void IndexIVF::train(idx_t n, const float* x) {
    if (verbose) {
        printf("Training level-1 quantizer\n");
    }

// Train Quantizer

    train_q1(n, x, verbose, metric_type);

    if (verbose) {
        printf("Training IVF residual\n");
    }

    // optional subsampling
    idx_t max_nt = train_encoder_num_vectors();
    if (max_nt <= 0) {
        max_nt = (size_t)1 << 35;
    }

// Train Residuals

    TransformedVectors tv(
            x, fvecs_maybe_subsample(d, (size_t*)&n, max_nt, x, verbose));

    if (by_residual) {
        std::vector<idx_t> assign(n);
        quantizer->assign(n, tv.x, assign.data());

        std::vector<float> residuals(n * d); // <--- OOM LINE
        quantizer->compute_residual_n(n, tv.x, residuals.data(), assign.data());

        train_encoder(n, residuals.data(), assign.data());
    } else {
        train_encoder(n, tv.x, nullptr);
    }

    is_trained = true;
}