhtEpLIwwDMMwDKNTWBhhGIZhGEansDDCMAzDMIxOYWGEYRiGYRidwsIIwzAMwzA6hYURxmCJiopCp06ddL0bDMPoEO4HjAMWRvSMUaNGYeLEiTB1hg0bhrNnz8LUWLt2LUaPHo1u3bqJc7Bw4ULk5eWVuMzmzZsxc+bMattHpurhfsC0+wFT7Assdb0DjJqLFy8iNjYW2dnZCA0NRZ06dbQ6PZS/jn7m5ixjGiJLly4VHdDnn3+Oli1bIiQkBP/73/9w//59vP/++7rePaaa4H6AWWqCfQG/tfSI7du3o1evXsL0sG3bNmV8+/btsXr1agwdOhSDBg3C8uXLlWmffPIJZs+ejeeeew7du3dHREQEjAk6vkWLFhmF5F8Sqamp4jjfeecdtG3bFpaWlmjYsCFmzZqFf/75B2FhYUhISMAHH3yAAQMGoF+/fvjll1/E9f7qq69w5swZ9OjRA+PGjdP1oTAVhPsB0+0HTLkv0BthxJTVcURubi527dolbq6BAwdix44dQsshc/jwYfz9999YsGABVq5ciZMnTyrT/vvvP7zyyis4cOAAfHx8dHQETEU4f/68uAdIoNSkUaNG8PLywunTp8WXka2treiQtm7dKgRXPz8/vPfee2jXrh0OHTqENWvWGPyFMOW+gPsB5ryJ9gV6I4yYOsePH0dOTg66dOmC3r17Iz4+HsHBwcr0yZMnw9HREbVr18aIESOE4CLTt29fNGnSREjQ9GMMj8TERLi4uMDCwuKhaW5ubmI6ffG8+eabcHBwEB0RqW8Z44L7ASbRRPsCS320l37zzTdCFeXk5IQnn3wSEyZMENNIKxAeHi5e2seOHRM+FV9++SV8fX1hDKpZEkKsrKzEr2vXrmIcqekIkohlatWqhRs3bhQYZgwbZ2dn0cmQg1rhTogEUxpHHZGdnR1MBVPsC7gfYJxNtC/QO80IfdmTg86+fftERzR//nxcvXpVmU7jx44di7179yIwMBC///47DJ309HRhYqFjIp8Q+p04cQJ79uwRzqzE3bt3lfnv3bsHDw8PmAL0wGVlZSnDcXFxMEboy4bufTLHaXLt2jVER0ejRYsWwk6cmZn50LJmZmYwRkytL+B+oHhMpR8w5b5A74SRxo0bix9FhDRt2lSENZ07d06Z3rFjR+HQSReLfCs0NQSGCnWmNWrUwPr164U/CP3WrVsnJGD5hiSnVXJsun37NjZt2oT+/fvDFGjQoAGOHDkijp0ctOjYjRH68p8yZYpwRg4KChI2Y7q3P/zwQwwfPlzYgUlLNmfOHPHSoo7owoULYllXV1choNIyxoSp9QXcDxSPqfQDptwX6J2Z5tatW+IkX79+XahgSTNAfhIypJ6SIVsZXQxDh1Sz5AdSWNtBNx5NI8hsM378eHFOnnjiCZNJ9jVkyBChhqdIIroPSGuk+UIyJqZNmyY6IgrnI00Y3evkzDl16lQxncaThoDG0RfQyJEjxVdShw4dhOMyOT+TyY4ir4wBU+sLuB8oHlPqB0y2L5D0hEcffVQKDg6WZsyYIc2fP1/KyMgQ49977z3pt99+E236/9lnnynLnDp1ShoxYoRk7LRr1066e/euZEr07dtXCg0N1fVuMDqA+4Ki4X6AMWb0zkxDXzcUNWJjYyOiSUg1x5gWFLpGYc3e3t663hVGh3BfYNpwP2Ba6J2Z5qWXXsIXX3whnNHIFNGzZ09d7xJTjdC1p/BGclwkgZQxXbgvMF24HzA9zEg9Aj2AssgtXry4gE2YYRjTg/sChjE99MJMw+o4hmG4L2AY00XnZhpWxzEMw30Bw5g2emOmYRiGYRjGNNELMw3DMAzDMKYLCyMMwzAMw5iWMEJpzidOnCjCdqnYlQxZi2iYMuxRwTjKMEdZF2VmzJghspD26NFD/F5++WVlGtUsoGx0lJWPPPHnzp1b3YfFMEw19QXEsmXLxHQK/aeMxGlpacq0P/74Q5RLoGrWP/30k1gfwzD6TbULI5TynAQL6ig02bx5sygMt3TpUmzdulUUQlq4cGGBef73v//h0KFD4vfzzz8X6Hxu3ryJtWvXih8Vmfvnn3+q7ZgYhqm+vmDNmjUiNTilAqACk59++qmodE1QLSfqA6hPoPmOHj2Kf//9ly8Pw+g51S6M0JdOr169RN59TagTGTVqFGrWrAkHBwdMmjQJW7ZsKdM6aVn6wqJic5TD//HHHxcdGsMw+kt5+gIqq75kyRLxYeLl5SXqclARNWtrazF927Ztok6Hn5+fEHaefPJJMY5hGP1Gr3xGCqtTY2JiRJVGme+//16oX2fOnPlQhU7NZakdEhJSDXvMMEx19gX0n6qU7t69W1TqJaFl48aNynyhoaFCOJGpX7++KLjHMIx+ozfCCPmDrF+/HtHR0UhJSREqWiIjI0P8Jx8RKhtNX0hkY6Zh2U7cpUsXrFy5EomJiYiNjRWVCuXlGIYxLErqC2Sh5M6dO6I/oDLr5CNGdazkejakTZGhNvcFDKP/6I0wMnz4cFH2mGzI48ePR8eOHWFpaamUCW/evDns7e1FqXBS21L7woULYtozzzwjvoDIkY1KLPfp00eUT2YYxvAoqS+Q6xVNnz5d9AWkBSENiVxQk/oFTWdWatvZ2ensWBiGKRt6I4yYm5vj2WefFb4eZOOtV68eGjduDAsLi2Lnl6FO6Z133hHLkbOas7MzmjZtWo17zzBMdfQFgYGBwlmVfEVkNNt16tQRzuwyZKKh5RmG0W+qXRjJzc0Vobj5+fnCGY3a9J9MLBEREcJWTB3IDz/8IL5+CFLVUiXX7OxsEeJHJpnk5GShLSHu3bsnzDO0zvPnzwu1LmlIGIbRX8rTF5CWQy6kR/0B+Yjs2rUL3bp1E9OHDBmCDRs2iOUpCof6ChrHMIx+U+3p4Cl/QOGQ3Y8//lgIFq+99hru378PT09PIUwMGzZMTE9ISBA+ImFhYUJd27BhQ7z66qvia0kutEfroE6MvOip9Hj37t2r87AYhqmGvkD+OPnss89ECL+LiwsmT54sHFll6GPkzz//FELOY489JvoOTe0JwzD6B9emYRiGYRhGp+iNzwjDMAzDMKYJCyMMwzAMw+gUFkYYhmEYhtEpLIwwDMMwDKNTWBhhGIZhGEansDDCMAzDMIxOYWGEYRiGYRidwsIIwzAGTfv27cWP0sczDGOYsDDCMEypUNE6+aX/+OOPF5hGmY8pHbs8/Zdffqn0M0qChrx+hmGMDxZGGIbRihs3biAoKEgZ/ueff0RdGYZhmPLCwgjDMGWGakMRf//9t/hPhe3WrVunjNckKSkJs2fPxtChQ9GpUycMHDgQH374Ie7evVugPg1pO6j2zO7duzF69GhRV4oK492+fVvM88knn+DTTz9VlpE1JLSsJqmpqWK+Xr16YfDgwVi0aBFfWYYxEFgYYRimzFCRSl9fX+zfv19Uyz548KAQLqiSriakKSHTztq1a0VF7cDAQKSlpWH79u2YMmWKKH6pSUxMDP73v/+Jgna0bHBwsCiGR1DxS9qmDBXSo1+tWrUKrOPXX3/FsWPHYGVlJYrs/fbbb6LaN8Mw+g8LIwzDlL3DMDfH2LFjFY2IrCEZP358gfl27tyJW7duiTZpR9asWYPFixeL5UlQoGFNaH3ffPONWKfsk3L+/HlkZmZi2rRp4ifzxx9/iB9V5NWkUaNGwrdEU1Nz6tQpvroMYwCwMMIwjFaMGDECdnZ2QqA4ffo0mjRpgpYtWxaY5/Lly+K/ra0tevfuLdqNGzcWGhLN6TKOjo7o2bOnaNetW1cZX1iDUhL9+/cXWhEXFxe4ubmJcfHx8Xx1GcYAYGGEYRitcHJyEj4ZZHYpSitS3nXKWFhYKG1Jkiq0Dm2WZ/7fvh3iKAxEYQCeNZBgGgJ4RGtQ3IIbcA4cd8FUcQxugcBW9AQVOJZ0kiXZZZOFNS9pvs9Mk5Fj/rz3F+III8DbttttPqfTaS6m/rRarfLZr1n6fknvcrmkpmm+3b+qn7B8uV6vXgwG5rkCD/CHsizT6XTKE4jRaPR0v9ls0vF4zL2R/X6f1zNt26bb7ZYWi8UjzLxquVw+vvvOynw+T7vdLq3Xa28FA2AyAvxLURS56/Gb8XicDofDIzj0E5HJZJLXO3Vd54nKO6qqyiXW2WyW/945n8+p6zovBwPx8WmpCgAEMhkBAEIJIwBAKGEEAAgljAAAoYQRACCUMAIAhBJGAIBQwggAEEoYAQBCCSMAQChhBAAIJYwAACnSHapwbdLRFHzUAAAAAElFTkSuQmCC", + "image/png": 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", "text/plain": [ "
" ] @@ -316,63 +316,19 @@ "metadata": {}, "source": [ "# 2. Partial fine-tuning with layer freezing\n", - "With this method, top layers of the model will be frozen. That means that their weights won't be updated during the fine-tuning. \n", - "\n", - "This is done with the `LayerFreezeCallback` available in darts. \n", - "\n", - "
\n", - "LayerFreezeCallback\n", - "\n", - "\n", - "Here is the source code of the callback method.\n", - "\n", - "It extends the `ModelTransformCallback` which applies a transform function to the model attribute (by default `model`) on the setup callback of `pytorch_lightning`.\n", - "\n", - " ```python\n", - "class LayerFreezeCallback(ModelTransformCallback):\n", - " @classmethod\n", - " def _freeze_layers(\n", - " cls, model: nn.Module, freeze_patterns: list[str], unfreeze_patterns: list[str]\n", - " ) -> nn.Module:\n", - " for name, param in model.named_parameters():\n", - " if any(name.startswith(layer) for layer in freeze_patterns):\n", - " param.requires_grad = False\n", - " if any(name.startswith(layer) for layer in unfreeze_patterns):\n", - " param.requires_grad = True\n", - " return model\n", - "\n", - " def __init__(\n", - " self,\n", - " freeze_patterns: list[str],\n", - " unfreeze_patterns: list[str] = None,\n", - " model_attribute: str = \"model\",\n", - " verbose: bool = False,\n", - " ):\n", - " unfreeze_patterns = unfreeze_patterns or []\n", - "\n", - " super().__init__(\n", - " transform_fn=partial(\n", - " self._freeze_layers,\n", - " freeze_patterns=freeze_patterns,\n", - " unfreeze_patterns=unfreeze_patterns,\n", - " ),\n", - " model_attribute=model_attribute,\n", - " verbose=verbose,\n", - " )\n", - "```\n", - "
" + "With this method, top layers of the model will be frozen. That means that their weights won't be updated during the fine-tuning. " ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 6, "id": "33fa7fc4", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5f830deafaf54b249882fcad5c672577", + "model_id": "1a38e2f67955406d8c399db728eb96e2", "version_major": 2, "version_minor": 0 }, @@ -385,19 +341,14 @@ } ], "source": [ - "from darts.models.forecasting.foundation_model import LayerFreezeCallback\n", - "\n", - "freeze_callback = LayerFreezeCallback(\n", - " freeze_patterns=[\"encoder.block.0\", \"encoder.block.1\", \"encoder.block.2\"],\n", - " unfreeze_patterns=[\"output_patch_embedding\"],\n", - ")\n", - "\n", "partial_finetuned_model = Chronos2Model(\n", " input_chunk_length=12,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=50,\n", - " pl_trainer_kwargs={\"accelerator\": \"gpu\", \"callbacks\": [freeze_callback]},\n", + " freeze_patterns=[\"encoder.block.0\", \"encoder.block.1\", \"encoder.block.2\"],\n", + " unfreeze_patterns=[\"output_patch_embedding\"],\n", + " n_epochs=100,\n", + " pl_trainer_kwargs={\"accelerator\": \"gpu\"},\n", ")\n", "partial_finetuned_model.fit(train_passengers, verbose=True)\n", "partial_finetuned_model.save(\"partial_finetuned.pt\")\n", @@ -408,14 +359,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 7, "id": "50830283", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3f92740814334e009f614fb2668b88c2", + "model_id": "0c6375a46aa043aba1397eb195e2b3fe", "version_major": 2, "version_minor": 0 }, @@ -429,7 +380,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "be8c720307a84928a25298ca935b3992", + "model_id": "5117f22a8ec94ad5842ea8709e74fd4d", "version_major": 2, "version_minor": 0 }, @@ -446,13 +397,13 @@ "" ] }, - "execution_count": 10, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -527,14 +478,14 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "id": "6981052c", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f747f8932c964382b4e2c45025fac6ec", + "model_id": "cd7cd86f70dc4759ab3ed10c73fd7afe", "version_major": 2, "version_minor": 0 }, @@ -548,10 +499,10 @@ { "data": { "text/plain": [ - "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=50, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=50, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" ] }, - "execution_count": 12, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -559,7 +510,7 @@ "source": [ "from peft import LoraConfig\n", "\n", - "from darts.models.forecasting.foundation_model import PeftCallback\n", + "from darts.utils.callbacks.fine_tuning import PeftCallback\n", "\n", "lora_config = LoraConfig(\n", " r=8,\n", @@ -578,7 +529,7 @@ " input_chunk_length=24,\n", " output_chunk_length=6,\n", " enable_finetuning=True,\n", - " n_epochs=50,\n", + " n_epochs=100,\n", " pl_trainer_kwargs={\"accelerator\": \"gpu\", \"callbacks\": [peft_callback]},\n", ")\n", "model_lora.fit(train_passengers, verbose=True)" @@ -595,7 +546,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 9, "id": "49b2c2e8", "metadata": {}, "outputs": [], @@ -607,14 +558,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 10, "id": "41e8a82f", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9423ea48aac342ea9600ae6f45f168ae", + "model_id": "80fe22ec79024e3e8d10bc5165d2f93e", "version_major": 2, "version_minor": 0 }, @@ -628,7 +579,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "01bbd79720504a9db991aed2291c721e", + "model_id": "1588da65b96e44559a7b0086ac5b3796", "version_major": 2, "version_minor": 0 }, @@ -645,13 +596,13 @@ "" ] }, - "execution_count": 14, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -690,7 +641,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 11, "id": "9a96ca55", "metadata": {}, "outputs": [ @@ -700,7 +651,7 @@ "True" ] }, - "execution_count": 15, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -722,7 +673,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 12, "id": "ce2fcd82", "metadata": {}, "outputs": [], @@ -740,7 +691,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "630bb5bc", "metadata": {}, "outputs": [], @@ -761,14 +712,14 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 14, "id": "c1fddf83", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "73a4c844302a4b458ad0780a7e2898f4", + "model_id": "1be22001384a4a0f98955ab22636d9e8", "version_major": 2, "version_minor": 0 }, @@ -782,7 +733,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e339655a9712423887f374b85505eb00", + "model_id": "98511c12d7914f8987a18451fb44a40c", "version_major": 2, "version_minor": 0 }, @@ -799,13 +750,13 @@ "" ] }, - "execution_count": 20, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] From 8f7ef24cd1ff8cf9818ebc6bcf959943c58c6a35 Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 30 Jan 2026 17:05:55 +0100 Subject: [PATCH 08/11] test: add unit tests for fine-tuning --- .../models/forecasting/test_foundation.py | 153 ++++++++++++++++++ 1 file changed, 153 insertions(+) diff --git a/darts/tests/models/forecasting/test_foundation.py b/darts/tests/models/forecasting/test_foundation.py index 0e2d55625d..e3b74b127d 100644 --- a/darts/tests/models/forecasting/test_foundation.py +++ b/darts/tests/models/forecasting/test_foundation.py @@ -1,10 +1,12 @@ import logging +import os import shutil from pathlib import Path from unittest.mock import patch import numpy as np import pytest +import torch from darts import TimeSeries, concatenate from darts.tests.conftest import TORCH_AVAILABLE, tfm_kwargs @@ -17,6 +19,7 @@ ) from darts.models import Chronos2Model +from darts.utils.callbacks.fine_tuning import LayerFreezeCallback, PeftCallback def generate_series(n_variables: int, length: int, prefix: str): @@ -180,3 +183,153 @@ def test_local_dir(self, mock_method, caplog): ) config_path.rmdir() test_local_dir.rmdir() + + @patch( + "darts.models.components.huggingface_connector.hf_hub_download", + side_effect=mock_download, + ) + def test_full_finetuning(self, mock_method, tmpdir): + # 1. Training activation + model = Chronos2Model( + input_chunk_length=12, + output_chunk_length=6, + enable_finetuning=True, + n_epochs=1, + **tfm_kwargs, + ) + assert model._requires_training is True + + # Capture initial weights + model.fit(self.series) + initial_params = { + n: p.clone() for n, p in model.internal_model.named_parameters() + } + + # 2. Weight update + # We need to actually train for 1 epoch. tfm_kwargs usually has "accelerator": "cpu" + model.fit(self.series, epochs=1) + + # Check if at least some weights changed + any_changed = False + for n, p in model.internal_model.named_parameters(): + if not torch.equal(initial_params[n], p): + any_changed = True + break + assert any_changed, "The weights should be updated after fine-tuning" + + # 3. Persistence (Save/Load) + save_path = os.path.join(tmpdir, "model.pt") + model.save(save_path) + loaded_model = Chronos2Model.load(save_path) + + pred_orig = model.predict(n=6, series=self.series) + pred_loaded = loaded_model.predict(n=6, series=self.series) + assert np.allclose(pred_orig.values(), pred_loaded.values()), ( + "Prediction of the fine-tuned model and the saved/loaded fine-tuned model should be the same" + ) + + @patch( + "darts.models.components.huggingface_connector.hf_hub_download", + side_effect=mock_download, + ) + def test_partial_finetuning(self, mock_method): + # 1. Callback injection + model = Chronos2Model( + input_chunk_length=12, + output_chunk_length=6, + enable_finetuning=True, + freeze_patterns=["encoder.block.0"], + unfreeze_patterns=["encoder.block.0.layer.0"], # Example unfreeze + **tfm_kwargs, + ) + assert any( + isinstance(c, LayerFreezeCallback) + for c in model.trainer_params["callbacks"] + ) + + # 2. Freezing logic + # We call fit to initialize the model and trigger the callback setup automatically + model.fit(self.series, epochs=1) + + # Check requires_grad status. + found_any = False + for name, param in model.internal_model.named_parameters(): + if name.startswith("encoder.block.0"): + found_any = True + if name.startswith("encoder.block.0.layer.0"): + assert param.requires_grad is True, ( + f"Parameter {name} should be trainable" + ) + else: + assert param.requires_grad is False, ( + f"Parameter {name} should be frozen" + ) + assert found_any, "No parameters matched the freeze patterns, test is invalid" + + @patch( + "darts.models.components.huggingface_connector.hf_hub_download", + side_effect=mock_download, + ) + def test_finetuning_misconfiguration(self, mock_method): + # Warning if freeze_patterns assigned but enable_finetuning is False + with patch( + "darts.models.forecasting.foundation_model.logger.warning" + ) as mock_warning: + _ = Chronos2Model( + input_chunk_length=12, + output_chunk_length=6, + enable_finetuning=False, + freeze_patterns=["some_pattern"], + **tfm_kwargs, + ) + mock_warning.assert_called_once() + assert "enable_finetuning` is False" in mock_warning.call_args[0][0] + + @patch( + "darts.models.components.huggingface_connector.hf_hub_download", + side_effect=mock_download, + ) + def test_lora_callback(self, mock_method, tmpdir): + pytest.importorskip("peft") + from peft import LoraConfig, PeftModel + + lora_config = LoraConfig(target_modules=["q", "v"]) + callback = PeftCallback(peft_config=lora_config) + + # Avoid duplicate pl_trainer_kwargs + kwargs = {k: v for k, v in tfm_kwargs.items() if k != "pl_trainer_kwargs"} + pl_trainer_kwargs = tfm_kwargs.get("pl_trainer_kwargs", {}).copy() + pl_trainer_kwargs["callbacks"] = [callback] + + model = Chronos2Model( + input_chunk_length=12, + output_chunk_length=6, + enable_finetuning=True, + pl_trainer_kwargs=pl_trainer_kwargs, + **kwargs, + ) + + # 1. Initialize and fit + model.fit(self.series, epochs=1) + + # Verify transformation happened + assert isinstance(model.internal_model, PeftModel), ( + "Internal model should be a PeftModel after fit" + ) + + # 2. Checkpoint merging test (via save/load) + save_path = os.path.join(tmpdir, "lora_model.pt") + model.save(save_path) + + # Loading back should yield a standard model (weights merged) + loaded_model = Chronos2Model.load(save_path) + assert not isinstance(loaded_model.internal_model, PeftModel), ( + "Loaded model should have merged weights and not be a PeftModel" + ) + + # Verify predictions match + pred_orig = model.predict(n=6, series=self.series) + pred_loaded = loaded_model.predict(n=6, series=self.series) + assert np.allclose(pred_orig.values(), pred_loaded.values()), ( + "Prediction of the fine-tuned model and the saved/loaded fine-tuned model should be the same" + ) From 260de97871993e67881f6e71a59beee826372416 Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 30 Jan 2026 17:25:37 +0100 Subject: [PATCH 09/11] documentation: update example notebook on finetuning --- .../26-Chronos-2-finetuning-examples.ipynb | 235 ++++++++++++++---- 1 file changed, 187 insertions(+), 48 deletions(-) diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index 8c3f9d92d2..5b7246820c 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -6,14 +6,14 @@ "metadata": {}, "source": [ "# Chronos-2 Foundation Model Fine-Tuning\n", - "This example notebook presents how fine-tuning can be applied to the Chronos-2 model.\n", + "This example notebook presents how fine-tuning can be applied to the Chronos-2 model using both built-in Darts features and external libraries.\n", "\n", "The following fine-tuning methods will be shown:\n", - "1) Full fine-tuning : all the models weights will be retrained\n", - "2) Partial fine-tuning : some layers of the model will be frozen\n", - "3) PEFT fine-tuning : the HuggingFace peft library will be used to apply LoRA fine-tuning (requires `pip install peft` since it is not a darts dependency)\n", + "1) **Full fine-tuning**: All model weights are retrained. This is natively supported by setting `enable_finetuning=True`.\n", + "2) **Partial fine-tuning**: Specific layers are frozen via name patterns. This is natively supported using `freeze_patterns` and `unfreeze_patterns`.\n", + "3) **PEFT fine-tuning**: The HuggingFace `peft` library is used via a custom Darts callback (`PeftCallback`) to apply LoRA. This shows how to extend Darts with external specialized libraries.\n", "\n", - "To be useful, a fine-tuned model should be easily saved and loaded. For each fine-tuning method, how to save and load the model will be shown with an example (straightforward for (1) and (2), slightly different for (3))" + "To be useful, a fine-tuned model should be easily saved and loaded. For each method, we will demonstrate how to persist the model weights.\n" ] }, { @@ -105,7 +105,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8547492bdce140e5a935ba4db13a6b21", + "model_id": "04eebab1f5554fedaf9084d8557b30d1", "version_major": 2, "version_minor": 0 }, @@ -159,9 +159,9 @@ "source": [ "# 1. Full fine-tuning\n", "\n", - "In this method, all the model weights are retrained. This is done with `enable_finetuning=True` in the model constructor.\n", + "In this method, all the model weights are retrained. This is simply enabled by passing `enable_finetuning=True` to the model constructor. \n", "\n", - "The model is saved and loaded with the usual `save` and `load` methods, so the behavior is the same as other darts models." + "When fine-tuning is enabled, Darts will treat the foundation model like a standard trainable model during `fit()`. Saving and loading follows the standard Darts API via the `save()` and `load()` methods.\n" ] }, { @@ -173,7 +173,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "16d446f7866f4d0ca54ded638d7e66e3", + "model_id": "17fd61ce4c33441ea964bb758bf15730", "version_major": 2, "version_minor": 0 }, @@ -217,7 +217,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "30691d9dda1d4f998b5ed5001809a6b5", + "model_id": "ce88ef8f24694408ba71cd8203e5a052", "version_major": 2, "version_minor": 0 }, @@ -231,7 +231,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9cba0f4cc07645f69c14457c61b59d40", + "model_id": "b3d8ba35afd3483d80d3004824d6f640", "version_major": 2, "version_minor": 0 }, @@ -254,7 +254,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -316,19 +316,26 @@ "metadata": {}, "source": [ "# 2. Partial fine-tuning with layer freezing\n", - "With this method, top layers of the model will be frozen. That means that their weights won't be updated during the fine-tuning. " + "\n", + "Partial fine-tuning allows you to update only a subset of the model's parameters, which is useful for preserving general knowledge while adapting to specific patterns. \n", + "\n", + "Darts foundation models natively support this via:\n", + "- `freeze_patterns`: A list of parameter name prefixes to freeze (`requires_grad=False`).\n", + "- `unfreeze_patterns`: A list of prefixes to unfreeze (applied after freezing).\n", + "\n", + "This mechanism automatically injects a `LayerFreezeCallback` into the training process." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "id": "33fa7fc4", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1a38e2f67955406d8c399db728eb96e2", + "model_id": "7f7cc6aed7a04945bd449ef829d0559c", "version_major": 2, "version_minor": 0 }, @@ -359,14 +366,14 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "id": "50830283", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0c6375a46aa043aba1397eb195e2b3fe", + "model_id": "3df3477b4b4f44a68eee8c816515a008", "version_major": 2, "version_minor": 0 }, @@ -380,7 +387,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5117f22a8ec94ad5842ea8709e74fd4d", + "model_id": "2fbdbaa04f094966b1a0f251cf6994c3", "version_major": 2, "version_minor": 0 }, @@ -397,13 +404,13 @@ "" ] }, - "execution_count": 7, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -468,24 +475,25 @@ "id": "b0d126dc", "metadata": {}, "source": [ - "# 3. LoRA fine-tuning\n", - "This fine-tuning method uses HuggingFace `peft` library. This library makes it easy to use **P**arameter **E**fficient **F**ine-**T**uning methods such as LoRA which greatly reduces the number of fine-tuned parameters.\n", + "# 3. LoRA fine-tuning (PEFT)\n", "\n", - "More information about peft can be found in the [official documentation](https://github.com/huggingface/peft)\n", + "This method uses the HuggingFace `peft` library for **P**arameter **E**fficient **F**ine-**T**uning. \n", "\n", - "To use LoRA fine-tuning, the `PeftCallback` is used. A `peft_config` is required. In this example, a `LoraConfig` is used with the same parameters used in the [official Chronos-2 implementation](https://github.com/amazon-science/chronos-forecasting/blob/f889ae66477b53f6beb130f5c7b13590b29a1035/src/chronos/chronos2/pipeline.py#L202)\n" + "Darts provides a `PeftCallback` that wraps the internal model with adapters (like LoRA) before training. One major advantage of this callback is that it automatically handles **weight merging** during checkpointing, allowing the saved model to be loaded back as a standard model without needing the `peft` library at inference time.\n", + "\n", + "More information about peft can be found in the [official documentation](https://github.com/huggingface/peft)" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 22, "id": "6981052c", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cd7cd86f70dc4759ab3ed10c73fd7afe", + "model_id": "8dba495f46e248b29d33d99b40675881", "version_major": 2, "version_minor": 0 }, @@ -499,10 +507,10 @@ { "data": { "text/plain": [ - "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=50, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=100, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" ] }, - "execution_count": 8, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -513,8 +521,8 @@ "from darts.utils.callbacks.fine_tuning import PeftCallback\n", "\n", "lora_config = LoraConfig(\n", - " r=8,\n", - " lora_alpha=16,\n", + " r=32,\n", + " lora_alpha=64,\n", " target_modules=[\n", " \"q\",\n", " \"v\",\n", @@ -546,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 23, "id": "49b2c2e8", "metadata": {}, "outputs": [], @@ -558,14 +566,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 24, "id": "41e8a82f", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "80fe22ec79024e3e8d10bc5165d2f93e", + "model_id": "34b9699f0deb4cb4bca42eb3b663a3ed", "version_major": 2, "version_minor": 0 }, @@ -579,7 +587,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1588da65b96e44559a7b0086ac5b3796", + "model_id": "3955fb726ade4ff9b17f2660cea15057", "version_major": 2, "version_minor": 0 }, @@ -596,13 +604,13 @@ "" ] }, - "execution_count": 10, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -641,7 +649,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 25, "id": "9a96ca55", "metadata": {}, "outputs": [ @@ -651,7 +659,7 @@ "True" ] }, - "execution_count": 11, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -666,14 +674,15 @@ "metadata": {}, "source": [ "## 3.2 Adapter saving\n", - "Another method is to save only the adapter. This results in a light-weight folder containing only the LoRA weights which can be plugged to the original model.\n", "\n", - "For that, we need to access the internal chronos model with the `internal_model` attribute to save only the adapter." + "Alternatively, you may want to save *only* the lightweight adapters rather than the full model weights.\n", + "\n", + "Foundation models in Darts provide an `internal_model` property that gives direct access to the underlying PyTorch `nn.Module`. We can use this to interact with the `peft` API directly for saving and loading.\n" ] }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 26, "id": "ce2fcd82", "metadata": {}, "outputs": [], @@ -691,7 +700,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 27, "id": "630bb5bc", "metadata": {}, "outputs": [], @@ -712,14 +721,14 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 28, "id": "c1fddf83", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1be22001384a4a0f98955ab22636d9e8", + "model_id": "71e7d2b9d04f427eae8f9e8ea576d7c6", "version_major": 2, "version_minor": 0 }, @@ -733,7 +742,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "98511c12d7914f8987a18451fb44a40c", + "model_id": "f523a392cf9c420d98cb2b28510021f1", "version_major": 2, "version_minor": 0 }, @@ -750,13 +759,13 @@ "" ] }, - "execution_count": 14, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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" ] @@ -785,10 +794,140 @@ ")" ] }, + { + "cell_type": "markdown", + "id": "022127ca", + "metadata": {}, + "source": [ + "# 4. Performance Evaluation\n", + "\n", + "Finally, let's compare the performance of all four models (Base, Full Fine-tuning, Partial Fine-tuning, and LoRA) on the validation set using standard metrics like **MAPE** (Mean Absolute Percentage Error) and **MAE** (Mean Absolute Error).\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3b81f2e2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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ModelMAPE (%)MAE
0Base Model15.25451870.704819
1Full Fine-tuning3.23726213.835668
2Partial Fine-tuning2.89984712.568367
3LoRA (PEFT)5.95182926.501753
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" + ], + "text/plain": [ + " Model MAPE (%) MAE\n", + "0 Base Model 15.254518 70.704819\n", + "1 Full Fine-tuning 3.237262 13.835668\n", + "2 Partial Fine-tuning 2.899847 12.568367\n", + "3 LoRA (PEFT) 5.951829 26.501753" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "from darts.metrics import mae, mape\n", + "\n", + "results = []\n", + "all_predictions = {\n", + " \"Base Model\": prediction,\n", + " \"Full Fine-tuning\": pred_full_finetuned,\n", + " \"Partial Fine-tuning\": pred_partial_finetuned,\n", + " \"LoRA (PEFT)\": pred_lora_trained,\n", + "}\n", + "\n", + "for name, pred in all_predictions.items():\n", + " results.append({\n", + " \"Model\": name,\n", + " \"MAPE (%)\": mape(val_passengers, pred),\n", + " \"MAE\": mae(val_passengers, pred),\n", + " })\n", + "\n", + "df_results = pd.DataFrame(results)\n", + "df_results" + ] + }, + { + "cell_type": "markdown", + "id": "996456e0", + "metadata": {}, + "source": [ + "### Observations\n", + "\n", + "While the results on this small \"toy\" dataset (Air Passengers) may vary depending on the random seed and hyperparameters, they demonstrate the flexibility of the fine-tuning API.\n", + "\n", + "In real-world scenarios with larger datasets:\n", + "- **Full Fine-tuning** offers the most flexibility but is computationally expensive and prone to \"catastrophic forgetting\".\n", + "- **Partial Fine-tuning** provides a good middle ground by updating only the most relevant layers (like the output head).\n", + "- **LoRA (PEFT)** is often the most effective strategy. It typically matches or exceeds full fine-tuning performance while only training a tiny fraction (often <1%) of the parameters. This makes it faster, more memory-efficient, and allows for much easier deployment of multiple task-specific \"adapters\" on top of a single base model.\n", + "\n", + "### Summary\n", + "In this notebook, we have seen:\n", + "1. How to enable **native full fine-tuning** in Darts foundation models.\n", + "2. How to use **layer freezing patterns** to perform partial fine-tuning without manual weight manipulation.\n", + "3. How to extend Darts foundation models with **custom callbacks** to leverage external libraries like `peft`.\n", + "4. How to use the `internal_model` property to gain low-level access to the underlying PyTorch module for advanced operations.\n" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "6f74bc02", + "id": "2286828a", "metadata": {}, "outputs": [], "source": [] From a20c94311e17ad04a7268de92d314c68d034f53e Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 30 Jan 2026 17:37:11 +0100 Subject: [PATCH 10/11] documentation: update changelog --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 0217f5bd80..26df25012b 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -22,6 +22,7 @@ but cannot always guarantee backwards compatibility. Changes that may **break co - Includes automatic downsampling for large series (configurable via `downsample_threshold` parameter) to avoid crashes when plotting large series - Integrates seamlessly with `plotting.use_darts_style` which now affects both `TimeSeries.plot()` and `TimeSeries.plotly()` - Plotly remains an optional dependency and can be installed with `pip install plotly` +- Added support for full and partial fine-tuning of foundation models with integrated layer freezing and `PeftCallback` for LoRA integration. [#2964](https://github.com/unit8co/darts/issues/2964) by [Alain Gysi](https://github.com/Kurokabe) **Fixed** From a568a3d14d6d78f3bb400463b948e3ffe761636d Mon Sep 17 00:00:00 2001 From: Alain Gysi Date: Fri, 30 Jan 2026 18:20:56 +0100 Subject: [PATCH 11/11] fix: update on_save_checkpoint of lora callback to avoid potential OOM error --- .../models/forecasting/test_foundation.py | 6 +- darts/utils/callbacks/fine_tuning.py | 40 +++++----- .../26-Chronos-2-finetuning-examples.ipynb | 78 +++++++++---------- 3 files changed, 63 insertions(+), 61 deletions(-) diff --git a/darts/tests/models/forecasting/test_foundation.py b/darts/tests/models/forecasting/test_foundation.py index e3b74b127d..c3f4a43c22 100644 --- a/darts/tests/models/forecasting/test_foundation.py +++ b/darts/tests/models/forecasting/test_foundation.py @@ -194,7 +194,7 @@ def test_full_finetuning(self, mock_method, tmpdir): input_chunk_length=12, output_chunk_length=6, enable_finetuning=True, - n_epochs=1, + n_epochs=5, **tfm_kwargs, ) assert model._requires_training is True @@ -249,7 +249,7 @@ def test_partial_finetuning(self, mock_method): # 2. Freezing logic # We call fit to initialize the model and trigger the callback setup automatically - model.fit(self.series, epochs=1) + model.fit(self.series, epochs=5) # Check requires_grad status. found_any = False @@ -310,7 +310,7 @@ def test_lora_callback(self, mock_method, tmpdir): ) # 1. Initialize and fit - model.fit(self.series, epochs=1) + model.fit(self.series, epochs=5) # Verify transformation happened assert isinstance(model.internal_model, PeftModel), ( diff --git a/darts/utils/callbacks/fine_tuning.py b/darts/utils/callbacks/fine_tuning.py index 8583191b94..3c904f3824 100644 --- a/darts/utils/callbacks/fine_tuning.py +++ b/darts/utils/callbacks/fine_tuning.py @@ -1,4 +1,3 @@ -from copy import deepcopy from functools import partial from typing import Any, Callable, Optional @@ -210,28 +209,31 @@ def on_save_checkpoint(self, trainer, pl_module, checkpoint): return if isinstance(peft_model, PeftModel): - # Merge adapters into the base model weights - # TODO: This might be inefficient for large models, think about a better way - model_copy = deepcopy(peft_model) - setattr(pl_module, self.model_attribute, peft_model.merge_and_unload()) + # In-place merge of adapters into the base model weights. + # This is memory-efficient as it avoids a full deepcopy and works on GPU. + peft_model.merge_adapter() try: - # Get the state dict of the base model - # This returns the weights including the merged adapters - # base_state_dict = peft_model.get_base_model().state_dict() - - # We need to prepend the model attribute name to the keys - # because the PL module expects keys to start with `model.` (or `model_attribute.`) + # Obtain the state_dict of the base model (which now has merged weights). + # We filter out the adapter-specific keys (e.g. lora_A, lora_B) + # and restore the original key names by removing PEFT wrapper prefixes (e.g. base_layer). + # This allows the model to be loaded back as a standard (non-PEFT) model. prefix = self.model_attribute + "." - new_state_dict = { - prefix + k: v - for k, v in getattr(pl_module, self.model_attribute) - .state_dict() - .items() - } + new_state_dict = {} + # IMPORTANT: We move merged weights to CPU. This avoids GPU OOM + # (holding two copies of the parameters on GPU) and ensures we have + # a 'snapshot' that won't be changed by the subsequent unmerge. + for k, v in peft_model.get_base_model().state_dict().items(): + if any(sub in k for sub in ["lora_", "modules_to_save"]): + continue + + # PEFT wraps layers and adds a ".base_layer" to the key path + # We only replace if it's followed by a dot to avoid partial matches + clean_key = k.replace(".base_layer.", ".") + new_state_dict[prefix + clean_key] = v.cpu().clone() # Update the checkpoint checkpoint["state_dict"] = new_state_dict finally: - # Unmerge adapters to keep the current model in PEFT mode - setattr(pl_module, self.model_attribute, model_copy) + # Restore the adapters (unmerge from base weights) to allow training to continue. + peft_model.unmerge_adapter() diff --git a/examples/26-Chronos-2-finetuning-examples.ipynb b/examples/26-Chronos-2-finetuning-examples.ipynb index 5b7246820c..09554b97d5 100644 --- a/examples/26-Chronos-2-finetuning-examples.ipynb +++ b/examples/26-Chronos-2-finetuning-examples.ipynb @@ -105,7 +105,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "04eebab1f5554fedaf9084d8557b30d1", + "model_id": "d269fe29e6ab4b0faa9ca063fc607f74", "version_major": 2, "version_minor": 0 }, @@ -173,7 +173,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "17fd61ce4c33441ea964bb758bf15730", + "model_id": "45bbf43f117543b7a171e399527dce2d", "version_major": 2, "version_minor": 0 }, @@ -217,7 +217,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ce88ef8f24694408ba71cd8203e5a052", + "model_id": "5c258dd1f466442ba7f0d7ffa12fe5fb", "version_major": 2, "version_minor": 0 }, @@ -231,7 +231,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b3d8ba35afd3483d80d3004824d6f640", + "model_id": "cd4bb0d55fd94fb48bffd7428f22e10c", "version_major": 2, "version_minor": 0 }, @@ -254,7 +254,7 @@ }, { "data": { - "image/png": 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", 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", 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" ] @@ -335,7 +335,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7f7cc6aed7a04945bd449ef829d0559c", + "model_id": "50dfcff23af64611b005b9875ed3209f", "version_major": 2, "version_minor": 0 }, @@ -373,7 +373,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3df3477b4b4f44a68eee8c816515a008", + "model_id": "aaec2192041d44fa99aedae592c73a9d", "version_major": 2, "version_minor": 0 }, @@ -387,7 +387,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2fbdbaa04f094966b1a0f251cf6994c3", + "model_id": "72100e6de88e44fe904f1ced2c4189dc", "version_major": 2, "version_minor": 0 }, @@ -410,7 +410,7 @@ }, { "data": { - "image/png": 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", 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E5lCdpMvRkH42ZnsMw7RdUuzsAP37S1jwAHRzC8KvwQPx5Jq7cExdhXK1Ci8n/41jS47g2elL4eDobukuM42AnWStBHI0raqqEqabX3/9VZhSSKOycOFCnDx58rIFsp555hnMnz9fRPKcOXMGH3/8MZYvX46nn35a0cIMHTpURODQtrds2YKXX3650f0kR9wff/wR8+bNw+nTp4W/R1xcXL3fiYiIEJqMVatWITMzE0VFRXWu25B+NmZ7DMO0XZJV8kuKt6M3XN2CRDsoqC/mz9qKGx1DlfV+LU/GXYtHIz298S9ljOVgAcVKoPDgQ4cO4YorrsALL7yAPn36CGHliy++EELGm2++We/3r7vuOuFvQk6x0dHR+Oabb4QQQaG8BkiwICGI/D4otJccXBvLzTffjP/7v/8Toby0nfPnz+PBBx+s9zuUw+X1118XDrcUnkyhxfVxuX42dnsMw7Q9KrQVyCiR/cvyC92xdF+Ssow0Ja/c8g/eCLsKDnpz8VF1Feb+ORM4t9VifWYah0oyNfbbCAUFBfD09ER+fj48PDyqLaNoknPnziEyMlJEnTAMwzC2TW339cT8RFz9h5wfqjK/N8pSZ+GekZF48aoe0KiNaRmOn/wDT+z8P1RIWvyamo4Ackm74jVg+KPkpGaxY2qvFNTz/K4Ja1AYhmEYmyOl0Kgx0VXKqQd+2H4O9y7Yh8Iyo2N9z+7X4dfpf+Er+44IIL81SQus+z9g2Z1AeaFF+s40DBZQGIZhGJsjOW6Z0u5cZaxVtulUJq7/aicuZBvneXlHosfslcDoZ5R5BSf/xKMLR+LcuaalSGBaHhZQGIZhGJvWoDhWuWPeXYPg5SKnGTiTUYTrvtqBvedyjF9Qa4DxLwO3/AKdowde9PfDZjsdZm5+FBt2cBiyNcICCsMwDGNzJJVkKm0Pj54Y1y0Afzw0Ap385TQNOcUVuPX73Vi63yjICLpfhbw7/kSKk7xesVqFx88uwqcHPoVWx6kLrAkWUBiGYRib4/9ytfg7KRVfp2UgMlzOrN3RzxXLHxqBUV38xHSlVsKzvx3FO6tPQKszxoP4hPTHops3YIpG9l0hfoj9AQ+sfwA5ZSZaF8aisIDCMAzD2BwuBUnoUFWFjqVu6NcxUJnv6WyPeXcOwp3DjXV4vt2agDk/7a/mPOvi4of3Zm3CcwOfhp1Kzlm6O203bl51M2LPyxXeGcvCAgrDMAxjW5TmwkkrR+Bc0AWgfwfvaovtNGq8dk003rouRgk53nAyAzd8vQtJOUbnWZVajdnRd+D7Sd/D18lXzEsvTsftmx7B7+ueatVDYi6FBRSGYRjGptDlGKueZ9oFIcz70nplxOyhEfjp7sHwcJI1JKcuFuK6L3dgX2J1M86AwAFYevVS9PPuIaYrVSq8lroWO/d92aLHwdQPCygMwzCMTbH19CZ84eWJFW6uyPEJUIqa1saIzn744+ERiPKTnWKzyXn2uz347UBytfUCXALww6R5mOUcIaYna7wxbED9WbKZloUFFMYmSE9PFwUVqZCil5dXg7+XmJgobl5NKYxobVDZAkr931A2b94sjj0vL69R40rf+eOPP9CWobpVjbmOWpKmXKONvRbaGjtTD+Bbb0+84u+Li76Xzxge5e+GFQ+NwMjOsvNshVaHp5cdwdw11Z1n7R1d8cJNq/Bp51vx+nW/CRMQYzl49K2EO++8U9ykav6dPXsWtoo5HwKffPKJqHBMN3EqUljXGFJNIlunLsGCij9eriaTOcaVpqdMmWLW/XTs2BGffvqpWbfJtF/SSlKVdreQmAZ9x9PFXuRKuW2orCEhvtmSgPt/PoCi8qpq604Y8Txc3ALM2GOmKbCAYkVMnjxZPBxM/6j2RFOoqKhAWyI+Pl4UD+zSpQsCAtrujaOy0hhlUBMfHx+4u7u3+LgGBQXB0dHRrPthGHOSpc1X2gO7DW/w9+w1arx5XQzeuDZacZ5df+Iibvh6J5Jzjc6zjHXAAooVQQ8FejiY/mk0GrFsy5YtGDx4sFgnODhYVPKlir+mKl+q6ktqXz8/P0yaNEnMj42NFW/Dbm5uovLvbbfdhqysLOV7Op0O77//Pjp37iy23aFDB7z99tvK8ueeew5du3aFi4sLoqKiRCVj04fokSNHMG7cOPHgpMJP9LDbv3+/0ALcddddoiCUQRv02muv1XnsX3/9tajo7ODggG7duuHnn3+u9vb9+++/46effhLbIU1JTWjbCxYswJ9//qnsj/pgICEhQfSTjoMqRe/atava97dv345Ro0bB2dkZ4eHh+M9//oPi4uI6+0v769u3r6gaTevTdm+66SZxvAb27dsnzCd0Pqg41pgxY3Dw4MFq26F+0rFfc801wsxy3333iX4S3t7e1Y63plqfxogqXtPY07Uya9YsZGTI1V0bQl3jamriMZgfSHvT1PGjflPV6yeeeEI5N6ZjaAppWahfNbViVKWbrntfX188/PDD1a7B8vJyUfGbqlzTGA4ZMqTauTdo8+japv5Pnz4d2dnZ9Y6N4biXLl2qHNegQYOElonOK407/abot5WZmVnt9/TGG28gLCxM/J7o+P75559q2967dy/69esnit7RdqiKeU0u97ttz1CocK5GfgFz0kkIC5QdWxvD7cM6Yv5dg+Cud549mS47zx44n6uso62qwMlTf2HhmgdwLpHDji2CZIPk5+eT0VB81qS0tFQ6fvy4+LQl7rjjDunaa6+tdVlycrLk4uIiPfTQQ9KJEyekFStWSH5+ftKrr76qrDNmzBjJzc1NeuaZZ6STJ0+Kv9zcXMnf31964YUXxPcOHjwoXXnlldK4ceOU7z377LOSt7e3NH/+fOns2bPStm3bpO+++05Z/uabb0o7duyQzp07J/31119SYGCg9N577ynLo6OjpdmzZ4vtnz59Wlq6dKl0+PBhqby8XPr0008lDw8PKS0tTfwVFhbWenzLly+X7O3tpS+//FI6deqU9NFHH0kajUbauHGjWJ6RkSFNnjxZuummm8R28vLyLtkGbZuW03qG/VEfqN90rXTv3l1atWqV2P4NN9wgRURESJWVleK7dNyurq7SJ598Io6Bjrdfv37SnXfeWef5orGn74wfP146dOiQtGXLFqlz587SrFmzlHU2bNgg/fzzz2Js6Jq85557xPgVFBQo61DfAgICpB9//FGKj4+XEhMTpd9//13Mp76aHi+d48cee0z57g8//CCtXr1afG/Xrl3SsGHDpClTpijLN23aJLZD10Ft1DWu9B26xghzjF92drYUFhYmvfHGG8q5MYxhnz59qvWJtkHbNv1d0DX0wAMPiHFcuXKl+C18++23yjr33nuvNHz4cGnr1q2iLx988IHk6Ogo+kLs3r1bUqvV4rql/n/22WeSl5eX5OnpWef5NT3uf/75R5y/oUOHSgMGDJDGjh0rbd++Xfye6JxT3wx8/PHHor+//PKL+A3S74uubUNf6Dql3yRdJ7GxseJ4oqKixL7oOiIa8ruteS20dUzv61tPpUn95kVLMfNjpGnfxTRru2cuFkpj3t8oRTy3Svx1eXG19PuBJLFs6b+Pi33Q348r7zbTkTD59Ty/a9K+BJQdX0jSh92b/5ewtfp2adqwjPbRBOhGTA9lutEb/uhBQLz44otSt27dJJ1Op6xPD3MSSLRarXLDooeCKSRcTJw4sdq8pKQk5eFHD0q6kZsKJJeDbv50kzbg7u4uhJvamDdvXr0PAQP0cLnvvvuqzbvxxhulq666Spkm4Y3GqLFCnuFB8/333yvz4uLixDy6+RMkOMyZM6fa90hQo4daXYIuPVzpfJHwaGDNmjXiO4YHcE3oXNF40UPJAPXj8ccfr7ZeXYLF5R5K+/btE98zCIKXE1DqGtfaBJTmjh8JHSR8mNJQAYWmq6qqql0bN998s2ifP39enIeUlJRq25kwYYJ4wBMzZ86sdi0R9P2GCCimx01CB80jwdPA3LlzxW/TQEhIiPT2229X29agQYPEywXxzTffSL6+vtWuq6+//rqagHK53217F1A+W7lSERzu+WFQs7edW1wu3fLNLkVIob/31pyQTp9dq+zn4QVDzXIcjNQoAUXWb7UXqLR2odG5qsloyy+dNmy3GeW7SYVO6n4DpK4mTpw4gWHDhlULpRsxYgSKioqQnJwsVNcEmVdMIfPLpk2bhJq4Nt8DcsIk9fiECRPq7NOvv/6Kzz//XKxP+yOzEplyDDz55JO49957hbnhiiuuwI033ihMNY2Bjm/OnDnV5tHxffbZZzAXvXv3VtpkKiDIHNK9e3cxTkePHsWiRYuUdeg5Ter6c+fOoUeP2lXINO5kVjBA54i+c+rUKWFyuXjxIl5++WVhbqB9abValJSU4MKFC9W2Q2r+pnDgwAFhJqH+5+bmin0TtP2ePXvCnLTE+DWU6OhoxdRp2P+xY8dEmz5pXMkMaQpd12QOMlxfZNYxhc5VTdPL5Y6bTC1Er169qs0zmNUKCgqQmpoqrl1TaJrGyNAX2iaZd0z70pjfbc1jbW+cSz0I6F2kwp3kqJzm4OXigJ/uGYxX/4rD4j3yb/OrzfE4c9Ef3joJuWoVDmoLhclHY+fQ7P0xDad9CSiO7oB7SPO3o3G8dNqwXdpHEyGBhHxBmvN9U0iguPrqq/Hee+9dsi7d5Mkvoz7Iz+DWW2/F66+/LnxayI9iyZIl+Oijj5R16AFJvg9///031qxZg1dffVWsU/OBYGns7eUqp4RB0DM80Gmc7r//fuE3UROD8NcU7rjjDuHrQIJWRESE8Emgh1FNB+aa560hkH8HnRP6I8HA399fCCY03RIO0i0xfmq1Wggyl3MSNt23Yf+m+ybhhYQ1UyGGqO0Bb47jrjnP0BdzcbnfbXuGrpecgrOAvzwd6RVulu2S8+zb18Wga4Ab3lh1HBR5vO5EJsZ0dEGucykK1Sqcjl+DHt2uNcv+mIbRvgSU4Y/If+YmchTw1Am0FPQGSs6M9OM03CR37NghnCPJGa8u+vfvL75HTod2dpeeaorcIOe/DRs2CC1ITXbu3CkerC+99JIyj5wda0JvdPRHTpAzZ87EvHnzhIBCDq/0dtuQ46PjoQe6AZpurBagofurbZyOHz/eaOGQBAJ6Yw4JkYXT3bt3i4cuOfkajuGrr77CVVddJaaTkpIa5OhIx0HUdywnT54Uws+7774rnFIJck62BA0Zv9rODQlVlIfF9LpubL4acjal7ZIWg5xZ67q+9uzZU20enStzQ5pFuhbovJNDtAGaJgd3Q19I21hWVqZoUWr25XK/2/ZMSl4pJHW6Mh3m1ThtbX0IR/ERkaLg4KOLD6GwvArawlDAWU71cCCBBZTWhqN4bICHHnpIPNweffRR8WCiSBXSVJB5hR6IdUHRDjk5OUJooMgDUg//+++/IrqGbup0g6QonWeffVZEctByuln+8MMPigBDD2HSiNAyMvWsWLFC2X5paamIHCITBgkudCOm/RhU+nSDpbdBEoDowUzmjdp45plnRJQFmbfOnDmDjz/+WESNUGRGY6D9kamBTCy0v/pCdk2hMSBhjI6FHpDUBxpjmq4PGj8Sqkglv23bNqFBoEgeMu8Yxo8eRqTWpwckaaNIILwcJBTSzXLVqlUiQoTGsDbNBD30v/jiC6EJ++uvv8yeI6WhNGT86Nxs3boVKSkpipBG0T10fBRFRtfXl19+KbRwjYEEYxrX22+/XVwzZFKiKJm5c+cKrR5B54XMORQJRH3773//2yDzTlOga5k0H2QapeuQou1oTB577DGxnLSNdG4pWouEutWrV4t+NeZ32545nlqAyko/dC+xQ1iVhPAAownOXIztFoD/u1p+OUor7qfM358lmxWZ1oMFFBuA/BzoRkY3XgrxfOCBB3DPPfcI/4b6MLzN0U1t4sSJwnZOYaqUPM0g2FDY8FNPPYVXXnlFCBY333yzYlOn0FfSitCDhsIl6SFE6xsglTq9xdPDgR4U9HCm0EgyCRHDhw8XfaVt0tsyPYhqg8JIyQxCN2ryN6DQXdLC0AOsMdBNn7QX5NNB+6NjbwjkE0Bh3BRCSm/h9FZO42HQjNQFaQyuv/56oSGh8aXtkMbEAAl65BtCb8QUJkoPyobkcKHzTWNIDzfycahNUKLjI6Fu2bJlQtNEmpSaD7rWoiHjR6G3FLpL/knUd4KuNxovEkzouqbru7FCKUHXCl2DdB3T+afriR7sBvPS0KFD8d1334lrjPazdu3ay/52mgqdY3pxoL7Q740EIRIeSVg1mJ1WrlwpfGdonEg7WdOU05DfbXvlRFoBduXein3n38JLozejS+fJLbKfPmFygsmEsj5w18omvANV+dBpqyd0Y1oWFXnKNuYL9AZEb0z0pkNvxHSTphuEwdGPNkdv93RDICdMchCjN2PDD5SgtwPSBtAPlX5wM2bMEDePhtqMyRmN/CEo54SpwyZBqlN6i6IEZ6aOaAxjTsj3hnKFtIUU+gxj7Rju6+9uz8aWeMqtBBx9dSLcnar7J5mLKq0O0a/+i/IqHYZHvIpjLnJgxPKRH6JLJznHFNM06nt+16RR4ji9DZLAQU5iJKCQipIcJimhlAF6SyZTwP/+9z+h1iYHQHLcowvMAKlk4+LisG7dOqHGJtVvzSgOhmEYhjGgkyQkZMnJ/7oGuLeYcELYadToESw/PNXFRk3ggTOr+IS0Io3ywCJVJDnkkcbEgGkqdtKeUCZIUp9ee63s7Uy+DaSmprfNW265RdjjSe1pyMZIkB2d1OSkor6cWp1hGIZpf1RqdUrEVL8OLV/oMSbUA4eT8pBR3Be+3mcxoKwM4Y4pLb5fpokaFLKlklBBuS7Ilk42VDLlGCAVHHnlUz4MA6TKodTThtTY9Em2VNPcD7Q+mXpqetqb5jQgtZDpH8NY2sTD5h2GaT0qqnTo7rIdoV2fxdm82/D35ldadH8xIZ7iM750AP5NzcNHmdkYkRxLb+Itul+miQIKRQsY/EnIq/zBBx8UTmFUA4Ug4cQ0oZEBmjYso8+ajoIUSkeF0Azr1IQ88knQMfwZwioZhmGY9iOgONtnokCjxik7Hcoq666VZQ5iQmUBRQs7JDhFyzOLLgLZ8S26X6aJAgqp1ygi4Z133hHaE/IbocgJ8jdpSV544QXhUGP4o5BbhmEYpn1A7gMVWglldsYs3qE+LZtRt0ugG+w1+rxTVd2NC843LDqQaWUBhbIY1kyeRaGChtTdhvwPlOLbFJo2LKPPmhVXKX06RfYY1qkJZeAkb1/TP4ZhGKb9+J9odRLi7YyRnqGdJrboPh3tNOgaKGcGX1MYJT7LVCokJKxr0f0yTRRQKIKHkg+ZQrkPKLGUwWGWhAxKzGWA/EXIt8RQb4I+KfyYUlMb2Lhxo9DOkK8KwzAMw5hSViknqFPb5YtPjUqDII+6s2ib2w/lqC4Sc4KCMCwiDPcXHoZk5vIGjBkEFEraRZlGycRz9uxZLF68GN9++63IfEhQhkRKKPTWW28Jh1pKRkQJlCgyh5InGTQukydPFqYhSsxECYkoERVF+HAED8MwDFOTskpZIFDb54nPINcg2KtbLszYNJKHqIQ9Su3dUKVSIV2jQkrqPj5J1iagDBo0SKQ6/+WXXxATEyNSa1NYMeU1MUBp0ykJG/mn0PqUppvCik2TplFxM6qCSlV0Kbx45MiRQtBhGIZhmJqUCg2KDiq1XAgzzK3ltSemjrJEoNYYnHEgeRufpFag0XmTp02bJjQjlHiNcpqQJsQU0qJQWmuKyKF11q9ff0l5cIrYIe1LYWGhcHr98ccfzVJ5lGm70PV05ZVXisR/FKbeUCi9Ol2T5g4JpjBjSv/f0phjPy01Bq3dpzvvvFPRxNYF5Vui7NZUhoG0uVQOoDHXi61CZSHoeK2Bxl6zl7sWdDpJZHS1Vxlra4W2Uk0iStamUcuOsmfKjaU39mtlUxPTsrTvwg5WBN186Uda849MabaKOR8On3zyCdLS0sRNjPyemvoAY1qf2s4LpQqg80maWHNy//3344YbbhCRfqThpTpQdV0vTYWKY9Jvk3zpmNbRnlAUj1plFEpCq1qnJo6TvQad/eWX57j0SDio5Urj+9MtUzm8vcECihVBvjl00zb9M83U2xgqKmRVaFuBKroOGDBA5OBpSME9xvJQsTtD5s+akIaDHOopB5K5IHMyRQhSaQ3yZ3N3dxfVo/l6sW1KKmTBRGUioIR5ylE1rUG03g+lSmuHKA+5UntyUTLSi2vP28WYDxZQrAgKp6abtukf3cgJqhY7ePBgsQ6Fe1OlWwrPNlXxkrMxqXn9/PzETZqIjY0VFYbJhEYJ86iqrqHcPUEPEKqfRGpx2jZVgH377beV5VQYkkx0Li4uiIqKEtWMKyuNqtYjR45g3Lhx4mFA4d8kROzfv1+8ZVJ5eDLhGbRBpPqtC0oASJVuHRwcREXan3/+WVnWsWNH/P7776JsAm2H3shrQtumhIF//vmnsj/qg2mSQeonHQdVtDVkNjawfft2UYmXHmj0dk8JCIuLG54IisaRTJthYWFiHEnFTb5XplxuLAmqSkznicaTKlab1rAy8P333wtnc/LrIl8u0wrKBDmfU54iWk4Zmw8dOnTZ/tMYk8Zh5syZwoxGFZWpyrApH3/8saisS8tpjB566CEhFNTUmJGDPKUjoHG4++67az0vNdX6JMzQ8ZJATueArgEqINpQaJs0ZsT48eOV/dTU4hnMD3R90TFT4kdy0Cdzs+m5pOSQhr7Q9fLbb7+JZdRvuo4IqkFmej3S9sgnzxTal+l1T+vT+Zs+fbq4DkjgpvEy5XK/WbouKfiAltO9gOqhXQ7DcZM5nX7j9F06fzTu9Punew0Jcqa/fYJSSFDZElqfft9UsbxmGglzXLP1UVIh3+ccdcAL2Tl4JjsXvYIHo7UwRPIQPhpZQCEOsBal5ZFskPz8fMo1LD5rUlpaKh0/flx81mR+7Hxp/NLxl/17ZP0jl3yX5jXku7SPpnDHHXdI1157ba3LkpOTJRcXF+mhhx6STpw4Ia1YsULy8/OTXn31VWWdMWPGSG5ubtIzzzwjnTx5Uvzl5uZK/v7+0gsvvCC+d/DgQenKK6+Uxo0bp3zv2Weflby9vaX58+dLZ8+elbZt2yZ99913yvI333xT2rFjh3Tu3Dnpr7/+kgIDA6X33ntPWR4dHS3Nnj1bbP/06dPS0qVLpcOHD0vl5eXSp59+Knl4eEhpaWnir7CwsNbjW758uWRvby99+eWX0qlTp6SPPvpI0mg00saNG8XyjIwMafLkydJNN90ktpOXl3fJNmjbtJzWM+yP+kD9pmule/fu0qpVq8T2b7jhBikiIkKqrKwU36XjdnV1lT755BNxDHS8/fr1k+688846zxeNfZ8+fZTpjz/+WBzrL7/8IsaexpWOibbX0LH89ddfJUdHR+n7778X23jppZckd3f3avtZuHChFBwcLP3+++9SQkKC+PTx8RHnzzAOdM5nzZolxcbGSitXrpSioqLEGBw6dKjO46HxoH3NnTtXjNHnn38uzsHatWuVdWh86JxQ/zds2CB169ZNevDBB5Xl8+bNE8c8fPhwcZx0DPQbre+8GPpUUVEhvfLKK9K+ffvEcdFx0jVPY9KQ3whtk/pN26QxMeyH+uTp6VntvNHv5Prrr5eOHTsmbd26VQoKCpJefPFFZZ233npLXC///POPFB8fL7ZB52Xz5s1SVVWV2D7th/Znej3SGNIYmULnzvR3St8LCwuTFi9eLJ05c0b6z3/+I/qTnZ0tljfkN0tj3qFDB2n9+vXS0aNHpWnTpolz99hjj9V5fg3HTdd+XFycuP4cHBykSZMmSY8++qg4Vz/++KPo3+7du8V3tFqt1LdvX2nkyJHS/v37xfwBAwaIe405r9ma10JNjqfmS4fPXZQO7twolX4QLUmvekhSYYbUWuxJyJYinlsl/h7+5VspZn6M+HttyeRW60Nbor7nd03alYDy5aEvlYurvr9Zf8+65Ls0ryHfpX00Bbr50gOBHpSGP7qZEHTzpIeBTqczHsuXX4obDt1ECLpp0EPVFHogTpw4sdq8pKQk5eZaUFAgbi6mAsnl+OCDD8RNygDdjAw3mprUfDjUBT3Q7rvvvmrzbrzxRumqq65SpunBRGNUH7U9wAw3P7qBGqAbNM2jBwBxzz33SHPmzKn2PRLU1Gp1rddRbQJKSEiI9Pbbb1dbZ9CgQUKobOhYDhs27JL1hwwZUm0/nTp1Eg+3mueZvkt88803kq+vb7V+f/311w0SUEiIMOXmm2+WpkyZUud3li1bJvZler5pPySgNvS81Nenhx9+WJoxY0a92zGFHu60zU2bNlXrU00BhQQfuvYNkFBP40yUlZWJ5Tt37qy2bbpGZs6cKdq0fdoP7c+UhgooL7/8sjJdVFQk5q1Zs6ZBv1kSQEmwoBcBAyTcODs7X1ZAqXncJJx07NhRuYcQdJ8hIZUg4ZTuSRcuXLjkt7N3716zXbP1XQvllVrpSFKuEFCO7VwvCyhvBUmSyb2wpSksq1QElBmfr5L6zosW9/qrf+jVan1orwKK+QzANoCrvSsCXC7vv+Dj6FPrvIZ8l/bRVEh1TKYOZVuu8rYoWooS3JF62DRpHqnXk5OThcqWIPOKKWR+2bRpU60RUuTTQU5+VIiRwr3r4tdff8Xnn38u1qf9kVnJNJPvk08+iXvvvVeozKnoIxWSJFNNY6Djo7B0U+j4GqPivxy9e/dW2qQWJ8hfgdTNNE5Hjx4V4e8G6FlCqn4qgEmq6fqgZISpqamizzWPgbbd0LGkcXjggQeqbYPOO51Dg2qfvktqdNPoOdoOmSoM26BjNQ3rNyRJvBw116NpU5MFReSR6ePkyZPimGm/pM4vKSkR5gqCTHSmY90YyKREJggyK5SWlgo/qpaIlCJTjMEcZLgeDNmtySmdjocixkyhvpDZzByYjg/9xukaMOz/cr9Zw7iYJrWkqEgyiTX2uMksQyZkKtRqOs/QF7qWyJRnWvuMTHdkMqNllEbCHNdsfZTqzTuEGnofFO+OZCtDa+HmaIcoP1ckZBXj6EU1Brk54Kg+oqi0JAfOLpc+Lxjz0K4ElDui7xB/TeGLCV+gpaGbFfmCNOf7ptBD8Oqrr8Z77713ybp0Uya/jPogPw3KcfP6668Lnxa6oSxZsqSazZts27NmzcLff/+NNWvW4NVXXxXrkI3dmrC3NyZ1Mgh6BgdOGieK/iC/k5oYhL/m0pCxvBwGfw+qIF4z67LBV6mlIN8LSjFABULJT4EeiuS3Qw8eemAaBBTy2TAVpBsKjcXTTz8txoMecPQg/eCDD+qscG6ua4Gg/ppeCwRdz+SHYwr51NQHPehlJYmRmj5GDdl/fb/Z5kT11bbf+vpiDpp7zRocZO1QJdLMn7a3R4RnGC4v2piX6FBPIaBQwcJ7Yl5C78ho+PmZ1OdhWoR2JaDYKvQGT06idPMz3PwpAy/dxMkpsy6osCN9j96caouWIAc9eqBQaQLSgtRk586doozBSy+9pMw7f/78JeuR4yf9UaZhcrKcN2+eEFDobZqc8BpyfHQ8d9xhFB5pumbdp8vR0P3VNk7Hjx9vsnBIb8AUNUJ9HjNmjDKfpsmxuaFjSeNAD2RygDRAmZtN325pPyRYmiZHrLkN0maRZsOgRTHdRn3UXI+mDdojKk1BDy4SIAxv3EuXLjXbeaGxGj58uHDcNEBv3q2NwbmXtDim57Lm8RA1j8nf319E3hkgLRNp4BrD5X6zpJ0koYKuE4PwnJubK0Kp6+pvU6FzT+Ha9GfQotDvhDSvht+mOa7Z+ijWCygadQVyNWq8F+CPCZoyPIfWJSbEAyuPpIp2tmow/PyMWiWm5eAoHhuAbtp0k6AMvaRep4gI0lSQecVUPVsTKkFARRhJaNi3b5+44f/7778iuoZurvQAo8gSyv5LETK0nG4uP/zwgyLA0I2a3m5pGZknKJOwAVI3U+QQRUvQw5YeMrQfw0ONbrL0BkUCEEUhkOq8Np555hkRbUHmrTNnzohokeXLl4s36sZA+yNTDdWLov3V9vZaGzQGJEDQsVBUCfWBxpimGwodA731khmH9k9RVrStxx57rEFjSdC6ZOIgAY8eOHSO4+Liqq1DGhgys9D3aR1Kmkjr05gRpM0iIZbU6fQwWb16NT788MMGHQOdP4rooO2SuWXZsmVK/0l4o/H84osvxMOGhKCGVjFvyHmh8aHoL7o+af8U4UTXUmtDQj9ddyRsU/QRnauDBw+K46ZpggRNGuNVq1YhMzNT0RJQ9BCNy7Zt28R5IYG7sZqty/1myfRDWiu63qiGGUX8UBRRffeBpkImW4raIsGCxoCiw0gQIUGIosPMdc3WhU6S9BlkAXu10dQT6l5ds9XaGWXjUgtaff/tFqkdOclaM5dzAKQIAnK6JAc5ijp47rnnlCgUg5NsbU5yFEUyffp0ycvLSzjSUXTC448/rjjckoMcRS2Qgx9FYFB0wDvvvFPNgZAcIckhl5wmyQnQ4HRIURK33HKLFB4eLvpFjqKPPPJItbF/4IEHxPfpfJk6C9bkq6++EtEm1IeuXbtKP/30U7XlDXGSpWgfinigvhqcJWtzwKvNmZKc/gzfJQfl3r17X+L0Wp+TLI3ja6+9JoWGhopjoGUGx8eGjKUB2idFaNE6dLwUDWS6H2LRokUiuoLGnCKwRo8eLSKhDOzatUt8h5bTeoaok8s5yb7++uvCOZmcKeka++yzz6qtQ5FKFI1B1xE5WNI5MnUWrcspuiHnhZxTKWqKvk/XKkWqPP/889WO3VxOsjXHk84DHb8B+m1QBBo5jNK5pKgaOt4tW7Yo67zxxhtijFQqlXJd0v2IzitFc9FvgpzHa3OSpSg8U6h/1M+G/mbJUZYi5+g8USTY+++/X+fvv77jrm08a27n/Pnz0jXXXCN+E+QQT9dHenq6Wa/Zupxki8srhYMs/SWknJDW710vXbn4SmnTzg+k1ia3uNzoKPvVjlbff3t1klXRP9gYpDolGz7l2DB1MiRItU1qVcphYOooyDBM/VoOyqFjLenSGSarqBypeaViINw0qTiXnIb3zr6HLwc9iS6dJ7f6AI18byOSc0vh4qDBspllWHHkG+wvScF/us/G+OHP8gkzw/O7JmziYRiGYayOknKjj48WRsfd0KD+FumPIWEbOe6eTDmOX8uTEa+RsC9lu0X60x5gAYVhGIaxOgwZZNUqFaogK/o9dRJc3CxT6iJGn/KekFwnQKU3PhwoumCR/rQHOIqHYRgRRsww1kKlVocKraw1cbFXoVivTAlUWe6RRaHGBk7luKOLpMFplQ6nVFUoLEiBu0frO++2dViDwjAMw1gVhvwnhLOdsfBpoN2lCewsUZMnNqUAA13lUGOdSoVDJ5ZZrF9tmTYroNig7y/DMAxjYt4h7NWVIAuPBAmBTt4WGx9/d0cEeciBF7Gp+egfPFRZtj95q8X61ZZpcwKKITNiXTk3GIZhGNvRoNipJagqJFTpquDnbDkBxdQPpbCsCiEhVyvzDxQ0LiEf0059UCgxEtWKMNSToBTcTUm9zTAMw1hG+11cUio+7dUqaCsdoSm1R3RwV/j1kjMzW4roEE+sPyE/Wy4UByBKq0KCRsJxVSVKijIs5sDbVmlzAgoRFBQkPg1CCsMwDGMbUL2bjMJy0Xa210Dl5iBeOum+bumXTdOMsmTmGeASgoTyFFSpVDh88jcMH2gs1cA0nzYpoNBFTIW1AgICGpzunGEYhrE8fx5OweebkkT7wbGdMaxrZIsXw2xKqHFsSj5mdh6CZYnLxfT+C5tZQDEzbVJAMUAXtbVc2AzDMMzl2XO+ECmFsg9KdLivVd3DyUnW19UB2cUVoibPoGk34P5D8zCwrAx9tMGW7l6bo805yTIMwzC2y6GkPPHpoFEjzDUfd84fiJcWT8DKTcZK4JbUzhvyoeQUV6DSsTMeUflgaFk5nFMOAZVyan7GPLCAwjAMw1gF9NA/l1Us2tGhHsjIPIgDqnL8VZmB/el7YQ3EhFQ386DjCHlCWwEk77dcx9ogLKAwDMMwVsHhpFyl3b+DN1KyTynTYa7WYUKp7ihbAESMNC48v8MynWqjsIDCMAzDWAWHLsjmHaJfBy8kewYq06GdJsIaMM0oG5eSD6nDMMTb22Gpuxu+Of+3RfvW1mABhWEYhrEKDl4walD6kQalMEWZDgvoDWsg3McZ7k52SqixyqcjHgwOxpt+Pvhel4vKctlExTQfFlAYhmEYi6PVSTiSlC/agR6OCPF0QkqRUUAJdbOOYnzkKGvQolwsKEdGYRkGOMoJ2srUKsSeWmHhHrYdWEBhGIZhLM7ZjCIUlcs1ePqFewtBILkoWUw72znDx8kH1oJpPhQKNx4YbMxwe6AszUK9anuwgMIwDMNYlXmnf4QXdNoqpBZcENOhDl4WzyJbl6Ms+aEMHPigMr0/P95CvWp7sIDCMAzDWJxDNfxPMjJjUUlljMn/pLQI1gTV5DEQm1KADu4d4O/sL6YPZRwShQ2Z5sMCCsMwDGNxDuojeOzUKvQK9URy+mFlWZiTL6yJSD9XuDhojI6yKhUGBA4Q0yVVJTiZc9LCPWwbsIDCMAzDWJT80krhg0L0DPGAk70GgeXFeDQnD9MLizDAu7tVnSGNWoVofcK25NxS5JVUYGDgQGX5/jN/WbB3bQcWUBiGYRiLckSf3p7oF+4lPsNL8jEnvwBvZOXgig7jYW2YmnmEo6xbB2V6/5mVFupV24IFFMYm2brnEzywYAj+3vyKpbvCMIxZHWS95UbueeMKXhFWN8bVMsqm5CMqZAi8dbLPzEFtIbRVFRbsXdugTVczZtoub8X9gDSNCjvOr8DRrRV4euSbsFfbW7pbDMM0N4NsuF5AyTMRULytUUAxhhofS8mHSq3GeKcQ5FYVY4B/NKqqSqGxc7BoH20dFlAYmyM/L1EIJwYWn/sbZ0sz8eGYD+HtpL+5MQxjE+h0khLB4+vqIDK1EucKEhGkUsHZxQ9wcIW10dnfDY52apRX6YSJh3ht5lpLd6tNwSYexuZwyUvGwtR09C0rV+btTd+LmX/PxKkcY3ExhmGsn4SsYhSU6RO0dZATtJWX5eMab3sM7hiOB/2MphRrwk6jRvdgWYtCFZgLyyot3aU2BwsojM1hnx2PPuUV+DntIn7uMAO++hBESot926pbsHbbW816m6uo0pmxtwzDNDz/iewgm5p2UJnnbu9mtQMYo4/kIY7rtSiM+WABhbE9sk4rzb4dxmDJtCWI9o0W06VSFZ5K+BVfrpjZqE1WaXX4aVciBr29HkPnbhBvRAzDtF7+E1MBJTnzmDIvzMVY0diqHWVNBJSK8kIcPPITsjJPWKhnbQMWUBjbI9PEjOPfDUGuQZg/eT6mOQQps13sXRq8uW1nMnHV59vwyp9xyC6uQE5xBVYclGuAMAzTOhoUtQroEyYLKCk5Z5TlYR7G8F1rw1A00JDynvhn6+sYvngY7jj8ATYc/NqCvbN9WEBhbI5lBaewzdkJac4egHuwmOdk54R3bv4XT/sNwzX2Abjzqu8uux3Skty7YB9u+2EvTl+snkqbvPIZhmlZqDjg6YuFot0tyAOujnLcRnJhkrJOqE9Xqz0NXYPcROZbQ0ZZItw/BuX6efszjdlwmcbDUTyMTVFakoM3XSRIrgHopbPDYpMCYhTmd8fUbyHpdKJtSnraIQQF91OyVv534xnM35mISq2ct4DoE+6FhMwiFJZVCQFFkiSrKlDGMG2No0l50KcOQX+9eYdIKctS2mGBfWGtONpp0DXQHcfTCkQm3NIKLbp1ngrX3a+iWK3C/oqcWu9HTMPgUWNsisSkbZD0QkOkY+3l12veDHbu+xJT/r0N81bdi4W7zmH8h5vx3bZzinAS6OGIT27ugxUPDkdffRbLrKIKpBeUtfjxMEx75pBpBtkOxhQByVWyVkUjSQgM6A1rxpAPhQStE+kFsLN3Ql+1HBadpVHhQtIOC/fQdmEBhbEpEtIOKO0o98vbptPTD+OZ2K9RpVLh4+w9WLP/FhSVyDZvymHwn/GdsenpsZjeLwxqtaqa09uxZDbzMExLcvD8pRE8kCSkQCuaQTqVeOBbM6b3DIMfykCfHsq8/af/sEi/2gIsoDA2RUKu0UE2yk+O3KmPMk0UBlZ0VKaPepSgW8c3MaNHETY8NQZPTuwGFwejpZOqqJqmr2YYpmUgE6pBg+LpbI8oP1nrkJ9/AYV6H44wjXULJzVr8sSmyJE8Azteqczbn2EMmWZaUEB57bXXhE3e9K97d2OVybFjx16y/IEHHqi2jQsXLmDq1KlwcXFBQEAAnnnmGVRVyUl6GOZynCtKUdpU+6I+57v3/jmJiZ/uwJ/nHkS3lCFw1sn5Tc45AQe0byIrecUl3zMVUNhRlmFajgs5JSJizqA9Mfh7paQfUtYJc7D+zNA9gt1FBJKpo2x01+vgpHeuOVCeacnutS8n2ejoaKxfv964Abvqm7jvvvvwxhtvKNMkiBjQarVCOAkKCsLOnTuRlpaG22+/Hfb29njnnXeafhRMuyGhsgDQAPaShNCQQbUmWvvtYDI++PcUMguNmWbPS7fgoeDRWJL6AVI1QLZGhbsOzMX/pR/C9Vd+qKwX5u0MLxd75JVU4lhKATvKMkxrFAg08T/p0fUabA/qi+S0A3C2gdIVpIHt5O+GMxlFIiKpvEoLR0dX9FE7Yw/KRFmOlJS9CA0dbOmutn0BhQQSEjDqggSSupavXbsWx48fFwJOYGAg+vbtizfffBPPPfec0M44OHBhJaZuKitLcF5NWhAVOkqaS2zT+xJz8PrKOEXNSjho1LhnVCQeHtcZbo52uC5nBJ7+62bsVZULv5RXU//FyV9P4Jnrl8He3kW8xZEWZduZLGQVleNiQTmCPK1fzcwwNl0g0CSCh5zcPb06ij9bgfxQSEAhx/szF4vE9ADPrtiTf1Qs339qOQsoreGDcubMGYSEhCAqKgq33nqrMNmYsmjRIvj5+SEmJgYvvPACSkpKlGW7du1Cr169hHBiYNKkSSgoKEBcXFyd+ywvLxfrmP4x7Y+k5N1CqCCi7I2mmOTcEjy8+CBu/N+uasLJ5OggrH9yDJ6b3F0IJ4S3Tyf879atuNXZePP7syQRaYumA8VyaGM1R1n2Q2GYFtWg0E+aQvxtmWoZZQ2Osh0niM+wykrosoyJ55gW0qAMGTIE8+fPR7du3YR55vXXX8eoUaMQGxsLd3d3zJo1CxEREUKAOXr0qNCMnDp1CsuXLxffT09PryacEIZpWlYXc+fOFfti2jfnUvcq7SjXUJRUVOHrzfH4dmuCqChqoHuQO165uieGd/KrdTukKXn+ppXotv4ZvJW8BnMzs9GhJBn4dhwwczF6hfpVE1Cu7Gm9qbYZxhahfCEn0uRQ4i4BbvBwsoctY1qTx+CH0rf7jVi3+gUEVZQB3qyFbXEBZcqUKUq7d+/eQmAhgWTp0qW45557MGfOHGU5aUqCg4MxYcIExMfHo1OnTmgqpIl58sknlWnSoISHhzd5e4xtolKp0V2nxjlo4WofifEfbqmWq4RKtT81sRtuHhQOjcFrrR6mX/EBRp69Ev5/PEK3TCD/AvDDRAya8AmVKBPrcCQPw5gfEvy1eifSfuHV/Uy+WjETrg5uiPTridFDnrCJ4e9pKqDotbj2Tu4ICuoPXNgJ5J4DClIBjxAL9rKdhRl7eXmha9euOHv2bK3LSYAhDMvJN+XixYvV1jFM1+fX4ujoCA8Pj2p/TPtj/PBnseyuI9hz+yF8f2yUIpzYa1S4b1QkNj0zFrOGdGiQcGLAv/NEYM5mIKS/mJYqS/D1vucxwFNOrnQ0Wc4oyzBMyzjImvqfaKsq8H3+MXyYtRufHp9vM0Pu7mSPSH2Y9Im0AlF8VNBxhHGlRE7Y1qoCSlFRkdCOkKakNg4flusQGJYPGzYMx44dQ0ZGhrLOunXrhMDRs2fP5nSFaUecyy5HUr58A+gW6I61T4zBS1N7Nl1NTG81d61BUa8b8Ku7G5Z5uMPPW76ZGBxlGYYxf4FAon+EUYOSmRmHSr2fWahGfuDbCtF6LQqZm+Mz9dXQI4wCSmXiNkt1rX0IKE8//TS2bNmCxMREESY8ffp0aDQazJw5UwgqFJFz4MABsfyvv/4SIcSjR48W5iBi4sSJQhC57bbbcOTIEfz77794+eWX8fDDDwstCcM0hN0J2Up7ev9Q5c2lWdg7QT3lPbzvK98sz9sb98GOsgxjPkgjeVAfwePuaIfO/m7KsmSd0WQbRuYRG6I253opbBA+8vHBjSFBuDFrswV71w4ElOTkZCGMkJPsTTfdBF9fX+zevRv+/v4iRJjCh0kIoeRtTz31FGbMmIGVK1cq3ydhZtWqVeKTtCmzZ88WQoxp3hSGuRy7TASUYVG+ZhswFxc/9IHszJZip4KLfZpos4DCMOYjJa9UyVHUt4OXKDFhILnU6AIQFj7MpoY9plpGWVlAUTm64aC7N046OiBeIyEr66QFe9jGnWSXLFlS5zJyWiXtyuUgp9rVq1c3ZrcMg537v8I7R79GpJ078tIHUoC6CB02qFXNxdDuM7D/1GLRrnRNAvKC2VGWYVoq/0mN8OIUk0zRYW5hNjXupveiOH0kDzHQIxJHi06L9sHTf2GinzH7OlM/XIuHsQnOZhzGeQ2wWSqETpJTRw+O9IGdxryX8NBOVyltJ48E8ckaFIZpKQfZ6hE8yYXJSjvULdSmht3b1QGhXs6iHZdaILJaEwO6TVfW2a/hsi6NgQUUxiZIKDXWs8grixSfQ6N8zL6faN9ouNnLNnGNC0Wf6YQ6+qJJODPDMObRoPStqUHJkDOvEiFutheSGxMqa1FKKrQ4ly07yvbveh3UKvlRu//ifov2z9ZgAYWxCc65GNWn8eWy0/WwqNoTsTUHO7UdBgaRCQnQqorg4CirnI8lc2VjhmkuVKfmeKqcJ4SqF5PWwZSU/PPi01crwcXeWMfNlv1Q3Bzc0N1HNuucyT2D/HK+lzQUFlAYmyAhXza3oMoDFTp3uDvZVUuOZE6Gukcp7cHusr8Um3kYpvlQErMKfY6QmuadstJcZGj0IcYq26zLZhrJQ2YeAwMCByjtAxcPtHq/bBUWUBirJ6csB3nlslq4qtxffA6J9GlUQrbGMMxP1tAQFS5J4pMFFIYxb/4T0wRtRFlOPCYXFaNXWTl6OFh/FePaiNabeGpmoR7o20tpHzj8Q6v3q91UM2aY1iY+L15p68oDxOdQM4YX1yQyYhwCtBIKVYC9+InoWEBhmBasYEx4Fefgg0x9CoFRt9nkeAe4OyHA3REZheVCQKGcL1QhfYBPD6gkCZJKhf3ZdRfGZarDGhTG6jl34nel7VPh0OICCpV7/2H8l9gxaw/g8IX4mbCjLMOYT4Pi4qARWaCrkZtobHtH2OxwG8w8BWVVSM4tFW1Pr47ootOI9mlVFUpK5MrpTP2wgMJYPQmZxjcOvwoHeDrbo2dwy9Zj6thxDOwdXatnh2RHWYZpMun5ZUjNl6Pheod5XpoiIE92kBV4d2wblY1NzDyP9LgNX/W4D1uv/1ckhWQuDwsojNWTYJJdMq2sm8h/Ypp9siXpVUv6aoZhmll/p4aDLCHlnDNOeNmuBiXa5J4Ra5KwbdywpzFq8H/g7mFb+V0sCfugMFbPf/KKcGVVHs7aOeMbbYhZ09s3RECxQ/klb0MMwzSOQ0mm/ieXCiizSo8jLywYEVVafO0egtZ5BWnZlxqKWmKaDgsojHVTXoiY3BTEkPe7LgTfQN2i/iem7Dv8IxYc/Q6+3QoQljoKx1JuaJX9MkxbZPuZrDodZCWdDomqKhTZ2wNqe6jsmliZ3AoI9nSCj6sDcoorqjnKMo2HTTyMdZMl17AgzupC4eVij+5BNZzrWojislxskYpQolbDxe248MzP4IyyDNOkAoHH0woU/xM/t+rV6wsKLqBIb7YN08jp4m0VEkYMdXmyiytwsUDWwBLJybvx27on8dovExEfv86CvbQNWEBhrJtMEwFFChH5T1rL/2Rg9CxoJLmeRpZLjvhkPxSGaTwbThj9yK7oEXjJ8uQ0Y/KyUIfq2hVbxNS53tQ0vOnoPLyeug6/V6ThQPzfFuqd7cACCmPVHE7Zid1OjsjQaHBaal3/Ezf3YMRIclhzsoMK/nbnWUBhmCaw7vhlBJSs40o7zAZr8NSb8t7EUbZX+Gjj/OzYVu+XrcECCmPV/Jh9EPcFB2JCh1CcsXPHsE6tG5431Kur0u7ktoNDjRmmkRSWVWJ3gpyALcTTCT2CLzXRJuclGAUUT7kYqC1jKBpY01G2W6cpilY2tsxYAJWpHRZQGKsmoUr+cTvqJJTZdUOXALnScGsxNHKy0rZzjWcNCsM0km1nslCplR/KV/QMrNVhNKU4TWmH+va0+THu4OMi6oXVNPE4u/igiyQnbItXaTlh22VgAYWxWirLi5Gslm9swZUqDO0U0Gr+Jwb69LgRzjq5D8kuhcgoLGVHWYZpBOsvY94Rv61y2ceLCAvub/Pja+oom15QJjJRG4h2ksdAp1LhxBn2Q6kPFlAYq+V88g5o9W9bHhXOrRZebAplkx2glrU22XZqRDjGsRaFYRpIlVaHjacyRNvN0Q5DonxqXS9FK6eEd9FJ8PKyfRNPTT+UOFM/FD9j4cDY5O2t3i9bggUUxmpJSN2rtDXlPq3qIGvKUJMbSrjbXhZQGKaBHDifi7ySStEe09UfjnayecMUbVUFUvWa0jBoRC2stoBpJE9cqtEPJabjeKV9LPdUq/fLluBEbYzVEp99wjghdUDnVvY/MTC0y7VA1m7RdnC6wBllGaaBrDcNL+4pVyKvje/6Po2UnJOw11TPj9J2HGWNGpROHSfAabuEMrUKsRXG9P/MpbCAwlgtp/IvKO1A334Wy8bYpdNkvPLvkxicnw3vSntMLjDayxmGqR3KoGoIL9aoVRjXrXYBRWPngIF978TANjaQkX5ucLbXoLRSWy3U2M7eCT1VjjiICqRogJycePj4dLJoX62VtqFLY9okiVXyj5rC8np1HWuxfqg1drgxeCQiqqrgoSpFUBFllZWrsjIMUzvxmcVIzC4R7YER3vBykXMKtRdIKOupd5RNyilFvt7URYxwi8S44hL8JycPqvSjFuyldcMCCmOVkF06Wa0T7aBKYHiXcMt2KMooII1Qx7KZh2GamT22PRCjF1BqOsrO6XYLPs/Iwn35BfDOYD+UumABhbFKsnMTEVAF2EkSfCud0Mnf1XoEFE0cjiZzZWOGabj/Sd0Cyu4D32D73i+QmLgFOm1VmxrUaNOU9yYCCkJNQqlTDrZyr2wH9kFhrJKUUn8cj38PGlQgINrR8tVAvTrggE9HbJdysccpF+5J5wEYs8wyDGMku6hcRPAQ9HIR6Vf3C8aXx77BYVUlcALYe+MWkcysrVAt5b1JRll4RwLO3kBpLpBygBx2KHmKZTppxbAGhbFKdulTY2vhgEFdY2AN/B0QjO+9PHHMyQHF2ZxgiWHqYtOpTOjzG9arPSFSdBXi01cntSnhhOgS6AYHO/WlGhQSRkL6g7xSTlTloyDLJGKRUWABhbFKdicYI2WG1pHcqbUZFjZKaavtjrCjLMM0IHvslfX4n5RVliJTI2sOwpxat85Wa2CvUaNHkFx76FxWMYrKjSasZZ6eGBYRhptCg7Hr5O8W7KX1wgIKY3VUanXYnygLKIEejvWqh1uTwTG3QqV/KzzsrGZHWYaphbJKLbaekQvh+bg6oF8H7zrHKdW0Bk/okDY5ngY/FLLinEgzmnkCAnqhXJ+ULvYi+6HUBgsojNVx5EIuuoY+i2Hhr2K033eW9z/R4+nVEcEuXURbcsrA3vPGPC0MwxjNsyUVWtEe3z1AhNvWRXJRstIOcw9rk0NY3Q/FaOaJ7nyVcX4lJ2yrDRZQGKtj94n9iHeSEOtWjkxNPKyJYSFDlfaedGMqfoZhagsvrjt7LJFcaCKguLVRAaVaRlmjBsXPrzuCnf1FO05XAq1OFuoYIyygMFbH8Qt7lHaUi3XlT5gYafRDSSw+bNG+MIw1Zo9df1wuDuigUWNUF/kBXBfJWXFKO9QtFG2RroHusNNrkUxzoRAxAX3FZ2lVKc7ln7NI/6wZFlAYq6KiSofNhUZHsu7dr4Y10T+wH1SSHJ3v5HAQGflyFVaGYeSieOkFcpbl4Z194epYfyaLlMTNSjusjWa9cLLXoEug7Ch7JqNI+OgYiPEzRigeyzpmkf5ZMyygMFbF0eQ8aO3SlemoYOuq0OFk54RelfLPpsi+ArtiN1q6SwxjNRhq7zQ0e2xKVZH4pISMgf7WkU6gJTPKanUSTqYXKvN7mVRKj82KtUjfrBkWUBirYld8NtSOcgQAEeUVBWsj2sWYoO1I/HKL9oVhrDV77ITL+J9QWItTVQWcdToE6VSiaGBbJcYko+wxE0fZnj49YHAhjj31hwV6Zt20TZ0aY9MRAGoH+SbnYe8JHyfryIFiyqgeN+HEtmSUFndHatB0S3eHYayC1LxSYeIheoV6ItjTuf4vlOZiYUoqKHK/KHI02jKmjrJxJgKKq4MborQqxGsknEY5ysvy4ehkFGbaO6xBYayG8iotTibFQ20vq0A7O1tn4qYRfa/D4ZyXsb/gOhxOd7R0dxjGKthwUnaObXBxwNxE8UEaBHdK/d6G6RHsoWSyr5ZRljSyTrIjsY8OSL/IlY1NYQ0KYzUcvpCHQE0cDIGHUeXW6YCqVqsQHeohst2SQ2BmYTn83VlQYdo3ptljr+h5GfMOkUf1rPR4d0RbxsXBDp383XA2owin0gtFMIAhBf5DY+biMTsXBAS2XR+cpsIaFMZqoAe+l5Mx1C7Kw3pvWqTCri35EsO0RyiFO/mPESGeTugZbDRpXE6DIvCOQFvH4ChbqZVw+qLRUTY0dDALJ3XAAgpjNexKyEKfskq8mJWDWwoK0S94iFU7vflpkjHEcwk27fmPpbvDMBZl2+lMVGh1oj2hR2CDsj9/k7oZjwb44T0fL2S7Wp+vWUs6ytbMh8LUDpt4GKuAcgMcvJCHe1VZuKJQDj1E5JWwZg2KZ+TnOG6vxllJwouluXCi8ukM0w5ZZ5o99jLViw0cKE3DLlcX0Z7j2QFtnehqKe8LcPMgi3bHJmANCmMVHLqQJ+yynVWp8gx7V8DTelNfd/R1RWiZrLKtUKlw+PhSS3eJYSxClVaHTXoHWVcHTYOrj6doZR8zV50EL6+27SRLkN+agd0J2SLrroFjccswd+k03DqvP/Yd+sFCPbQ+WEBhrAL6wTqiAuEqfSSAXxcobu9W6ijrrTImWdoev9ai/WEYS0Gaz9ySStEe080fjnaay35HW1WBVLX8gA6FBip9Vd+2jIeTPQZEeCsZZQ+cNxYIPHfxEBaXnsdRdSWOJG21YC+ti7Z/VTA2k/8kwi4BB50dkK1WQ/LrBmsnKPg6pb230LqKGjKMZYoDNsy8k5FxDFX6F5AwjRvaC7cOMZqyFu0xVkOPiZygtGPzz7Z6v6wVFlAYq/A/oRBjL9djuDs4EGMjwvCTg/xGZs30jOqDDuXyW+BJTRXy8403HIZpb/4nVA9vXLcGhBdTkcCMI0o71ErzHbUEV/UKhpeLvWj/fSwNOcUVot2xwxhh6iKOVbIDrQEWUBiLc/B8rogAcHLU+5/QW5Vvd1g75CjrWyLfXCWVCvuOLbJ0lximVYnPLEJCZrFoD4zwgbdrw9LVJ2efbPNVjOsqHHjjANm3jnzufjuQJNpqjR2iVU6inaFRIeMi1+UR42LBc8UwinmHqHIw2mSjQqw3xNjUUba8zJhcaXcy246ZdmzeaUhyNj0pBUZtY7hPF7QnZg0x5nxZvOcCdHrNSYy7cX5s/GqL9M2mBZTXXntNxLeb/nXvbnzTLSsrw8MPPwxfX1+4ublhxowZuHjReAETFy5cwNSpU+Hi4oKAgAA888wzqKqqMt8RMTbpIEvkOZQqlU3DQ4fC2iFHWTvPqaK/xK4SQw5chmkfrD/eyPT2epJLjM+FUL/2lUE10s8VIzvLmtfE7BLsiM8S7V6Bxsrtsen7LdY/m9agREdHIy0tTfnbvn27suyJJ57AypUrsWzZMmzZsgWpqam4/vrrleVarVYIJxUVFdi5cycWLFiA+fPn45VXXjHfETE2RWmFFoeT8qBBBdL12uEInRp29rK609rpER6ByDI5auGCBkhL5RsL0z4g/4n953NEO8rfFVH+DXd2TTHxswgJHoD2RjVn2d2yNimm02RlXmyhSZbddkyjE7XZ2dkhKCjokvn5+fn44YcfsHjxYowfP17MmzdvHnr06IHdu3dj6NChWLt2LY4fP47169cjMDAQffv2xZtvvonnnntOaGccHNpuuW2mdijUjlI/hzucRZ7eqz/KvgFpsq2EXmGeOHsyBANxFkPLymCftB8IMb4JMUxbhXKf6K0TuLIR2hPipogp6Jt9HHkVhXB2aftZZGtCyewC3B2RUVgunIwvFpQhMLAP/LQSsjQqxOpKIOl07SL8uj4affRnzpxBSEgIoqKicOuttwqTDXHgwAFUVlbiiiuuUNYl80+HDh2wa9cuMU2fvXr1EsKJgUmTJqGgoABxcXF17rO8vFysY/rHtJ309oS/kzG0LsqGnOYofXVh9pWYl56B+/MK4JfMGhSmfbDhZOOzxxq4etzbeOqGFXhz1nq0R+w1atwyKFy0tToJS/YmCWEkxk5+OStUq3AhaQfaO40SUIYMGSJMMv/88w++/vprnDt3DqNGjUJhYSHS09OFBsTLy6vad0gYoWUEfZoKJ4blhmV1MXfuXHh6eip/4eHyiWXaRoFAwtXB6L8R5WP9ETwGIn1dEe/QDUWS3iSVsBkwyRDJMG2R8iottpzKFG1vF3v078BlHhrLzYM7iNBsYsm+CyIj7xTfvpiTm4/PL2bCP8ek2nM7pVECypQpU3DjjTeid+/eQvOxevVq5OXlYenSlk3z/cILLwgTkuEvKUkOzWJsm+LyKhxJyhNtjYssqBBRQbZjkyZH2W4hPtit6yHPKM4EMo5bulsM0+IvFsUVWtEe3z0QGsOTlmkwoV7OGN9djnxKyy/DplOZuKrb9Xg0Lx/jSkrhks6hxs0ycJG2pGvXrjh79qzwSyHnVxJYTKEoHoPPCn3WjOoxTNfm12LA0dERHh4e1f6YtuF/UqU3YmvsJWgkCSpJQscOo2BLUD6UHboYUC3XUw72iDu+zNJdYpgWZf1x0+yxDQ8vJrIyT+DixaPQaTl689ahxtDihbvPAyH9jQOVcgDtnWYJKEVFRYiPj0dwcDAGDBgAe3t7bNiwQVl+6tQp4aMybNgwMU2fx44dQ0aGMTRt3bp1QuDo2bNnc7rC2HD+E+K6wcuxd+Yu/Dn2vzZXFZgcZbeoIzGuQyhuCA3Gl0n/WLpLDNNiUJG79fr8Jw4aNUZ19W/U93/c/Dyu+OdWDPq5L47E/Yr2zOgu/gjzdhbtrWcycaHUCfCJkhemHwW01p9R22oElKefflqEDycmJoow4enTp0Oj0WDmzJnCN+See+7Bk08+iU2bNgmn2bvuuksIJRTBQ0ycOFEIIrfddhuOHDmCf//9Fy+//LLInUJaEqZ95j8hhkT5wMHRHZEdx8LWIEfZhMqulE5WTO/XFqGyXM6uyTBtjbjUAmGSIIZ18oWbY+OCQVPKspQq4P7endCeIdPYzMFyyDG5ri3eewG64H5IsLfDX04apJ5v38kfGyWgJCcnC2GkW7duuOmmm0RCNgoh9veXJehPPvkE06ZNEwnaRo8eLcw2y5cvV75PwsyqVavEJwkus2fPxu2334433njD/EfGWDVF5VU4miznQugc4IYAd9vIe1KXo6ybowPCSuU8EKVqFY6m7rR0tximRTBoT5oSvUMk28kCjZ0EBAb0RnvnpoHhsNfILzfL9idhoYs9rg0LwUv+vth+dhXaM40SfZcsWVLvcicnJ3z55Zfiry4iIiKEcy3TvtmXmCPC64hhUb6wZchRtmeIB+JyxgHuf4t5u/NPYwCutHTXGMbsbDiR0WT/EzIPpUjloh3sEQ6NHee+8nd3xKToIKw6mobs4gpI6l4A5BecuOz27SjbvrPAMFZh3nEpeQvPLByNr/+Yhfw828ygSI6y+cV0Y5HZk7bHov1hmJYgLb8Ux1JkzWdMqAeCPWX/iYaSV56H4sridlck8HLMNnGW/fd8FxEwQByDXO24vcICCmMRdscbBZRT5WfwjzYXX+UfA1RqmxVQpCovaMtlc+fRzKMoqiiydLcYpgW1J40376QUpSjtMHe5qi8DDIn0QSd/VzEUOxOrEO4hF1CMr8xDSWVJux0i23waMDZNYVml8hbWNdAN5yCrfH11Ejw9jTUqbM1RltAWd5Y/JS0OcHVjpi37nzRBQEkuMCYfYw2KESq8e6tJlWOUy/dBnaTDiZwTaK+wgMJYxP/EUMNjQEdH5OiTPEV5d7PZsxHl5wpXBw28SuQqpcTu/V9btE8MY+7EijvPyprPYE8nRIc0Ph9VcpwxR1BYmVy9nJGZ0T8MTvbyIzkxxeiXF5vVfv1QWEBhLJbenugQZDSDRAX1s2lH2ehQT5QUd4Nabz/eXcSpqpm2w7YzmajQUjpCYEKPAPHW31hSitOUdphrsFn7Z+t4utjj6t4hol1caByb2IsH0V5hAYVpdXaZ+J+4uhvbUZ76BEU2CvmhFOr80LFcDS+tDp0dvFDZju3HTNti3fHm+Z8QqeW5Sjss2HZKWrR2ZlldeSDsdbIAeCxxI9orLKAwrUp+aSXiUmX/k+5B7kgvNWoZorxsX0Ahki48ips6/IYPZm+Fvb2LpbvFMM2GUgJsOiULKGTKpARtTeHLvHKsSUrB95mF8PQ08blgBH3CPEV0FKBBhOyahxQNkJsT3y5HiAUUplXZd87ofzI0yhcJ54xvB1Hutn3DMjjK5mhDEJvGmWSZtsOhC7nIKZZDXkd39YejnabxG9FpYZefjLAqLYa4hkGl5sdPfc6y7mU+8NDqMAIuKCwymsbaE3yFMBbLf0ICyjl92KGbToK/S9PUxtbmKEvEphRYujsMYzbWNTN6R1CQAuj0BQK9bftlpCW5pk8I3B3tsOfiQ8g59wHev3k7OnQYifYICyiMRQoEkn9dnyAdUvUvYlGwt/k3KuEoGyJrUVLySsUbZ0lJFkqKjLZ7hrHl6sUUcDeue+OyxyrkmjiNe3c0U8/aHq6OdpjePxTlkitKKyWsOGjMHdPesO0nAmNT5JVU4HiarFnoEeQBj5LzeC47FzcWFGK8S9tI2mQw8/Rw3oHHfh2KEUvH4s/tXGuKsV0SMosQnymbLAdEeMPHtWnp6fclbcXn3p743c0V6a4+Zu5l28I0J8rC3edFiYD2SOPKUDJMM9h7LkdU7DSYd1zzYjG7oFCe0W9CmxjbXmFybogqyRGHNVQqXYU9mYcw09IdYxgLZY81sDv7KL7zkgX4L+01COIzUifdgtwxqKM39iXm4kxGEfYkZGJAB7d253TPGhSm1c07hIgCyDxlXOhvu0naaovkOVvWF576nBF7q/KhrWrfNTWYNuJ/0oTqxQYSTNPcBxjrVjF1a1H6uK3FwIiX8PjWcdi4+6N2N1QsoDCtnqCN/E8Gd/QBskwEFL+ubeJMRPq5wcVBAwl2iCyTa2sUqlU4fupPS3eNYRpNbnEFDpzPVZzAO/m7NWkU09MPY7M2T7Q9dRLCQ4by2bgMk2OC4OZQhVMuWhSr1TicdqDdjRkLKEyr3ehO6P1PKEU2ZU08kX0S+eR1p3FsM05zGuEoK5t5tEXGY9odv9KCvWKYprH5dIbIgdJc7cni7a+jSp959mavaNg7ysI7UzdO9hr06nyVMn204EK7Gy4WUJhWYc85Y3r7oZG+IsPqLJcyjIwIxz2hIYC6CXkVrJReoV7iM7HI+Ja4O+e4BXvEME1jvRmyxxYVpmFZ4RnRtpckzBz1Op+OBnLL6LEIqJRNxWc15ais0GdvayewgMK0ev4T8j9JSt6tvFF5OzS+6JgtOMqmVnRDcJX89nkIZSgtMQppDGPtlFdpseV0pmh7u9ijfwdZ8G4sv299BUX6gqDXOIbAz6+7WfvZluno54pwraxtKlGr8feev9CeYAGFaVUBhe5TgyJ9cC51r7IsyjW0TZ0Fg6MsEVUlh1NWqlQ4FPeLBXvFMI1jT0IOisrlxGqU+8RO0/jHBWlKf764S5m+fejzfBoaSQ+PLkp7+/E17Wr8WEBhWpzsonKcTC9U8oR4ONkjIdto8ojybVtvVAZHWaKi2Hhsu8+vt2CvGKZxrDdD9th/tr+DixpZezJW5Y6oyPF8GhrJmK5jlXZG+Wmk5Ze2mzFkAYVplfwnBij/CZFQmKTMiwwZ1KbOgqmj7MHsIcr8lHyTTJoMY8VQYjBD/hMHjVrU32kK8TknodInP7qj9xyz9rG9ENN1mjKGeY75WLLXeO9s67CAwrRu/hO9gBJfIYcuqiUJHcPbXp0JQ0bZPG0Q3i9yxMYLyfgoKR5gPxTGBjiRVijKNRBDO/nCzbFpOT0fn/EbVo3/Hx7zGYABvW83cy/bB27uweiokx/VSY4Sft97AlX6HEttHRZQmBZnV3y2olkY2NEbOm0VEiHbtsN0Kjg6ti0n2Zp+KMEOg+FvuKFcMNrjGcYWzDtX9mhi7R09VOju3qvn23ytLUvSy0nWYFFggVvVXqw3ye7bluErhmlRsorKRapmg1bB3cke6RcPo1Tv1R9l594mz4CpgLJLa+Jjk7jdMh1imCYKKBOakd6eMQ83hIzGBxlZWJOUgkEVBVi0p32Yi1lAYVovvNjgf5Js1CJEurbNihxR/kZH2T9zqfCXLJCxgMJYe2jxN1vicTQ5X0yTL1WIl3Ojt3Po6EIRwcOYh35dpmFycQnCqrToq07AtjNZOJ8tF3Bsy7CAwrQoq4+lKe3hVH8HwMX8RMXpK8rLGELXliBzVs9g2XR1Mt8O24O64i1fb0zXZCA/v/04uTG24xS7Ni4dEz/ZirlrTirzp/YObvS20tMO4e6D72LKz4OxbO0TZu5pOyUwBtDIVaT7qBLE5+I9bT+zLAsoTIuRX1KpZKL0c3OQCwQCmHHlR9h78zb8NmwuxvRru579vcKMZp5/XH3xq4c7zjo44NCJpRbtF8OYcjK9ALN/2IM5Px/A+WxZ60E5FGcN6YD7RkU1erAW7pDT2lN48cVi4wsK0wzsHGUhBUBndSrcUYKl+5OExqst0zTXbIZpACuPpqJC7xx6TZ9Q2JskenJy9ka3rtPa9Dia+qF42PUGKpJFe3/SNowd+pQFe8YwQE5xBT5ed0q8ievL7QiGRPrglat7IjrEeP02lMKKQvxWJlctduC09mYlOzgGB/JOINbREZ3z9uFQyRisOZaO6/q1rUSXprCAwrQYyw/KD2RixoC2+yNqiICSXEGh1KtFe59j26k7xNgelVodftp1Hp+tP42CMjmajgjzdsZLV/UQVXRV+jIUjeW307+hWFsm2tdEXQ1fv25m63d7Z7urK14OlKN5+lbGAaVjhLMsCygM00jOZRXj4AW5vHr3IHfFH6M9YXCULanQ4mC6K7r06IIzuWdwMu+seNN0d2ibEUyM9bLpZAbe/Ps4EjKNDpZ0jT48rjPuGRkpKug2lUptJRaeWCjaKqhwe5+2a761BL0irwSS/pYnXDOALGBfYi5OpReiW1DbvJewDwrT4tqT6/uHKm9kx0/+gRcWjcN3f92OU6dXtenRN3WUTc4tRS+f/qKtk3Q4lHHIwr1j2hNnMwpxx497cdf8fdWEkxsGhGHz02OFgNIc4YRYk7gGGSWyz9nY8LGI9Ixsdr8ZIx07jIGrJN9Hz7kaz1VbDjlmAYUxOzqdhOUHZTs0pTu5rq/RvBN7fhNWVWXh89xDOHxubZsffUNGWcLXrofS3p++30I9YtoTeSUVeO2vOEz6dJtSmZgYGOGNvx4ZgQ9v7IMAD6dm70fS6TB/59vK9J3RdzZ7m0x11Bo7RAfLZUHypWI4O8n5peheW6wv6tjWYAGFMTt7E3OUNNmjuvhXuwEm5MshckRUQJ925YdSWdxRae8/u9JCPWLaA5QKfcHORIz9cDPm70yEVu8FG+LphM9n9sOyB4ahd5iX2fa388BXOKOTI4B6q1zQL6Cf2bbNGInxkyN5iCHdZU0YVZxeeSQVbRF2kmXMzu8Hqpt3TEnwDARKE0U7sh1UNjUNNY5PBzppVYjXSDhelonionS4urXNRHWM5dh6OhNvrjquZHAmnO01eGBMJ8wZHQVnfQJBc/LT8Z+U9p1R1zbZyZZpuIASFpwNHJaz/C7ccx43Dwpvc+POGhTGrJRWaJXkbO6OdpgUXf0BnFAgCyceDh7w9TRqFNoqnfzdxMOBoOycA13DRFurUuHQ8WUW7h3TlkjILMI98/fh9h/3VhNOrusbgo1Pj8FjV3RpEeEEaUfwctJZzMovRFctMH7o0+bfByPo5ddLbgDIyD+A3voXoNiUAiX7b1uCNSiMWVl7PB3FFXLyoKt6BVdzvCuqKMLFErnGR5RnVJuT9utylI0J9RDe9uQoO2DENHhmbsHADuPQt8dNlu4e0wbIL63EFxvOYMGuRFRqjQlN+oR74dWre6J/B++W7cDO/yK8SosXcnKhG/Ii1HZyxlPG/AS6BMJXUiFbJSE2Oxb/GRSmCCYLd58X57wtwQIKY1Z+q8e8cy7/nNLu5NWp3Yz8lT0DhYBCnC2/Eo9Of8jSXWLaCDvjs/DI4kMi6ZqBQA9HPD+lO67tEwq1vihni5GXBMT+LredfaDuN7tl99fOUalU6KV2w2apEIVqFfr5JcLdyQ6FZVUiMebLU3vC08UebQU28TBmIz2/DDvOZol2uI8zBnX0qbY8IcEYtRPp3LwS7rbE1N4hSptuIgxjDiqqdHjy1yOKcOJop8Z/xnfGpqfHYnq/sJYXTih6Z/fXgKRPtz74PsDBpcX32d4Z6BuNAZIj7nTtDHdnN8zoL5uNyyp1+DcuHW0J1qAwZuPPwylKyuzabpAJyTuVdlRl2wyLq41QL2cMiPDGgfO5OH2xqE0nVmJaj7+OpCK9QM7a2r+Dl4jOCfNuPQGhID8Js5P/wHRPd9xQUgX3Qfe12r7bM3dM/Q53mExP650jIrWIbWezcNOgcLQVWIPCmK0a6u+mydlqqQ+RYFI4LCp0aLsa+atNqsKuPJyMhHMbsXTt4/hn6xsW7Rdju7+377YaQ/ZfmtqjVYUT4retr+KcvQYf+3jji079ADc5DTvTuvQJ9xIBCQRpsCkPVVuBBRTGLMSlFgjtgCEJVEc/10vWGV9cgusKizCgvBLBQXJW1fYCOQwbfIK3xe7FtVsfw5tpG7A44U9Ld42xQSjp2qmLhYr2ZEBEdXNqS1NZXoxFmXtFWyVJmDX0+VbdP2OEirAO1VeKJ3Pf8bQCtBVYQGHMQjXtid4mWo2qckzPOI83s3IwX+cvsiK2JyhZ3dBI+SZyJMsPHfRm+2MoR2lJjmU7x9gc35poT+aMbn2H89U73kSGRpa4x2k80bHjmFbvQ3tH0umQkrIX+XmJGNXFT5m/Xe8H2BZgAYUxS3XUvw7Lzp8OdmpMNTFnKGTH0y9Kbvu3zwqn0/oYxyVKJwsrVSoVjpzgfChMw4lNycfO+GzRjvRzFVFirYlIa39+jTJ9V98HW3X/DLBhx7sYu6A3Jq+/B2v3foaRnU0ElDMsoDCMwpZTmcjWRxLQzdLTuZYwt6xTxnY7LcE+JSZY5EUhSgqMhdT2X9howV4xtsY3JtqTe0dFKtdUa7Fj/5c4q5ZfNvro7NG3F4cWtzY+7mHI0Z93yodCgio54xtKjZRV6lW0Ng5rUJhms/yQ0bwzo0buEwNZ6UdQbHDC8O/aLkfdx9VBedM5ljNQmb8v/6wFe8XYEkk5JUqmZl9XByXEtDWZf8IkrX2XG1t9/wzQvfNV0EiyM+yxsgyRH8Vwb6Hw832JbcNszAIK0+xqqeuPyyXW/dwcRHHA2ng/bROGdgzHFeEhSHNtXYc+a2Ka3vyVUdURoVX6GwzKUVYqJ3JjmPr4ccc5pfDf7cM6VsvU3BocP/kH9kAObSY/qnFDn2rV/TMyzi4+6CzJ5z5epUVJSRZGmvihbGsjZp5mCSjvvvuukNwef/xxZd7YsWPFPNO/Bx54oNr3Lly4gKlTp8LFxQUBAQF45plnUFXVfvJitCVWHU1DhVZW917bN1R4lNdGQmWe+MzSaODXziJ4TJkYHQQH/RgFlXqIz0qVCsdO6rNxMkwd5JdU4td9SaLtZK/GbcMiWn2s5u//RGnfHjoOGk5rbzFinGTfI51KhRNn/saIzn7GSMH2LqDs27cP33zzDXr37n3Jsvvuuw9paWnK3/vvv68s02q1QjipqKjAzp07sWDBAsyfPx+vvPJK04+CsRjLq0Xv1G7e0VZVIBGyTTRcp4a946UhyO0F8s8Z3VXWMpUVRSnz9yVusGCvGFuAKtaW6Otc3TQwXJgMW9s5NtDJB846Cd46CdeMeq1V98/UXdk4NnmHuB6iQ+SXnhNpBcgsLEe7FFCKiopw66234rvvvoO396WFqEgzEhQUpPx5eMiDRqxduxbHjx/HwoUL0bdvX0yZMgVvvvkmvvzySyG0MLZVPfXgBVkz0j3IHT2DjefZlNS0/SjXO3RF2XMG1av10TyJRUOUMdqff6ZVzhljm5DT47wdcrZQ+indO9Io3LYWKrUaT92wAuuuX41P+j8jzAyM5egVMV5px+aeFJ8jO/tXq9PULgWUhx9+WGhBrrjiilqXL1q0CH5+foiJicELL7yAkpISZdmuXbvQq1cvBAYaQ+MmTZqEgoICxMXF1bq98vJysdz0j7E8Kw6lKG1y1qurOnFCym6lHeVqrEvTXrmiR6BQ0adXRaFzuQ5ji0swMTcTqJRt+wxTWxmJrKJyJRqsg6/lat54enbAgD6mydYZS9Ap8go46f2RYitkHzbTfChtwczT6GxZS5YswcGDB4WJpzZmzZqFiIgIhISE4OjRo3juuedw6tQpLF++XCxPT0+vJpwQhmlaVhtz587F66+/3tiuMi0IpVNefjBFeaO7tm/dgkdCllHwjPJunyHGprg62mFC90D8fSwNsy5E4Ua7rfKClANAxxGW7h5jhb8108Rs941ufe0JY33Y2Tuhh8oRh1CBZA2QmxOPARHkOK0WhQMpHwqVRKjrxbHNaVCSkpLw2GOPCQ2Jk5NTrevMmTNHaERIS0JmoJ9++gkrVqxAfHx8kztJWpj8/Hzlj/rBWJY953KQklcq2hS5Q5lS6yKh4LzSjgpuvw6ytZl59kg9jDMTt1uuQ4zVsvFkBuIzi0V7cKQP+oZ7ter+K8oL8dPqOaI4IGNdxLjKYeYuOh0uJG4UUV2D9RmrqZBkfKZcfqRdCCgHDhxARkYG+vfvDzs7O/G3ZcsWfP7556JNDrA1GTJEtrOfPSvneiCflIsXL1ZbxzBNy2rD0dFR+LGY/jHW4xw7Y0D9uRgSyo0x+ZEdRrdov2yFsd0C4OqgwW5dT+PM8yygMJdiqj253wLak9Xb38IHmbtw5fIp+HMj19yxJmZGTsOK5DTsPJ+MPgXyfXZU57Zj5mmUgDJhwgQcO3YMhw8fVv4GDhwoNCXU1mgujcmn+URwsPzGOGzYMLENEnQMrFu3TggdPXua3KwZq6W0Qqski6IqmhPrSbVNnv/nIDs/B2sluLgYfzztGXrToZDjZMkfyZIfKgEcunhIvK0yjIFDF3JFZlCic4AbxnULaNXBod/vggv/iHaJWoWIgEujNhnLER41AZ0rK6ExmIjJUda0Lo+NCyiN8kFxd3cXjq+muLq6wtfXV8wnM87ixYtx1VVXiXnkg/LEE09g9OjRSjjyxIkThSBy2223ifBj8jt5+eWXheMtaUoY6+ffuHQU68MdqUpvfcmisnNOo9AQwaNpv+HFdZl5yNH4I48QbPdxQplajQUnV6B/n9st3TXGSvhum4nvyahIqFs5rf321B1KWvt+cELfmFmtun/mMnhHAs7eACV6TD0ISJKIqPRzcxRO1bsTskWttLryU1k7Zu21g4MD1q9fL4SQ7t2746mnnsKMGTOwcuVKZR3SsqxatUp8kjZl9uzZuP322/HGG2+YsytMK1Uuvpx5x8+vO3bPWIdfBr2CRwc/y+fFBAoJpLwo6VVhQjgh9p9fx2PECM5nF+OfWDlwwN/dEdf1qz3PUEsyP26+0r5j7Lt8ZqwNlQoI0fv1FWcC+Un6tPeyHwq9SB7Sp4KwRZpd837z5s1KOzw8XPikXA6K8lm9enVzd81YgPT8MuzQl/MO93HGwIhL8+DUxNUtCDE9uWZHTajy8+ToIGw/OogCBcW8faXpmNMC542xPb7fdg76KFLcObwjHO1aN619XHYc9qbvFe0IjwiM6zCuVffPNIxzAZ2xJns/jjk64KZjP2PcqJcwsos//tBXmN9+JlM4V9sitqn3YSzGH4dTlJvm9H5hra5ybmtM6xOMlIouUFfK5q8jVfmo1JFHCtOeySmuwLIDctSMi4MGs4e0flr7BbFG7cntPW+HWsWPC2skzbcjvvb2xHYXZ2xM2iTmGQoHEltt2A+FrzimwVBM/e8HLl+52EBW1knhZMfUzbAoX/i6OqG8pIuYLq0qRZxJ3himffLTrkSRy4K4ZVAHeLrYt+r+U1L2Yu052TnWx9EL13S6plX3zzScATG3ivIDxI6ydHHPDfJ0QpcANzHvaHKeqONki7CAwjSYuNQCnMmQ4+rJtBPhW7fTK/1I7lt5M25a0A9rtrzGgkod2GnUwtFYW2IMH91/cT9fle08rf1Pu+TcQRq1CneP7NjqfVi48y1o9crRW5wj4GRXd54jxrI4OnlikD4fSqZGhdN5Z6pF85DssivBNrUoLKAwDeY3E+3J9f3rd47duu8z4f1/Uq3DwoS/eJTrYVrvYFQVmwgoabVnaWbaz++MTDzE1F7BCPNu3bT2lamH8G+hnFiTUqnfMoqzeFs7I3oZI/+2pWxrM2nvWUBhGgSFqv11JFVx7pzaW85rUxc/pBqdpe/tPksUGmNqZ1BHH/g7h8CpSq5OeyhlByorjfWrmPaDVifhe5PQ4jmtnZjt+J+wn3cV/khOwZM5ubjbrTO8fTq1bh+YRjMqdJTS3pGyQ3wOifSFvUZWg23XBzbYGvzUYBrEllOZylvdlT0DRXhsXRy8eBCHCuQ3sE4uwRgz+HEe5fp+hGoVpvUKRddSjZIQ68RpY2g+035YdzwdidmycDqisy9iQj1bZ8fkK7ZpLrD0dqCyBB46CXe5dcWDU39snf0zzSLcIxwd3DuI9uGMwyiqKBI1v/p3kKMsz2eXICnH9l56WEBhGp/75DLOsd8f+15p393/Eag1zY5mbxdJ26QS2dcguEpCXlHthTOZtu2E/o1JWvs5o1tHc1FSlIFnF43Bwd2fGGf2vgW4czXgYpvhqe2RkSHDxWeVVIU9R35sE2YeFlCYy5JXUoENJ+TSBH5uDhjdxb/OdU/lnFJsoMGuwZgSOYVHuAFQAbhsaQZcz8xBfPz7iI5+gMetnXHgfK6SVIuygY42ebi0ZLTObcuuxBpdHp4I9EOanT0w8S1g+v8Ae3aMtSVGqOWoHWLb2VXik/KhGNh+NhO2BgsozGVZdTQNFVo55PHavqEi8qQuftxsLCZ2R/QdsFe3bnikrULZH8f17oP0qijhh7BGn0GUaT+Yak/uGxUlromWZN/hHzFz7d04rU9lX6FSI3nym8DwR+UMpYxNMSjmNjhIcrjxztJUETnZK9RTMcfvOJst7i22BAsoTCPNO3VH7yQl7cI/BXKImzc0uL7L9Ty6jTTzGFipd0hm2gfxmUVYf0Jf1d3DCVf3CWnR/S399zHMOfwxcvWJFjtqgUXjvsCggQ+26H6ZlsPZxQcP+Q7COx2uxS/XLBeBCRSmPryTnPY+v7QSsSn5NnUK2DmAqZeEzKJqaueeIR51rrtg5xvQ6d+8bvWKgbOdM49uI+gZ7IEoP1ckZBWLCrapuQUI8a57vJm2A0Xu6F9+Rd4TipRrCSg67L3fZ+DX8mRFSzICLnhvxm/w9AxvkX0yrcc9V8+7ZB7lQzFoZCmap0+4l82cEtagMPVC1XYboj1BUQamJx7FxKJiuOl0uGXsOzyyjYRU+tOiXTE66APERD6PV5dfyWPYDsgsLMfvB+XfmZujHW4ZLEdjmJvcnHjcv2i0LJzoucOlE/5761YWTtowozob/VC2nbG8H8ofJs+Uy8ECClMnOp2E5fobJ2mCr+1Xj9p599eILi3CR5nZ+DdoKjw9W+Ym29aZ1rcrEjwykegIxKqLoK2SQ7uZtp3WvqJK9gOZNaQDPJzM77dVVVmGu/6Yjn2qcjFtL0l4O/xqPH3jH7CzczT7/hjroYOvCzr4uCiO2MXlVRbrS3JuCV79q+GlPFhAYepkz7kcpOSVivborv4IcK/Dq78sH9inDy1W28NjBOc9aSpdgz0RVS6XEChSq7HryJ98hbZhSiqq8PNuOa29nVqFu0a0TFp7O3snzOk0XbT9tBLmDXwZ14xnLWdbpKQoA5t2fYA3l0zGnoPfVkt7X6mVsPdcjsX69uP2xEY56rKAwtTJ8oMNTG2/fx5QXiC3+9wCeLSsg19bp7NrD6W9Me4Pi/aFaVmW7ktCnr6Q2zV9QxDs2XJ+W1eNeR3/FzQeS6YuRp+YW1psP4xl2XPsJ/zn9E9YWp6CdadXiHmjOls+HwoVLFyy70KjvsMCClPnm93qY2mi7e5oh4k9A2tdr7wsH/ee+A4r3VxQCRXA2pNmM6HXdUr7dMlpvkLbKFVaHb7ffq5F0tqXlGRh5aaXL5l/06TPEBjY22z7YayPIb1uh53e43p7SbIINx7eyU+Y6S2ZD2XR3vMoqdA26jssoDC1sjbuIor1FxPV3XGyl9Ow1+TPra9ij4MaL/r7YW7nvoBfZx7RZjKs99Xw0OedSXAoQXyGbYUGMg3jn7h0JOcaTajdg8wTsZWauh+3/zoBL174E39uNOYlYtoHLm4BGKCSNXEpGiDxwlZ4utijd5gcvXP6YhEuFpS1ap/Kq7SYtyNRtBuTYocFFOayuU/qMu+Q49285A3K9IyB/+HRNANUGqCn5C7ahRo1Vm5fyuPaBtPaf2uSmO1+M2lPDlw8gJkbH8YpffK1j8+vEj4JTPtipG8fpb3jxJJL0t5vb2Uzz5+HUkW0GnFFj4AGf48FFOYS0vPLsENf/TLcxxmDOsoFp2qybte7SNYrVobBGdHdOTGbuRjsZ1TDn0xey1dpG2N3Qg6OJsuasegQDyWZVnP47fRvuHftvcjRykXhOmiBeWM/E2/UTPtiRPcblPb2jEPic6SJH0prVjemaNBvTSp03zG84Y7gLKAwl/DH4RQYHK2v7xdWa8ptsmv+EC87YBH39LqXR9KMjOpxtdLO15zDqfRCHt82xLdb5WrfBt+T5qS1r9RW4J097+D1Xa+jSieHkA4NGoLF169CVOQEs/SXsS06R01EoFa+ie+TilFamot+Hbzh4qBRBBTS4rUGm05l4GxGkWjTy27f8NpfeGuDBRSmGnTR/n7A1LxTe+XiHfu/VNTIMTo7DO7LAoo56dppiuKHkuxcipWHk/hKbSOcvliITadkR8VQL2dM7WUscdBY0tMO4cGFI/DLyV+UebN7zMbXV/4Pnl4RZukvY3uo1GqMdJajKStUKuw/9rPITjw0StbUkbnl1MXWeen5thkVullAYaoRl1qAMybSboSvnJOjJj8cX6C07+16s/hBMOb1Q3nCLgxfpmdgdVIK4o7sabU3HqZl+c7khn33yMh6i2/WCiXvi/sDx3+ehkn/3oY9kB0e7VQavDH8DTw3+DnYqbmKSXtnRPhYpb09ce2lZp5W8EM5kpQn8mkRnfxdMaF748yN/FRhqvHbgcs7xx6OXYz9+oyUHbUqjBv6NI9iC3BDl2swurQM7pKE8IJDQnhkbBuKniATKuHhZIdbBjW8/k1p6iHgnxeBj7sDy+5At/htCNTKkXY+Ogk/9nsW07vIydgYZmjvO6DRv9TsKDp/iaNsa+RD+bZGhW61Ida5gbCYzShUanX4S19Fl9SBV9Whev7h4H+V9t0Rk8XbPtMCRIxQmkPUJ0SF45hQTx5qG4ZCLSmbJzF7aARcHev/7RQWpOCf3R9gRcoWuJQX4ft0Y0QOeRPcWW6HPN9euGnkK/Dz697i/WdsB3ePUFwHN3jlpWJEaRmk7Hh0DohCoIcjLhaUY8+5bBH+62hXewqJ5nIhuwRrYuVcWn5ujriuX+3uAvXBTxZGYcupTOQUy7VfKDGbp/OlNUGoNoybxhHqygL464BpI1/lEWwpgnpB5+gBdXkBhqhP4p0jqXh+SvdmOVQylqOovAqL9shvsg4aNe6sI5qBHND3H52PP+IWYm1FBsrorZN03c5OSLbTIEyyA3pMA/rdhlmRYwA2rzJ18Fqnm4ANr8sT8RsB304Y2dlfpJEoq9ThQGIuhpuYfczJ99sTlGCLO4dH1JlLqz5YQGFqzX1SV+VijZ0D5t66CQ8l7UJq5jHYO9buo8KYAbUGGR0GYVfabux3soN9xj4cvNAfAyIa7gXPWA9L9l5AYZkcZTO9XygCPKrXtrp48Sj+2vMhVmQdQpLhXm6iEu+hUyNn5OMIG/wI4OLTqn1nbJTOVxgFlDPrgMH3CTOP4V6/7WxWiwgoucUVWLpfduynyCHSFjYFFlAYwc74LKw9flFRx5naKmsjPHyY+GNaln+9fPFhlex537tkP1YeuZoFFBs1n/5oktb+vtGRxmWVJXjilwnYpiuEjrRjJi+aHjoJU10iML3vHPTodm1rd5uxdYJ6AW6BQNFFIHEbUFmGETUcZZ+bbP7dUgFM0tAQNw0Mh5eLQ5O2w06yjCiB/cjiQ0qVSaqo2ujIAqZFGBhlvHtILudFfaTGVANlrIOfd51Har4cbUORDJ0D5EzBhL29C8qkKlk40TMUzni/4wxsnLkDL978NwsnTNOga6rzFUiys8NiJzWOH/8V/u6O6BEsl1WITc0X2g5zUlapxYKdiYoC8J6RRmG8sfBTqJ1DF9MDCw8ovidjuvrjgTGXxqrn5JzF8vVPo6KcE4a1Jt06T4UrFWEEcNwZyCgss2i5dGvjfHaxkkLbWqEkVe/9cxJu6lwM91kAR/xH+HKZMj1iCoK1Eh70iME/V/yA7+7YiyljXoOjEztFM81jk18YrgoPwVw/H/x9ermYZ9CQU5DPjnjzRvOQ+Shb/zyhQItwH5cmb4sFlHYM5dV4YfkxxKbI4asRvi74/JZ+0NQSCrZoy0t4NeVfTFk0DPsO/WCB3rZP7Oyd0D90pGhr7cqgdsjEqqNypFV7D9d9aNEBjPlgM8Z/tBlxqflWW7H4qWVH4K45Du/Oc3Es8AS2qYqw59B31dabNOJFrLn9IB6a/gtCQwdbrL9M26N/zCyoDdWNC8+1aD4U0u5+v81oyry/kYnZasICSjtm/s5ErDiUojgyfXvbQFH1sibFxZn4JS9OtHPUQHjwgFbva3tmYNBApa1xOYc1senCp6E9QjfAn3YlYsJHW7D6WLqYR46njy4+hOJy2QHVmvh6czyOpiajNOwP5JmYTXedX3+JIEoO6Axjbjy9OqI3HEU7QSMhtSAJgyN9RCoJQz4UcyWBXH/iIs5lFYv2sChf9AprngaQBZR2yq74bLz19wll+oMb+qBbkNEubspviatRqNeqTHMMQlBQ31brJwMMDDQVUBKEOW5nfHa7G5rjqQW4/uudeOXPOBGya0pCVjH+789YWBOxKfn4bMNJOIUuhtohT8yLdu+IX4e8gSdnyKp2hmkNRpiUItmetkuE/BqKwKbklSIxWy4wada09mOaX6GbBZR2CF2Qjyw+qDhbks/J1N61J2Wr0Fbgp7ifRFsFFe6a/HWr9pUBevj2gIudbMd1cz1J9UGxSp9Qrz1QUlGFuatP4Or/bhepsw3cPDAcfzw8Am76ZGfLD6ZUqyNlad+up5YegcZ/Fexc5Zu2n7MfPp/8A3p2n865bJhWZVTYaKW9I2WH+KR8KAa2n5FrQzWHA+dzcOB8rmh3DXTD2K7G7TcVFlDao1PszwcUJyZylnpmUrc6118ZvxIZpXL2yvEdxiPKu0ur9ZWRsVfbox8l5wJQbleODg4n8U9cusgC2dbZdDIDV368Fd9sTVAEaqrp8eucoXjvht7oG+6Ft6fHKOuTFiU+U64lZUk+WXcaXuXfwMFnp3IOPxn7CQJcGleLhGHM9ZLj4yTnztmdthuV2kqzp73/Zkv1tPbmSCjJAko7guyML644hmMpskNhuI8zvphZu1Msoa2qxLzYecr0PTH3tFpfmeoM9OistMPc9gu/i22nW76WhqXIKCjDw4sP4q75+4TGjyCb+ZNXdsXqx0ZhiL4qK3Ft31ChTSFKKrQiZJ4EcUuxLzEHW/cvxJmgI8q8l4a8iL4BbBplLINapcbwkOGiXVJVgsMJ/6BnsAd8XB0Ukz85dDeVhMwirDsh59GiVPr0mzRLv82yFcYm+GnXeaEGJ5ztZafY+hLobNj1Hs4Xyqm5hwQNRi//Xq3WV6Y6QztPwwi44DaHXkgulp2UV7bBaB6dThJJnsgJ9u+jch0Pg8PdP4+Nwn8mdKm1dsir1/RE5wA30T6RVoB3Vhv9q1oTctR9+9eNcA9cgUr9G+TNTuGY0fUGi/SHYQyMdDKa8bcdnScK9w3vJAv6heVVOJLc9Ei477efEyHLxF0jIhUH3ObCAko7YU9CNt5cdVyZfv+G3kqynrrqgXx/9jdl+m6/QS3eR6ZuYnreiP/dsQeP37gQ+Wr5TXzd8YsorWg7Zp6T6QWY8b+d+L8/YsUNk/B2scdHN/bB4vuGIMpfFkBqw8XBDl/O6g9H/Y2RhPF/YuUon9bkvVVH8ErxXHx1MQ39y8owQHLAc9cbf0cMYymGd5oKlSHcuCBefFY38zTNDyWrqBy/6X2/yB9s1pAOMBcsoLQDUvNK8dCig6jS2/DvHx2Fq/uE1Pud+NjFOKOSHxI9dBoM6zenVfrK1A+9mUyODlLMGZtOGavb2iokZL275iSmfb4dhy4YnWBvGBCGDU+NxYwBYQ2yZ1MU2qtXRyvTz/52RGRJbi02n7yInofeQH/1WfjpdPhfoR0+u2aZyBTLMJbG26cTBsEJY1XuuDlkjHgJHdnF1FG2aSbjn3YmoqJKNg/dMigcHk6XpqpoKlyLp41DtvgHF1Z3in128uXLsnc+uARrklKxwNMdg/rfDxVXTLUaSLj8VV+Ia+WRVJGt0VbZfCpDOLYm5ch+JkSUnyvent4Lw/Tq58Ywc3A4dpzNwt/H0lBQVoX//HIIv94/DPYtXLohv6QSe5d9gGftNovpKrUjnGcthrNP80MtGcZcfH/73mr38lAvZ0T5uyIhsxiHkvJQWFYJ90YIGBRh99Nu2Q3ATq3C3c1Ia18brEFp406xL/8Rq9gWw7yd68wUW43k/aKwVJBWi+fgi/HDn2udDjOXpaqyDO4VGzHC518xvfFkxiU5QWwBStn/6C+HcOe8fYpw4qBR4/ErumDN46OaJJwQpGmZO6OXcAAnDl7IExE1Lc27S97DOb8/ka+/+Wuu/QII6dfi+2WYxlDbi+YofVZZipLbndC4MhrL9icjr6RSeXEK8ZJ/d+aCBZQ2zMLd5xXboJO9WjjFeuu9tutl+yfG9ojHAPWlTolM66PTVuHKnwdi9v43cdF3o8iHUl6lw7rjre9r0Rwn2MV7LuCKj7YI7Y+BIZE+Ijrn8Su61uoE2xhIxfzFzP7ijY74ekt8k+3rDeG37WuxHb9gu4sTbgkJxLl+d0LV5+YW2x/DmJPqZp6G/04o6uf77dVDi80NCygtrMF4acUxTPlsm0jPbbDTtQZUUO71lUan2Pdm9EbPkLqdYg3kpuxD2am/5Qn3YKDPLS3ZTaYRqDV26KSR31Au2qkQ4iA7ui3ZK5t7rJ1T6YW48ZtdItSdzC+El4s9PrihN5bMGapE4ZgDyo/ynN6USX6BT/x6WGhtzM2FjFT8dPwpJY19oMoN4Ve9Z/b9MIw5qSwvxt5D3yMpaQeGRvkoWvVtZxvuh/Jv3EVF+0muAw15vjQWFlBakIMXcrFozwUR9kjpucd9uBnL9ic1K968IaTlk1PsAcUp9r5RkQ2OS/9oywuYFB6C7z09UDJkDmAn13BgrIOBXsaker18D4rPPedyxDVmzfyw/Rymfr5NyTRJXN8/FBueHIMbB4a3SGZVKvM+tpv8dphVVIEnfz0iNDjmQqfV4vUVM3BO/xMJrpLw6YzfRF0dhrFW9hz8FiMXD8E9Rz/Din2fCZ+TfuFeYhn5olBQRUNevr/dKr8gEXNGt4yvFQsoLcj6E9UjLCjh1DO/HcWkT7eKHA/mvFkaoOyiDyw8KG7IxIjOvsqb5OVITzuEvyvSkaPR4EcvT0h9Z5m9f0zzGBhxhdJ2cped0wjS0FkrZy4WihB3g8Ac6eeKxfcOwcc39YWvW8sJwJTngUKUKXEUsf1sljD3mIt3l9yBvU5y1lpnnQ7vDpkLL6+OZts+w7QEncJHoUSvMdmeL/tnjTQJN25INA+9FBl8Gynhm2l1ZHPCAkoLskGfWY9eDk1PYHxmsciSSbVFKJW3uSpJ0nZe+SNOqVdCHtrCFt/ACIYF215Blf5NdqZXNFzd5HBWxnro1X06HPUP+pPIUerQUFXqvBJZKLU2ftxhLL9OORLWPDYKw1vohlYTEoA+vbmf+A0SH687jf2JjXMErI3VWz/Fr5WHlek5PtPRP+bqZm+XYVoaP/8eInUEcUKtRVbmyer5UBpg5qlWFHB0I9LaV5UDlWWtI6C8++67omOPP/64Mq+srAwPP/wwfH194ebmhhkzZuDiRflBbeDChQuYOnUqXFxcEBAQgGeeeQZVVbYXiVAfSTklOH1Rfrsi9dnCe4eI+iGGCpJEXGqBSOV94/92iURqzYXMSYbwU3KK/ea2AUoq4/qgePjv/rodi0rkB4mTTsKtY95udn8Y8+Po5IneKtmEkKoBbo4uFO2ySh2W6s+9NZFdVI7f9dmL3R3t8MKU7qKSamtCEUGPju+iRCpQ6HFzhLnz53fgrbPfQae/KU8sj8C9175ltv4yTEsz0sNYU23nsZ/QJ8xL/D4JCtOvT7tPGlGKHiRCPJ3qLDRbK+tfA+ZPa3kBZd++ffjmm2/Qu3fvavOfeOIJrFy5EsuWLcOWLVuQmpqK66+/Xlmu1WqFcFJRUYGdO3diwYIFmD9/Pl555RW0Re0JMaFHoPik+iFL7x+GeXcNQrSJQ9H+87m4+dvduO2HPTiabExU1RjorfD1lXHVnGJjQj0v+72Sogw8tWg0Ps89BEl/w73Nsyd8fIy1XxjrYqCn8eYS5b5XaVP2VENBPWuB0tYrSZwGhzcqx4I5+c/4zhgcKRdLS80vw7O/HW2S5pJ+L4+ufwCFeq1krxIHvDJ7mdn7yzAtyYjORiFhe+oOoWUfqg/tzymuwPF6fNq+22bUnlDekwbnGDq7Htj9FZBFFdlbUEApKirCrbfeiu+++w7e3kaNQH5+Pn744Qd8/PHHGD9+PAYMGIB58+YJQWT37t1inbVr1+L48eNYuHAh+vbtiylTpuDNN9/El19+KYSWtsIGvYRJTOhhrGBKGqdx3QKw8pGR+OrW/qIyq2lFyWv+uwP3/7wfpy/Kb8YNIT2/TPidVGolxTmwIU6x5MF967IrsU4n2xIpDfKj3n3xyLWLG7xvpvUZ1HGC0j6VdxBj9GXNk3NLlTcba0kS+PMu2U+GogTuGG45/wy6AX92S1+ROp9Ye/yiEOgay/ncKniWyL/Z0AoJc0b9BE8X8+Z+YJiWpk/Pm+Guf5nZWZkNbVVFNTMP+WvVVcTzj0NyegB3JzvcMrhhae1zc+JxbNXDje5nkwQUMuGQFuSKK4wOe8SBAwdQWVlZbX737t3RoUMH7Nq1S0zTZ69evRAYKGsViEmTJqGgoABxcUYNgCnl5eViuemfNUOJs3brTTbkB9It0L1WBz7KAPrv46Px4Y19RBI10/AtcqR98tfDuJBdclmn2AcXHRD1EAgq/kRq9MsRe3wZbl5/P86q5bdbN52E//a4B3Ou+VmEszLWS6/uM2Cvf/vfX3oRd5o8+BfstB5n2T8PpygZjKfEBCHM27Ip34M9ncVvzcDbf59ArL6yd0Og6Lvn/0zAtpSX0DujC0Z6PIOxMcbU+gxjK9jZO2GonRy5k69WIfbk8mp+knXlDZpHae31Uai3DolQfOAu50Lw6qrbcJuXPb719IC24+iWE1CWLFmCgwcPYu7cuZcsS09Ph4ODA7y85AM3QMIILTOsYyqcGJYbltUG7cvT01P5Cw+XS6tbK9tOZyrajCt6BNTrQERvdlRzZONTY/HmtdHwd5cjDuj5s/xQCsZ/tFnkUiEtSW289lecUr9Edort1yCn2MgOo+AvyetFalVYPO6/GD3kiSYdL9O6ODl7oxccEVBVhd6lxRgeUIyOvi7Kmw/ZiC0NmU++32Z0jr23BZI4NQUyt5KGkaAbLWWzbWgm3q82x+sjF9RIU/8HT18/u4V7yzAtx8jgoUp7x5k/RXQdPUOIfYm5QgNqCv1OKPknYa9R4a4RDdOILlv/JDZJhdCqVFjo5Yn8K19rGQElKSkJjz32GBYtWgQnp9aL9X/hhReE+cjwR/2wFfPOeL3/SUOKwN02rCO2PjMOz0/pLhJYERSaSc6vYz7YhLf/Pi7sgwYoI+cv+iRdVMWVnGIbGrZJETqfjf8C0+z8sPjGfxHZcWwjj5KxJF+GTcP6pFS8m5kNx+R94toxsMAKQo63nsnCmQzZSXxghLdInGYtUNh9L71/1rmsYrzyR2y9659L3IxNB/7G5xvOKOYqCpFubWdfhjEnw2OMAvb2vJPiRdpg5iG/MUr2acqSvRdQqE+weF3fUAR6XF4GSDi3ER+krFem3+xxF3z8uraMgEImnIyMDPTv3x92dnbijxxhP//8c9EmTQj5keTlVXf0pCieoCA5ZJU+a0b1GKYN69TE0dERHh4e1f6sFXJSpNBhwtVBI7L0NQZnBw0eGNMJW58dh/9M6CK2QVBK8++2ncOo9zaKUMktpzPx6l/GG+vc63vV6xSblLRL5DkxpWPHMZh76ya4UcZYxqZwixoHRS93dgNuHBgGF/21svxgCgrK5PoYluJ7E0e6e0eZt4BYc6GXgf/O6qeop0lTaSgJUZOC/CQ8svFRvHD0WfRyXSXmPTS2k1UJXAzTFIKC+qKLTo2wykr0KsyFriizej4UEz+USq0O83YYX3zua0BiNspW+/zmJ1Gmz7lys2MYxgx9qlF9bJSAMmHCBBw7dgyHDx9W/gYOHCgcZg1te3t7bNiwQfnOqVOnRFjxsGHDxDR90jZI0DGwbt06IXT07NkTts7hpDyTysH+Ta4rQvVEnryyqxBUKBMsaUiI4gqteJO748e9ihmJVG3X9w+rc1s793+FW9bfh8f+uQtlpcZMnowN02EY4KgX1E+thoedTmRmJUoqtKKIlyVT2pPDt+imjwuu7Gl9+XQifF3xzvW9lOn/+yMWZ/UaHwNanRbPr74DFzRAsVqNKv9tiAl2VkKWGcbWmRc8GauT0/BCTi7UCZsxopOfkjPI8BsmVh9LE4lGiXHd/NG1Fr/Kmnyx6jaRZ4WI0qrw1DWLGt2/Rgko7u7uiImJqfbn6uoqcp5Qm/xD7rnnHjz55JPYtGmT0LjcddddQigZOlS2d02cOFEIIrfddhuOHDmCf//9Fy+//LJwvCVNia2z8aRROzTeJHqnqZDJ5qWpPbHlmXG4dUgHpQCaAdLQvHhVjzr9AOYd/R4Pxn6NArUKx9VafLP6vmb3ibECqARBt6tEM6uyCClxv+MOEzPPz7sSWyRTcUP4waSA2N0jOl6+eraFuKZPCG4ZJPuzlVZq8cjig9Xs7v89/F9sq5CdBT21OhSk3IuPbh4kNDAM0xbw7DbVRBO7ThSTjQmRNfFUPiOzsFw8R77ZYpqYrVOD0unPL5Sz1NpJEt4b8RacXRpnTSDM/kv75JNPMG3aNJGgbfTo0cJss3z5cmW5RqPBqlWrxCcJLrNnz8btt9+ON954A22BDfr09iSFju/efAHFQJCnE96e3gsbnhqD6/uFgu753YPc8d9Z/WuNQy+pLMFzW5/Dx4c+g05/BY5VuePuKz8zW58Yy5LWeQzuCQrAhA6h+DL2e3QJdBelDYjE7BJhBmxt6IZmGoZIdXasmVevjkYXfZHCk+mFIrKH+CfxH3x/7HvRliQ1qlJuxKzx09At6PJvjgxjM4QPBRz0RTrPbqBy49XMPDvjs7DjbLaSF6V3mOdl3Rbycs/hxcOfK3m1Hvcfhu7drmlS91SSufKstyIUZkzaGnKYtSZ/lOTcEox8b5No9+vghRUPjWixfdGbHr2Z1iacJBcm4/FNj+NU7ill3oOdZuCBYS9zCHEboqK8EGMWD0ORWiXCxLfM2oXNZ4sx5+cDYjnlR1lw9+BW7RP5RxmcSe8fE4UXptSu3bMmyCR1zX+3Cz8v4v+me+Kbs0+itEpWaZelT0Nfz6uxZM4wq9UGMUyT+WUWcOpvZKnVUN+2Aie1MZj1/R6xiCJMLxaUKeYe8t2a1juk3s09u3AM1mhlB9uhcMY3s3dWe+405vnNukozYpoka4IZtSe1QREEtQknuw78D7csn6YIJ672rvh03Kd4aORrLJy0MRwc3THOQb7OSEjZGf+3CKM15NQhDUpCZnW/ipaEhGZDGCKZIk3zs1gzpBV57Ro5n4kGFVh09FFFOKnM6w/7YjlXEQsnTFvkWGg0bgoJwriIMCw7+gMGdPQWpVKIf2LTFeGE7iuToy/vT3b3oKeEz4mnTsLbk39s1nOHBZQWql5sSG/fakgSFvx9Hx449l/kQ7ajd/ToiMVXLcaEDsbMo0zbYmLfe5X22uyj4iF629AIZV5TsqU2FYoeMoTBU30OSoxmK5AvCvV5kNdvyHSQQykdy3xRlj4dL17VUzjVMkxbxKfTlTjhKNds25EbJwI7BkfKpmLTHEH3joxsUI4tMucsuWUzvh32FgICY5rVNxZQzJk9Nj5bKaBE/iGtRkUJsPw+ZJ1dqxQwG61yw+JJ8xHlZR0JspiWYXj3G+BmL9uQNyVtQoW2AjcPClfegCh8tqGJyJoDOeSaOscakqHZCpQD4s1ruiDH74gyL+jiQIzuEiKc0xmmrRIaOlgk6ySOoBL5JdkYVaPaOOXluknvUN4QyCG2Z/frmt03FlDMxPYzWUoKYNKeNLj8dHPJuwD8OBE4tgyP5eZheEkp7vfoiS9u3QZ3F1kKZtouDhoHjAsfJ9pFlUXYmboTXi4OIpGSmFdeheUHWz7kmMxJ8ZnFok1F+XqH2V6eEM/TK/BwXo7IC9GtRIMLuivx/ozerfdbZhgLMTJyovikgIpdGfuqOcoSpJV1cajbVLNz35ci74m5YQGlRaoXt6z/iYGck6uAb8YA6cfEtJ2DG74c/QEemf4r+5u0IyZ2lG8uxNozf4rPO2rU52lpX/jvTbQnpAq2ObSV0Gz9ENcWFeOv5DTEaO7Dj3cOEtFzDNPWGdn1eqW9I2WHsAAE6MuuUFj97SYpDGqy//B8PBD3NWYvHiGyLpsTFlDMpN7edEr2P6FsnkOjWlZzQWFc5G8yeddziNXqnSB9ooB718MuenqL7puxPoaHDIebWi6NsOn8OhHd0yPYQ2gyCNJs1FWd1BwcTy0QoYgE1QRqdf8rc3B4MZCnrzPSaTxem/MwBnZsfN4GhrFFBgQNgJPGSRFQDNnJB0R4CwdxQ424mhSU5uKFQx+JkGLKs7Xx2AKz9ovL1pqBI8l5yCqSnQOpIqS5anSUluQg4fwmnE7dg7M5p3CmJA1ntCXI0uhVzmo1Hgv0w28O3eB9wzzA2dss+2Vs0Myj9sJKXaYczXPoW4wd+pSIojHU0yAtCmU2bgl+2G4sCnj3yEjbi3apqgC2fmCcHvuiJXvDMK2Oo8YRg4IGYVvKNmSWZuJ09nFM6BFd78sGaWXf3PsO0vVqjoGSI+6c8o1Z+8UCihmTsxFXNOHtsaqyDCqVGho72ZOaWLr2cbyVul5JdqNgEE70XOMdAw9KIWzyXab9MbHTVKw6OQ/94AgHOzl6ZmLPQAR7OiEtv0wUsLyQXYIO+qrH5iKjoAx/HUkRbU9ne5E3wdb4beNz2O1Qggft7dApYhwQPsjSXWKYVmekT08hoBDbdn2AblfPr3f9lQkrRUJDwt3eHXOv+LbaM8wcsIBiBtab+J+M7e5fr8R5seQizuadxZncMzgT/4/QjMSrqrBg8KuI6Xmjsm6wVxSktEvfRL10ErqonNDFJQgTulyHwf2MYaZM+2VEvwewPnJStbA+CgmcPTQCH/x7iqLQ8fPuRFE2wZxQGLOhJtSsIR3qdaSzRsgc9k3yOqS7uWKdqwtWDbkH1p37lmFahpH+/ZT29uxY1PdkSSpIwtu731amXxn+CoICmhdSXBu2dTexQqiAEqXIJvqEeyHAvbpTXezxZfjj6I84U5aBMw6OKKyU11UQ6jEVzqTtqyagdI0Yi+i4H9HF0Q9dvKLQOaAvukaMg69vN6jU7DrEVMfe0bXWnAOU3+OzDWdE+fRf9yXhiSu7mk2IKK3QYuEeY2I201pAtsLyTS8iXa+VHKV2R3iXKZbuEsNYhA7hI9BBC6SqJdir1NBpq2oNtiCN//P/3I2SqhIxfW2nazG54+QW6RMLKM1ko4n25Ioa2WMPH56POw5/KOcmoXtgpeynYopakhChU0Otqi50BAb2xpK7Dje3e0w7h4pNXt07BL8fTEZBWZWok0OaDnNA28wrqVQK79laxEt5WT6+S92kmE0fHPyMpbvEMBbl41HvIjSoP9zcg+tc59tVd+Foabpoh7kE4YUhL7RYf1hAMWP22GrViwvS0H3dW7jOWYvl7nIirUB7d3QJ6IMuXl3QxbsLunhEItI9HI5OcvVIhjEH9OZz9MRS9OxytUiHT86yJEwYnGVnDg5vdm4Pilz7sYZzrK3x26YXkKEXTsapPBDd3RhqyTDtkW5dpta7PC52Cb7JPyaq4WokCe/2uEeUU2kpWEBpBsXlVdhlkj22Z7C+8JG2Elh2J5yKM/F6MTDUoxOGXfM9vLxsTwXO2Bart7yKj+N/x0WNCv8tSseYoU+iV5gn+nfwwsELeTh1sRC7E3IwrJNvs+tOJWTJiZmGRfkiJtS2hOyy0lz8kLZV0Z48NOQ5S3eJYaybsnx0Xf827lQVYJ6nBx7w7os+Mbe06C7ZmaEZUG4JQ/ZY0p4ob6XrXwOSdsttjzBMmfErCydMq+Di6CGEE2Jtwiplfs3EbWZNzDbKBrUnm19Apn6crlB7NrkcPMO0ZU1seVm+ccbqZ2CfdwFP5OZjoS4A9039scX7wAJKM9hoWhywuxxevGPnB0jc9z/96NoDNy0AXDnlPNM6DO83B246OapmU3mGiFIhpsQEK8mW1h5PF87dTSU2JV9oYYgoP1eM69Y6mZPNBeUX+j5tuzL9wNCWs6EzjK1xLnEzXlw0HuN+6oslG56WZx5dBhz9VW47eqD39HlmDymuDRZQmmGDp9wShLO9RqjMExO34KlTC3BLaBDWuTgDk+cCYQPNeb4Ypl7I52ScgywwFKpV2HXoO3m+nVopekfyy8Ld582WmE1tY4nZlm56Htl67cmVaq/L2t0Zpr2xsioTOWoVtmUdRmrKPpz6Vy+oEFM/BryNFdNbEhZQmsjRlHxkFZWL9ojOftBV5uKJTf9BsVqFYrUa60O6A4M4RwljmaRtBkzNPBS9Y69/MC/ZewFlldpGbzs9vwwrj6QqFU5n9Le9xGwdfbujk1YFlSThwWEvWbo7DGNVdOwwGqH6W8NBqRTPrL0fM/3d8bOHO3QxNwK9jekwWhoWUMwQXjyhmx/eXHEjzqplfxS6+b06fZnwdGYYazHzUI6eq3rJ4YO5JZX4Sy9oNIYFuxJRpd/27CERcHYwT1mH1oQch3+/fT8W9H8eXTq3TP4GhrFVVGo1RrrILx6VKhWOqivF5yIvb5ROerNV+8ICihnCiyuyP8KqKrkYm4tOwsfjPoWLa8vUPWGYhph5xtZi5mlulWOKWlukNw2RJub2Ya2j5m0JyH7er/dsS3eDYaySERETLsnXNXfgc3CtJz9KS8ACShNIzSvF8bQC0Z4QchSfZW5Slr3R+WZERY433xlimCYwMeqqWs08/cK90DtMDgmOSy3AgfO5Dd6mIdkbcU2fUAR42FZiNoZhGsbgXrNhZ/LyMsezl0UEehZQmpgDgvDUXMQF10VC/UXMdu6ISaP+z7xniGGawPD+tZt5KBTeNCX9/AaGHGtrJGa7x8YSsxUVpuHZhWMQd3K5pbvCMFaPq1sQrnUMEe0hcML90+ZZpB8soDSBDScuQoUqdA/9Aul2snDSR2ePJ69dYu7zwzBNwtHRA2Md/OGh1eKK4mIUnflXWTatTzB8XeUQwX9i03GxoKxB13xitlx7Y0RnX/QM0ScltBEWbXwWa7Q5uGXPq/h59f2W7g7DWD0v3fAHlo/4AN/cugN29pbRlrKA0khKKqqwIz4bPV124ISLXIfERyfhwyk/ioJtDGMtPNPnIWy+kII3snLgc2a9Mt/RToOZg+WQY3J4NfiV1Mf3JtqTe0dGwZYoLC/Agly5rhWl5x4dzb4nDHM57O1dhBN5a+Q7qQsWUBrJjrPZojJsXMkYTFfNgK9Wwnu9H0VQUN+WOUMM00R8ul8De0e9puPkaqBKDosnbh3aARp9/pLFey+gvKrukOOjyXnYe05OzNbJ3xVjutqWA/jCE4tQqA+om+YSgYiIUZbuEsMwDYAFlEZCqm4DY4Y8hNW3bMbQAawyZqwQO0eg2xS5XZ4PxBuduYM9nTE5Oki0s4oqsPpYWp2b+X6bifZkVJRNJWYrqCjAz8d/Fm2NSoP7J+uzPDMMY/WwgNLE7LFO9moM7+QHFxe/ljo3DNN8el4nPgrUKhw8+lO1RaYhx/N3nq8zYu1vvfDi4+qA6f1CbeqskHBSWCk7CF/b+VqEe4RbuksMwzQQFlAawVtLrkE3hy9IVMHIzn5wsre9JFVMO6PTeDwXGIQxHcLwSNFRJZqHGNTRGz30FbiPJOXhcFLeJV+nXCkUwUPMHhrRpGueio69sWQyJv4Yg/mr7hXTrUF+3nn8HLdAtO1UdpjTe06r7JdhGPPAAkoD+Wfr61hWmYgjAQkYEfYWxnezLTs8006xd4LaIwRVKtUlSdso5PjO4RF1VjkuKq8S/imEg0aN24Y2LTHbknWPYVl5CtI0KnyUvQePLhqFvFyj2ailWLDxGRRXyUURr424EqFutqX9YZj2DgsoDSAhLwGvJv6hTEslEZjQU7bfM4y1MynKpDZP1qFqy67tGypq6hCrjqYis9DoSLtsfxIK9YnZrusXolRDbizeztWF+a1SEW5acTWOxLZcWH5uTjwW5R8XbUo4NafLTS22L4ZhWgYWUC5DSWUJntj8BEok+Ubds8ADBU6PIJCzaDI2wvD+98PNzlm0NxXEo0JboSwjk83Ng2S/jEqthF/0GhORmG2HaWK2pocWTxnzGjZdtRSTNN7w1puLSJty5/63sGD1HEg6uYaVOcnZ8yUiK+XjvN4pHCEhXFWcYWwNFlDqgeqUvLbrNSTkJ4hpbVkQ9qQ+jQk9WHvC2Fhtng5ybQ1yGN2dtrvacjLdGAJzFu05j0qtDuuOpyMpRzaPjOrih25B7s3qg59/D3w4eyuWXbUY/SU5rwKZnT7M3IXHFo5Cfr4sGJmF4ix0OrgEv6RexH8zcnHf2Lnm2zbDMK0GCyj1sOTYj1hzbo08UJITSlNuBSQHXNEjsLXOD8OYhUkdJyntfxONWWWJMG8X5Zq+WFAussvWDC1uLJXlxbXODwzsjR9u3YF73Lop8zZJBXh96VQg5QDMwo7PgMpikMw1Jnom5yhiGBuFBZQ6IPv4+wc/UabL026EVOGPQA9HxITaVppvhhkeMhxu9m5iIDad34CK8qJqg3KnScjx3NUnsF9fRLBLgBtGd2lcKD2ZbJ749Qq8tHg88vMurfVDabMfn/Ebvux+Lzx1Ety1Ojx5MQX4YRKw5xtSXTb9hBVlAHv1jsAaR2Dkk03fFsMwFoUFlDoc7J7e+5ZQQRNTXfqjLD9atMd3DxDRDwxjSzhoHDDWs6toF1YVY/dhYzQPMayTL7oGygJMar6xNs+9oyIbfb3/vfVVbJGK8FdlJu5bcV2dPiajhzyGZZMW4FPJF2GUyVZXCax5Flh6O1CW34SjBJatewL77fT7G3g34NG65eEZhjEfLKDURKdF3spH4aCTnWLJXq5SPawsntCdzTuMbTLJp5fS/jd+VbVlJITcblLlmKCCghTl0xiySrPwbrLRhPRAt1lQqeu+zQSHDMDgOzcAwx5R5pWcXImHF47E8ZPGyLmGkJkRh/fyjuCu4EA8EhQIacRjjfo+wzDWBQsoNdnyHiLP7cCSlHRcX1qF96cswIZTBWKRo50aIzpz5ljGNhnebw7cdBJ66jTo5dPzkuWUJdbdyU6Zvm1Y4xOzvbPnHeRrZefaKe6dMX74s5f/ksYemPQ2cMsvkJw88aafD7baA7N3v4wlax8TzuoN4cfNz6Nc7+0b4dsDKtaeMIxNwwKKKVTxdcv7oukOFV6f9C0yKsORoc8NQcKJswNnj2VsEwcnD6y5biV+veswbplMGZGr4+pop1QqJu0JZY5tDGsT12Ld+XWi7e3ojeev+qFxHex+FUrvWYvzLp5islKlwttpG/Hs1mdRVFHdZ6YmFy8ew9IS2bHXSSfhrnHvNW7fDMNYHTYtoNRX4KyxZF88isrl95KLnzxjwitA5ChsOGksDjihR4DZ9scwlsDLO7Le5f+Z0Bk/3zMYfzw8An5uDU/Mlleajbf3vK1MvzjkRfg4+TS6fy7+3bFg1nbMdjb285/Ef3DL37fgVM6pOr/3w+bnUaH3lbnFvQv8/Lo3et8Mw1gXNi2gPPf7USze0/z8CVQb5Kk1d+MuLwekazRAt6nAiMfFsg0n5OKABPufMG0d8kUZ1cUf4T4ujfree8tvRE5ZjmiPDx///+3dCVhUVRsH8D8gO4IiIC6YKe7iEqRh5poLkplZlmJufblk6pdGaloupZlmaV+m5ZJm5pKmopVruCSaYuKC5oI7brmiIIsw3/OeccYZlUSF5s7M//c883Bn7p3LHQYO75z3nPeYTWt+UM6unhjUPgYTG0xAYWd9/ZXjKcfR8eeO+HHbZ3cNuj17JgGLbugXO3SX3pMm4x/6exORdlh1gCKp6feW7ME3G5Me6TwL1vwXOxwysMvNFQNLloKuzWRpqXEuJR17kvWzCaqV9Eagj1s+XTmRZck/+b8OxODI0XWPfK6Nf3yOFTf/VtuFdcCwOu/ly0y3po83x4LWC1C1mH68TGZOJkbt/xaD5zVBmkwnvmX6hiEqHSQ6eFeCr2/wI39vIrI8qw5QDMb88hc+XXUgz4PpTCUnb8PnZ9Yb7/d/oj8cPIqq7d/+Muk9YXE2shFHj61H61k18fLWoZixZcyjnSz9KlYnTDfeHRQUCX+v/JvpFlQ4CHMi5qBDcDvjY7/cvIjlmz9S26dPx2Nx+km17ZGjQ9fG+jFkRGT9rDpA6dvk9ielL2MPY0RMInJurfWR10+RI9a+hRu3Rv63dy2FOrVlHIreuv23x588y/EnZCNKBtbGBQf930lsxrm7irY9kNXv48MzpzDq74uIgBeeb/yIAU8uNVzee3oEJpR7Rc1CesbBEy8/+5naN23jUGO9oiifKijqWz7fvz8RWYZVByg9G5bHyOf1BdTE7C3H8c6iXbiZnbfFx5b89i62Qj8lMjBbh7cjvzXuS8/Kxu+HL6htWcW1ekn9zAIia+fq5oNGLvoVhq85OtxVtC3PkmKBP2erkvJtMx0wrs3Cf6x58qiaPzMMC5pOxejn5sLRqZAaO3YqQ1/x1jNHhy4ce0JkU6w6QBFd6pXFhJdrGhc7++nPZLw5909kSGXKf3Du3G6MP7nSeH949Z7wKny76mRc0gWkZ+kDnaaVA+Bo+AZENqBFuchci7blifS6LO93+36zUUAR/arIBalMmfrGXhIJUr55bSumh/TF4DKR8CliXmiOiKyb1Qcool1oaXwVFQoXJ/3LWb3vHF6fFY+0TH012Huldkat6onrt4KONs7FUb9OX7Nj1prM3pHy9kS2pF7tN1Svw8Omeb6J6YzNGbf+Rso+A4R2gyVIj03dJ3rghaase0Jk1wHKlClTUKNGDXh7e6tbeHg4fv1Vv9qvaNSokRq9b3rr1auX2TlOnDiByMhIeHh4ICAgANHR0bh5896BxINoWT0QM7qGwf1W5UtJz3Sa/geupmXddeyKDR9go07fIPtl6xAdOdNsvwy2/e1WgOJSyBH1H3CxNCJbTvPs2DUb/0s7hF6BARjt5w88/wVQgKkdIrJPD9SqlC5dGmPHjsWOHTsQHx+PJk2aoE2bNkhMTDQe88Ybb+DMmTPG27hxt0fVZ2dnq+AkMzMTcXFxmD17NmbNmoUPPvggX16M1G/4/j914H2rXPefJ67g1Wlb8fetSrAGBy7sNW6/X7kzfHzKmO1PPJ2Csyn6BdOeLl8MHi63y38T2XOaJ/3GZQzf8anxfplyTQFfffVZIiKLBSitW7dGq1atUKFCBVSsWBGjR4+Gl5cXtm7dajxGekYCAwONN+lpMVi9ejX27duH77//HrVq1UJERAQ+/PBDTJ48WQUt+SH0MV/M7xEOPy8XdX//mRS0/3oLkq/oB8OKd15eiq+r9kJnj3L3XCvEtDhbE04vJhv1MGmer37ujuO3VnuomeOMjs3vLplPRJQfHrpfVnpD5s+fj9TUVJXqMZg7dy78/PxQvXp1DBkyBGlpacZ9W7ZsQUhICIoXv10noUWLFkhJSTHrhXlUVUt6Y2HPcJS8VVjt6IVUvDwlDkf+vt0A13uyD6JfXnbP55uVt+f4E7JRD5rm2bvvR8y+fkhtu+h0GNXoUzgV0n8QICKyeICyZ88e1Wvi6uqqxpcsWbIEVavqKz127NhR9Y7Exsaq4GTOnDno1KmT8blnz541C06E4b7sy01GRoYKYkxv91PO3ws/9q6Hx/081f3TV9NVT0riaX1l2NycT0nH7lP6Y6qW8EbJIu73/V5E1pzmcc/JQcT1VBQ7uSPX4zIzruH9rR8i51bNkd7FQlHu8Sb/4pUSkb154MEVlSpVQkJCAq5evYpFixahS5cu2LBhgwpSevToYTxOekpKlCiBpk2bIikpCeXLP3wBpY8//hgjR4584OeVKuKuelI6z9wGP7yHm+ml8Oo3NzGrW12VCroX8+qxnL1Dtq3+E72wMXYi3DKvASkbgZuZwD16Rab90gOHnfTpoCo5TujacqoFrpaI7MkD96C4uLggODgYoaGhKnCoWbMmJk2adM9j69atq74ePnxYfZUxKefO3U6fCMN92Zcb6Y2RgMhwO3lSX9o6L6TI2n+f2IqEIlewNzARIX4foNP0bdh0SL92yJ1MpxezvD3ZOmdXL7hVitDfybgKHIm965gDB1dg+tU9aruQTocPn/4IhZzZs0hEBeuR5wbm5OSoFMy9SE+LkJ4UIWNVJEV0/vztIGDNmjVqIK0hTXQvkk4yTG023PIqJTMF444tNN7XpVbAjaxsVSdl5V7ztJJUj918q3qsLDVfoxSrx5IdqNb29nbi0rt2j4kbbiwn/x+fEFSq+Ny/eXVEZKceKECRnoyNGzfi2LFjKtCQ++vXr0dUVJRK48iMHJmCLPtjYmLQuXNnNGjQQNVOEc2bN1eByGuvvYZdu3Zh1apVGDZsGPr06aOCkILwWfxnOJ9za8qwU1EUDvyv2s7MzsGbc3dg0Y5TxmO3JF1UwYtoUtmf1WPJPpRvArgURpqDA1YeW42sjFSz3R81/RJ1dK4IznFEj1a3FwYkItLMGBTp+ZCgQ+qb+Pj4qMBDgoxmzZqptMvatWsxceJENbMnKCgI7dq1UwGIgZOTE1asWIHevXur3hRPT081hmXUqFEF8doQdzoOiw8tVtuezp4Y/vwC+LsXx7uLd6uS+DLD8p0fd+F6eha6Pv041posDsj0DtkNZzfMfbw2JqYfQbqjIyYnTEODuvpAXgQFhWN65224eOkgnF31g86JiAqag07KploZmcUjAZKMR8kt3ZOWlYa2y9ridOppdf/9p95H+0rt1baseDxyeaJaXNBgYLOK+GHbCZy5mq6qx+58vxk8XVmgjexD7JZP0e/gbLX9vHMARndcZ+lLIiIblJf/3wY2W5964rIoY3BSJ7AOXqr4knGfLPw34vlq6Nsk2PjYhDUHVXAiwssVY3BC9lu07eZlbN4xFWnXb48VIyL6t9lkgCJrhcxL1c8ccocjRoQPh6OD+UuVdYIGNq+E91pVvuv5z3J6Mdlh0bbGQY3V9jVdFnrtnYwXFzbF1h1fW/rSiMhO2V6AkpmG/8XfXiukX0A4grzN19ox1aNBeXz8YghuTVJQGrN6LNmh5hVfNLuf7ATEJi232PUQkX2zvUEW68dgUvIpjPMtghNeRdGh2Rf3fUqHOmVQ1MMZ//vtMCKqB6J0UY9/5VKJtKReqXpqMHlqln4WT6lsoH8r85W+iYj+LbYVoJyKB7ZMho8uB6MvpyL9pZg8rxXSsnoJdSOyV65Ormj2WDMsPayvhTKiwRh4eLGaMhFZhu0EKDczgGV9AF2O/n7jIXALDLH0VRFZlegno1HUtShq+NfAU489a+nLISI7ZjMByq8r+yLs0kGotVlL1ALC+1r6koisjreLNwaEDbD0ZRAR2cYg2f0HlmHIhTi0KVUSywt7Ay98BTjZTOxFRERkd6w+QMnKSsP7cR8g28EB15wccar8M0Dxapa+LCIiIrLnAGXmLz1xwFE/7qRCjiP+EzHN0pdERERE9hygJB1Zh6mXd6ptJ1kGPnw41wohIiKyAVYdoJguA9+1cGVUq2xeaIqIiIisk1UHKImON9XXstkO6B05w9KXQ0RERPnEqgMU4SCpnScHqbVEiIiIyDZYfYAS5VkOtUKiLH0ZRERElI+sOkCRtUL6RnKtECIiIltj1QHK2Hoj4eHhZ+nLICIionxm1QFKhfItLH0JREREVACsOkAhIiIi28QAhYiIiDSHAQoRERFpDgMUIiIi0hwGKERERKQ5DFCIiIhIcxigEBERkeYwQCEiIiLNYYBCREREmsMAhYiIiDSHAQoRERFpDgMUIiIi0hwGKERERKQ5DFCIiIhIcwrBCul0OvU1JSXF0pdCREREeWT4v234P25zAcrFixfV16CgIEtfChERET2ga9euwcfHx/YCFF9fX/X1xIkT932BD+rJJ5/E9u3bNX/Ogjovr5U/A2v63ZJPY/JB5eTJk/D29rbLv4OCOi+vlT/Xgvg9kJ6T0NBQlCxZ8r7HWmWA4uioHzojwUl+NkrCycnJKs5ZUOfltfJnYG2/W0LOm5/ntqa/g4I6L6+VP9eC+j1wcXEx/h//Jxwke4c+ffpYxTkL6ry8Vv4MrO13qyBY099BQZ2X18qfq6V/txx0eRmpojHSrSu9J1evXi2wT2REpH1sC4hsl1X2oLi6umL48OHqKxHZL7YFRLbLKntQiIiIyLZZZQ8KUW4cHBywdOlS/oCI7BzbAuvHAEWjtmzZokZPR0ZGwp517doVL7zwAuyRTJ3t3r27mo4no94fe+wx9O/f31gH6H7Wr1+vGukrV64U+LVSwWFboMe2oLvdtQUMUDRqxowZ6Nu3LzZu3IjTp08/0rmys7ORk5OTb9dGBe/IkSMICwvDoUOHMG/ePBw+fBhTp07FunXrEB4ejkuXLvFtsBNsC+zbETtuCxigaND169exYMEC9O7dW/WgzJo1665I+Oeff0aNGjXg5uaGp556Cnv37jUeI8cXKVIEMTExqFq1qhpIKEXtrF3ZsmUxceJEs8dq1aqFESNGwNbINDz5pLR69Wo0bNgQZcqUQUREBNauXYvk5GQMHTpUHZeRkYFBgwapYmXyPgcHB6t/aMeOHUPjxo3VMUWLFlW/M/IJlKwL24J7Y1sQYRdtgSYDFHvuyhMLFy5E5cqVUalSJXTq1AkzZ868a92C6OhoTJgwQVX48/f3R+vWrZGVlWXcn5aWhk8++QTTp09HYmIiAgICLPBK6GHIJ6JVq1bhzTffhLu7u9m+wMBAREVFqQBWfic6d+6sPlV98cUX2L9/P77++mt4eXmpRmrx4sXqOQcOHMCZM2cwadIkq3tD2BawLbBnl+y8LbDKSrK2TqJeCUxEy5YtVb2XDRs2oFGjRsZjZJp1s2bN1Pbs2bNRunRpLFmyBO3bt1ePSbDy1VdfoWbNmhZ6FfSwpCtXGpwqVarcc788fvnyZRWcSjC7Zs0aPPvss2pfuXLl7loSQoJT6VEj68O2wL4dsvO2QJM9KKZWrlyJ+vXrqx9qsWLF8NxzzyEpKcm4X7qvpMvqp59+Ut1YHh4e6p+yDCyzRhLhbtu2DR06dFD3CxUqhFdeeUU1VKYk92j6yye9LRI1G0h6QFJAZL3uVwFAfvdlILWkgOwB2wK2BfZKZ6dtgeYDlNTUVAwYMADx8fFqUJDU72/btu1dgz4lD/fOO+8gISEBFStWVP/gb968CWsjgYhct4zWluBEblOmTFFddNKTklfSHSiBmy2R9/7OP1TTtJatkNyxvHemAacpeVxyyXd2+do6tgVsCwzYFthHW6D5AKVdu3Z48cUXVaMtAyJlPMaePXuwb98+s+MkOJEBpRKcjBw5EsePH1ejna2JBCbfffedGlsigZbhtmvXLhWwSH7RYOvWrcZt6eI7ePBgrt2AtkLG2kj+1LTM+dGjR2FrpKdQ0neSortx44bZvrNnz2Lu3LmqVy0kJEQF6pL+uxfpRTPM4rIFbAvYFhiwLYBdtAWO1pCDk94QyafJujsyelvcOSvFNJ1RokQJ9fX8+fOwJitWrFDBxuuvv47q1aub3aRxNk3zjBo1SvUoyewdGUjo5+dn8wOLmzRpgjlz5mDTpk0qSO3SpYvq1rRFX375pRqV36JFCzXVXGqiSIpDApdSpUph9OjR6m9BfgZSK0WK00mwJrO8JBctpFaC9MTI79Xff/+tZoRYM7YFbAsM2BastIu2QPMBisxOkZHM06ZNwx9//KFuIjMz0+w4Z2dn47YhtWFttT8kAJEBTrIQ4p0kQJE01+7du9X9sWPHqkI9oaGhKpJevny5MUq2JfIeSppLDBkyROVYZRyS9JZJQFa+fHnYogoVKqj3WwJzGfgsr7NHjx5qnJWMrzIMepP030svvaRG+cvMrzfeeEOlQoQ0XtKbOHjwYBQvXhxvvfUWrBnbAj22BWwLethLW6DToC5duujatGmju3Dhggw40G3cuNG4b9OmTeqxJUuWqPtHjx5V93fu3Gk85vLly+qx2NhYna2R1ySvTV6jPWjRooWuT58+lr4MshC2BbljW0C2TtPTjGXwj+Tjv/nmG5W2kbSORIBk+yTVtXnzZtVN2atXL0tfDlkY2wL7xbbAfhXScre+jNSeP38++vXrp8ZhyFRaKUJjWg+EbJPkUmVu/8CBA9GmTRtLXw5ZCNsCYltgvxykGwUaI8XJZNaODBQkIvvFtoDIfjlqrStPRhlLt76hGh4R2R+2BUSkqRQPu/KIiG0BEWk2xUNERET2TVMpHiIiIiLBAIWIiIg0x2IBipTvlsqQssaMVH6V8rymzp07p0q4y35ZoVhG80upa1My3Viea3q7s2aGlIOvV68eChcujMDAQAwaNMgqFxEkslX50RYIqaopJdA9PT3VshgNGjQwW8tIKlJHRUWpfbI6uiwpYS0lv4nskcUCFCnBW7NmTUyePPmufTIsRsqYHzlyBMuWLcPOnTvVWgIys8dQutdAyvnKAnKG27hx44z7ZJG9Vq1aqQZNzrFgwQLExMSw2BuRhuRHWyDBifydN2/eHNu2bVM1dKSct9RSMpDgJDExEWvWrFGzBSUwkpLhRKRROg0wLV0vDhw4oB7bu3ev8bHs7Gydv7+/btq0acbHGjZsqOvfv3+u5x0yZIguLCzM7LGYmBidm5ubLiUlJd9fBxFZpi2oW7eubtiwYbmed9++feo827dvNz7266+/6hwcHHTJycl824g0SJNjUGQVV+Hm5mZ8TD4Jubq64vfffzc7VpablpV8pdKsLCaXlpZmdh7Tcwh3d3ekp6djx44dBf46iKjg2wJZtVwWEQ0ICFDpXFkMTRaVNG0rpIdF0jphYWHGx6QXRs5lWICUiLRFkwGKrMRYpkwZFXBIwSZZufiTTz7BqVOnVBrHoGPHjvj+++8RGxurjp0zZw46depk3C9L1cfFxWHevHnIzs5GcnIyRo0apfaZnoeItCkvbYGkf8SIESNUynflypV44okn0LRpU+NYFVnxWwIYU7KchqwEK/uISHs0GaA4Ozvjp59+wsGDB1UDIgPjJAiJiIgwyylL/liCkJCQEJVf/u6777BkyRIkJSWp/ZKPHj9+vBo4K5+4KlasqMakCNPzEJE25aUtkPV6RM+ePdGtWzfUrl0bn3/+uVq7a+bMmRZ+BUT0sDT7Xzo0NBQJCQm4cuWK+qQkn4ouXryIcuXK5fqcunXrqq+HDx82PjZgwAB1DlkJ+cKFC8aF5/7pPERkPW2BrHQuqlatava8KlWqqL97ITP4JBVkSmbzycwe2UdE2qPZAMXAx8cH/v7+qqs2Pj7+H1e2lUbMtMEykKmLMkVRxp9IuicoKEh1AROR9citLShbtqz6+z5w4IDZ8dLrIjN+RHh4uApwTMee/fbbb6r3xfDBhoi0xWJr8Uj9AdOejqNHj6oAQ7pxJef8448/qsZItvfs2YP+/fur6YaSthGSxvnhhx9UyqZYsWLYvXs33n77bVX7oEaNGsbzSopHph9Kd7B0FY8dOxYLFy6Ek5OTRV43EeVvWyAfQKKjozF8+HA1XblWrVqYPXs2/vrrLyxatMjYmyLtgIxRmTp1KrKystQ05FdffVUFN0SkQZaaPhQbG6um/d1569Kli9o/adIkXenSpXXOzs66MmXKqCmEGRkZxuefOHFC16BBA52vr6/O1dVVFxwcrIuOjtZdvXrV7Ps0btxY5+Pjo6YWy1TEX3755V9/rURUcG2Bwccff6yO8/Dw0IWHh+s2bdpktv/ixYu6Dh066Ly8vHTe3t66bt266a5du8a3hkijuFggERERaY7mx6AQERGR/WGAQkRERJrDAIWIiIg0hwEKERERaQ4DFCIiItIcBihERESkOQxQiIiISHMYoBCRzZCqskuXLrX0ZRBRPmCAQkSPrGvXrio4kJXD79SnTx+1T47JLyNGjFAl7YnIdjFAIaJ8IYtwzp8/Hzdu3DA+lp6ertbMknV0iIgeBAMUIsoXskK4BCmyKKeBbEtwUrt2beNjGRkZ6NevHwICAuDm5ob69etj+/btxv3r169XPS7r1q1DWFgYPDw8UK9ePeNqxbNmzcLIkSOxa9cudZzc5DGDCxcuoG3btup5FSpUQExMDN9hIivEAIWI8k337t3x7bffGu/PnDkT3bp1Mzvm3XffxeLFi9WKw3/++SeCg4PRokULXLp0yey4oUOHYsKECYiPj0ehQoXUucUrr7yCgQMHolq1ajhz5oy6yWMGEry0b99erXAuq51HRUXddW4i0j4GKESUbzp16oTff/8dx48fV7fNmzerxwxSU1MxZcoUjB8/HhEREahatSqmTZsGd3d3zJgxw+xco0ePRsOGDdUxgwcPRlxcnEoZybFeXl4qaAkMDFQ3ecxAxrp06NBBBT5jxozB9evXsW3bNr7LRFamkKUvgIhsh7+/PyIjI1XKRafTqW0/Pz/j/qSkJGRlZeHpp582Pubs7Iw6depg//79ZueqUaOGcbtEiRLq6/nz5+87nsX0eZ6envD29lbPIyLrwgCFiPKVpGLeeusttT158uSHPo8ELgYyzkTk5OQ80PMMz83L84hIW5jiIaJ81bJlS2RmZqqeEhlbYqp8+fJwcXFRqR8DOU4GyUoqJ6/kHNnZ2fl63USkLexBIaJ85eTkZEzXyLYpSbn07t0b0dHR8PX1VemacePGIS0tDa+//nqev0fZsmVx9OhRJCQkoHTp0ihcuDBcXV35ThLZEAYoRJTvZNxHbsaOHatSLq+99hquXbumphKvWrUKRYsWzfP527Vrp6YwN27cGFeuXFEzh/KzEBwRWZ6DTkayEREREWkIx6AQERGR5jBAISIiIs1hgEJERESawwCFiIiINIcBChEREWkOAxQiIiLSHAYoREREpDkMUIiIiEhzGKAQERGR5jBAISIiIs1hgEJERESawwCFiIiIoDX/Byo2+KBRTPAMAAAAAElFTkSuQmCC", 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" ] @@ -486,14 +486,14 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 12, "id": "6981052c", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8dba495f46e248b29d33d99b40675881", + "model_id": "2fb40bbee4d246c4aac9d8c63d6dcec6", "version_major": 2, "version_minor": 0 }, @@ -507,10 +507,10 @@ { "data": { "text/plain": [ - "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=100, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" + "Chronos2Model(output_chunk_shift=0, likelihood=None, hub_model_name=amazon/chronos-2, hub_model_revision=None, local_dir=None, input_chunk_length=24, output_chunk_length=6, enable_finetuning=True, n_epochs=100, pl_trainer_kwargs={'accelerator': 'gpu', 'callbacks': []})" ] }, - "execution_count": 22, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -554,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 13, "id": "49b2c2e8", "metadata": {}, "outputs": [], @@ -566,14 +566,14 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 14, "id": "41e8a82f", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "34b9699f0deb4cb4bca42eb3b663a3ed", + "model_id": "32bc596de3864391bc0544b8850eef53", "version_major": 2, "version_minor": 0 }, @@ -587,7 +587,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3955fb726ade4ff9b17f2660cea15057", + "model_id": "67cf8731f2b149be8e37ac2a426256f8", "version_major": 2, "version_minor": 0 }, @@ -604,13 +604,13 @@ "" ] }, - "execution_count": 24, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -649,7 +649,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 15, "id": "9a96ca55", "metadata": {}, "outputs": [ @@ -659,7 +659,7 @@ "True" ] }, - "execution_count": 25, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -682,7 +682,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 16, "id": "ce2fcd82", "metadata": {}, "outputs": [], @@ -700,7 +700,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 17, "id": "630bb5bc", "metadata": {}, "outputs": [], @@ -721,14 +721,14 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 18, "id": "c1fddf83", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "71e7d2b9d04f427eae8f9e8ea576d7c6", + "model_id": "975912059afa49ffb2f73ed18de29fc1", "version_major": 2, "version_minor": 0 }, @@ -742,7 +742,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f523a392cf9c420d98cb2b28510021f1", + "model_id": "7e4af30c12834bf29a072214857d1bc1", "version_major": 2, "version_minor": 0 }, @@ -759,13 +759,13 @@ "" ] }, - "execution_count": 28, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -806,7 +806,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "3b81f2e2", "metadata": {}, "outputs": [ @@ -846,20 +846,20 @@ " \n", " 1\n", " Full Fine-tuning\n", - " 3.237262\n", - " 13.835668\n", + " 4.550051\n", + " 20.350664\n", " \n", " \n", " 2\n", " Partial Fine-tuning\n", - " 2.899847\n", - " 12.568367\n", + " 4.891376\n", + " 21.527288\n", " \n", " \n", " 3\n", " LoRA (PEFT)\n", - " 5.951829\n", - " 26.501753\n", + " 5.457223\n", + " 23.800879\n", " \n", " \n", "\n", @@ -868,12 +868,12 @@ "text/plain": [ " Model MAPE (%) MAE\n", "0 Base Model 15.254518 70.704819\n", - "1 Full Fine-tuning 3.237262 13.835668\n", - "2 Partial Fine-tuning 2.899847 12.568367\n", - "3 LoRA (PEFT) 5.951829 26.501753" + "1 Full Fine-tuning 4.550051 20.350664\n", + "2 Partial Fine-tuning 4.891376 21.527288\n", + "3 LoRA (PEFT) 5.457223 23.800879" ] }, - "execution_count": 31, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" }