fix: resolve broken APIs, deprecated calls, and add requirements.txt in Classification_Transformers

DeepLense_Classification_Transformers_Archil_Srivastava/eval.py

@@ -56,9 +56,9 @@ def evaluate(model, data_loader, loss_fn, device):
     # Concatenate all results
     logits, y = torch.cat(logits), torch.cat(y)
     loss.append(loss_fn(logits, y))
-    accuracy.append(accuracy_fn(logits, y, num_classes=NUM_CLASSES))
-    class_auroc.append(auroc_fn(logits, y, num_classes=NUM_CLASSES, average=None))
-    macro_auroc.append(auroc_fn(logits, y, num_classes=NUM_CLASSES, average="macro"))
+    accuracy.append(accuracy_fn(logits, y, task="multiclass", num_classes=NUM_CLASSES))
+    class_auroc.append(auroc_fn(logits, y, task="multiclass", num_classes=NUM_CLASSES, average=None))
+    macro_auroc.append(auroc_fn(logits, y, task="multiclass", num_classes=NUM_CLASSES, average="macro"))
 
     result = {
         "ground_truth": y,

DeepLense_Classification_Transformers_Archil_Srivastava/requirements.txt

@@ -0,0 +1,10 @@
+torch>=2.0.0
+torchvision>=0.15.0
+torchmetrics>=1.0.0
+timm>=0.9.0
+einops>=0.6.0
+wandb>=0.15.0
+numpy>=1.24.0
+matplotlib>=3.7.0
+scikit-learn>=1.2.0
+tqdm>=4.65.0

DeepLense_Classification_Transformers_Archil_Srivastava/train.py

@@ -319,7 +319,7 @@ def train(
         # Scheduler
         if run_config.decay_lr:
             scheduler = CosineAnnealingWarmRestarts(
-                optimizer, T_0=15, T_mult=1, eta_min=1e-6, verbose=True
+                optimizer, T_0=15, T_mult=1, eta_min=1e-6
             )
         else:
             scheduler = None

DeepLense_Classification_Transformers_Archil_Srivastava/utils.py

@@ -29,7 +29,7 @@ def get_device(device):
         return xm.xla_device()
     if (device == "cuda" or device == "best") and torch.cuda.is_available():
         return "cuda"
-    if (device == "mps" or device == "best") and torch.has_mps:
+    if (device == "mps" or device == "best") and torch.backends.mps.is_built():
         return "mps"
     if device == "cpu" or device == "best":
         return "cpu"