"num_workers": NUM_WORKERS, } test_dataset_args = { "inputs_path": trajectory_tensor_path, "targets_path": CROSS_VALIDATION_WHERE_TARGETS_PATH, "fold": fold, "heatmap_size": heatmap_size, "heatmap_smoothing_sigma": heatmap_smoothing_sigma, "phase": "test", "batch_size": BATCH_SIZE, "shuffle": False, "num_workers": NUM_WORKERS, } train_loader = get_trajectory_tensor_dataset(**train_dataset_args) val_loader = get_trajectory_tensor_dataset(**val_dataset_args) test_loader = get_trajectory_tensor_dataset(**test_dataset_args) # ########## SET UP MODEL ########## # embedder = CNN_2D_Encoder(**embedder_args).to(DEVICE) encoder = TrajectoryTensorGRU(**encoder_args).to(DEVICE) temporal_decoder = RecurrentDecoderTrajectoryTensor( **temporal_decoder_args).to(DEVICE) spatial_decoder = Trajectory_Tensor_CNN_2D_Decoder( **spatial_decoder_args).to(DEVICE) if multi_view_tensors: multi_view = "multi_view" else: multi_view = "single_view"
# ########## SET UP DATASET ########## # test_dataset_args = { "inputs_path": trajectory_tensor_path, "targets_path": when_targets_path, "fold": fold, "heatmap_size": heatmap_size, "heatmap_smoothing_sigma": heatmap_smoothing_sigma, "phase": "test", "batch_size": BATCH_SIZE, "shuffle": False, "num_workers": NUM_WORKERS, "multi_target": True, } test_loader = get_trajectory_tensor_dataset(**test_dataset_args) # ########## SET UP MODEL ########## # encoder = CNN_2D_1D_Encoder(**encoder_args).to(DEVICE) decoder = CNN_1D_Trajectory_Tensor_Classifier(**decoder_args).to(DEVICE) encoder.load_state_dict(torch.load(os.path.join(MODEL_LOAD_PATH, "encoder_fold_" + str(fold) + ".weights"))) decoder.load_state_dict(torch.load(os.path.join(MODEL_LOAD_PATH, "decoder_fold_" + str(fold) + ".weights"))) params = list(encoder.parameters()) + list(decoder.parameters()) loss_function = nn.BCELoss() # ########## TRAIN AND EVALUATE ########## # best_ap = 0 test_args = {