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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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 *.zst filter=lfs diff=lfs merge=lfs -text
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Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/dataset.json

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+        "Lesion": 1
+    },
+    "numTraining": 668,
+    "file_ending": ".nii.gz",
+    "overwrite_image_reader_writer": "SimpleITKIO"
+}

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Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_0/debug.json

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+    "_best_ema": "None",
+    "batch_size": "2",
+    "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}",
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+    "cudnn_version": 8902,
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+    "dataset_json": "{'channel_names': {'0': 'FLAIR'}, 'labels': {'background': 0, 'Lesion': 1}, 'numTraining': 668, 'file_ending': '.nii.gz', 'overwrite_image_reader_writer': 'SimpleITKIO'}",
+    "device": "cuda:0",
+    "disable_checkpointing": "False",
+    "enable_deep_supervision": "True",
+    "fold": "0",
+    "folder_with_segs_from_previous_stage": "None",
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+    "hostname": "lg02e14",
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+    "local_rank": "0",
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+    "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x147e2dc53c70>",
+    "loss": "DeepSupervisionWrapper(\n  (loss): DC_and_CE_loss(\n    (ce): RobustCrossEntropyLoss()\n    (dc): OptimizedModule(\n      (_orig_mod): MemoryEfficientSoftDiceLoss()\n    )\n  )\n)",
+    "lr_scheduler": "<nnunetv2.training.lr_scheduler.polylr.PolyLRScheduler object at 0x147e2c1a8eb0>",
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+    "network": "OptimizedModule",
+    "num_epochs": "8000",
+    "num_input_channels": "1",
+    "num_iterations_per_epoch": "250",
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+    "optimizer": "SGD (\nParameter Group 0\n    dampening: 0\n    differentiable: False\n    foreach: None\n    initial_lr: 0.01\n    lr: 0.01\n    maximize: False\n    momentum: 0.99\n    nesterov: True\n    weight_decay: 3e-05\n)",
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+    "output_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres",
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+    "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres",
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+    "unpack_dataset": "True",
+    "was_initialized": "True",
+    "weight_decay": "3e-05"
+}

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+    "disable_checkpointing": "False",
+    "enable_deep_supervision": "True",
+    "fold": "1",
+    "folder_with_segs_from_previous_stage": "None",
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+    "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}",
+    "configuration_name": "3d_fullres",
+    "cudnn_version": 8902,
+    "current_epoch": "0",
+    "dataloader_train": "<batchgenerators.dataloading.nondet_multi_threaded_augmenter.NonDetMultiThreadedAugmenter object at 0x1504e8ddbdf0>",
+    "dataloader_train.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x1504e8ddb1f0>",
+    "dataloader_train.num_processes": "12",
+    "dataloader_train.transform": "None",
+    "dataloader_val": "<batchgenerators.dataloading.nondet_multi_threaded_augmenter.NonDetMultiThreadedAugmenter object at 0x1504e8ddb4f0>",
+    "dataloader_val.generator": "<nnunetv2.training.dataloading.data_loader_3d.nnUNetDataLoader3D object at 0x1504e8ddb2b0>",
+    "dataloader_val.num_processes": "6",
+    "dataloader_val.transform": "None",
+    "dataset_json": "{'channel_names': {'0': 'FLAIR'}, 'labels': {'background': 0, 'Lesion': 1}, 'numTraining': 668, 'file_ending': '.nii.gz', 'overwrite_image_reader_writer': 'SimpleITKIO'}",
+    "device": "cuda:0",
+    "disable_checkpointing": "False",
+    "enable_deep_supervision": "True",
+    "fold": "4",
+    "folder_with_segs_from_previous_stage": "None",
+    "gpu_name": "NVIDIA H100 80GB HBM3",
+    "grad_scaler": "<torch.cuda.amp.grad_scaler.GradScaler object at 0x1504e95a3f70>",
+    "hostname": "lg02e16",
+    "inference_allowed_mirroring_axes": "(0, 1, 2)",
+    "initial_lr": "0.01",
+    "is_cascaded": "False",
+    "is_ddp": "False",
+    "label_manager": "<nnunetv2.utilities.label_handling.label_handling.LabelManager object at 0x1504e95a3fd0>",
+    "local_rank": "0",
+    "log_file": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4/training_log_2024_11_21_10_40_22.txt",
+    "logger": "<nnunetv2.training.logging.nnunet_logger.nnUNetLogger object at 0x1504e95a3dc0>",
+    "loss": "DeepSupervisionWrapper(\n  (loss): DC_and_CE_loss(\n    (ce): RobustCrossEntropyLoss()\n    (dc): OptimizedModule(\n      (_orig_mod): MemoryEfficientSoftDiceLoss()\n    )\n  )\n)",
+    "lr_scheduler": "<nnunetv2.training.lr_scheduler.polylr.PolyLRScheduler object at 0x1504e8ec0d60>",
+    "my_init_kwargs": "{'plans': {'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 106, 'patch_size': [160, 192], 'median_image_size_in_voxels': [154.0, 185.0], 'spacing': [0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}, 'configuration': '3d_fullres', 'fold': 4, 'dataset_json': {'channel_names': {'0': 'FLAIR'}, 'labels': {'background': 0, 'Lesion': 1}, 'numTraining': 668, 'file_ending': '.nii.gz', 'overwrite_image_reader_writer': 'SimpleITKIO'}, 'unpack_dataset': True, 'device': device(type='cuda')}",
+    "network": "OptimizedModule",
+    "num_epochs": "8000",
+    "num_input_channels": "1",
+    "num_iterations_per_epoch": "250",
+    "num_val_iterations_per_epoch": "50",
+    "optimizer": "SGD (\nParameter Group 0\n    dampening: 0\n    differentiable: False\n    foreach: None\n    initial_lr: 0.01\n    lr: 0.01\n    maximize: False\n    momentum: 0.99\n    nesterov: True\n    weight_decay: 3e-05\n)",
+    "output_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/fold_4",
+    "output_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_trained_models/Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres",
+    "oversample_foreground_percent": "0.33",
+    "plans_manager": "{'dataset_name': 'Dataset004_WML', 'plans_name': 'nnUNetPlans', 'original_median_spacing_after_transp': [1.0, 0.9000000059604645, 0.9000000059604645], 'original_median_shape_after_transp': [144, 177, 190], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [2, 0, 1], 'transpose_backward': [1, 2, 0], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 106, 'patch_size': [160, 192], 'median_image_size_in_voxels': [154.0, 185.0], 'spacing': [0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 512, 512], 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': [[3, 3], [3, 3], [3, 3], [3, 3], [3, 3], [3, 3]], 'strides': [[1, 1], [2, 2], [2, 2], [2, 2], [2, 2], [2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm2d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': True}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [112, 128, 160], 'median_image_size_in_voxels': [133.0, 154.0, 185.0], 'spacing': [1.0, 0.9000000059604645, 0.9000000059604645], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [True], 'resampling_fn_data': 'resample_data_or_seg_to_shape', 'resampling_fn_seg': 'resample_data_or_seg_to_shape', 'resampling_fn_data_kwargs': {'is_seg': False, 'order': 3, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_seg_kwargs': {'is_seg': True, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'resampling_fn_probabilities': 'resample_data_or_seg_to_shape', 'resampling_fn_probabilities_kwargs': {'is_seg': False, 'order': 1, 'order_z': 0, 'force_separate_z': None}, 'architecture': {'network_class_name': 'dynamic_network_architectures.architectures.unet.PlainConvUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [2, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_conv_per_stage': [2, 2, 2, 2, 2, 2], 'n_conv_per_stage_decoder': [2, 2, 2, 2, 2], 'conv_bias': True, 'norm_op': 'torch.nn.modules.instancenorm.InstanceNorm3d', 'norm_op_kwargs': {'eps': 1e-05, 'affine': True}, 'dropout_op': None, 'dropout_op_kwargs': None, 'nonlin': 'torch.nn.LeakyReLU', 'nonlin_kwargs': {'inplace': True}}, '_kw_requires_import': ['conv_op', 'norm_op', 'dropout_op', 'nonlin']}, 'batch_dice': False}}, 'experiment_planner_used': 'ExperimentPlanner', 'label_manager': 'LabelManager', 'foreground_intensity_properties_per_channel': {'0': {'max': 3688541.5, 'mean': 63206.06989644738, 'median': 167.43850708007812, 'min': 0.0, 'percentile_00_5': 47.72833251953125, 'percentile_99_5': 2077017.5018749982, 'std': 327313.09328078595}}}",
+    "preprocessed_dataset_folder": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML/nnUNetPlans_3d_fullres",
+    "preprocessed_dataset_folder_base": "/sc/arion/projects/becklab/Francesco/Models/nnUNet_v2/nnUNet_preprocessed/Dataset004_WML",
+    "save_every": "50",
+    "torch_version": "2.1.2+cu121",
+    "unpack_dataset": "True",
+    "was_initialized": "True",
+    "weight_decay": "3e-05"
+}

Dataset004_WML/nnUNetTrainer_8000epochs__nnUNetPlans__3d_fullres/plans.json

@@ -0,0 +1,345 @@
+{
+    "dataset_name": "Dataset004_WML",
+    "plans_name": "nnUNetPlans",
+    "original_median_spacing_after_transp": [
+        1.0,
+        0.9000000059604645,
+        0.9000000059604645
+    ],
+    "original_median_shape_after_transp": [
+        144,
+        177,
+        190
+    ],
+    "image_reader_writer": "SimpleITKIO",
+    "transpose_forward": [
+        2,
+        0,
+        1
+    ],
+    "transpose_backward": [
+        1,
+        2,
+        0
+    ],
+    "configurations": {
+        "2d": {
+            "data_identifier": "nnUNetPlans_2d",
+            "preprocessor_name": "DefaultPreprocessor",
+            "batch_size": 106,
+            "patch_size": [
+                160,
+                192
+            ],
+            "median_image_size_in_voxels": [
+                154.0,
+                185.0
+            ],
+            "spacing": [
+                0.9000000059604645,
+                0.9000000059604645
+            ],
+            "normalization_schemes": [
+                "ZScoreNormalization"
+            ],
+            "use_mask_for_norm": [
+                true
+            ],
+            "resampling_fn_data": "resample_data_or_seg_to_shape",
+            "resampling_fn_seg": "resample_data_or_seg_to_shape",
+            "resampling_fn_data_kwargs": {
+                "is_seg": false,
+                "order": 3,
+                "order_z": 0,
+                "force_separate_z": null
+            },
+            "resampling_fn_seg_kwargs": {
+                "is_seg": true,
+                "order": 1,
+                "order_z": 0,
+                "force_separate_z": null
+            },
+            "resampling_fn_probabilities": "resample_data_or_seg_to_shape",
+            "resampling_fn_probabilities_kwargs": {
+                "is_seg": false,
+                "order": 1,
+                "order_z": 0,
+                "force_separate_z": null
+            },
+            "architecture": {
+                "network_class_name": "dynamic_network_architectures.architectures.unet.PlainConvUNet",
+                "arch_kwargs": {
+                    "n_stages": 6,
+                    "features_per_stage": [
+                        32,
+                        64,
+                        128,
+                        256,
+                        512,
+                        512
+                    ],
+                    "conv_op": "torch.nn.modules.conv.Conv2d",
+                    "kernel_sizes": [
+                        [
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3
+                        ]
+                    ],
+                    "strides": [
+                        [
+                            1,
+                            1
+                        ],
+                        [
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2
+                        ]
+                    ],
+                    "n_conv_per_stage": [
+                        2,
+                        2,
+                        2,
+                        2,
+                        2,
+                        2
+                    ],
+                    "n_conv_per_stage_decoder": [
+                        2,
+                        2,
+                        2,
+                        2,
+                        2
+                    ],
+                    "conv_bias": true,
+                    "norm_op": "torch.nn.modules.instancenorm.InstanceNorm2d",
+                    "norm_op_kwargs": {
+                        "eps": 1e-05,
+                        "affine": true
+                    },
+                    "dropout_op": null,
+                    "dropout_op_kwargs": null,
+                    "nonlin": "torch.nn.LeakyReLU",
+                    "nonlin_kwargs": {
+                        "inplace": true
+                    }
+                },
+                "_kw_requires_import": [
+                    "conv_op",
+                    "norm_op",
+                    "dropout_op",
+                    "nonlin"
+                ]
+            },
+            "batch_dice": true
+        },
+        "3d_fullres": {
+            "data_identifier": "nnUNetPlans_3d_fullres",
+            "preprocessor_name": "DefaultPreprocessor",
+            "batch_size": 2,
+            "patch_size": [
+                112,
+                128,
+                160
+            ],
+            "median_image_size_in_voxels": [
+                133.0,
+                154.0,
+                185.0
+            ],
+            "spacing": [
+                1.0,
+                0.9000000059604645,
+                0.9000000059604645
+            ],
+            "normalization_schemes": [
+                "ZScoreNormalization"
+            ],
+            "use_mask_for_norm": [
+                true
+            ],
+            "resampling_fn_data": "resample_data_or_seg_to_shape",
+            "resampling_fn_seg": "resample_data_or_seg_to_shape",
+            "resampling_fn_data_kwargs": {
+                "is_seg": false,
+                "order": 3,
+                "order_z": 0,
+                "force_separate_z": null
+            },
+            "resampling_fn_seg_kwargs": {
+                "is_seg": true,
+                "order": 1,
+                "order_z": 0,
+                "force_separate_z": null
+            },
+            "resampling_fn_probabilities": "resample_data_or_seg_to_shape",
+            "resampling_fn_probabilities_kwargs": {
+                "is_seg": false,
+                "order": 1,
+                "order_z": 0,
+                "force_separate_z": null
+            },
+            "architecture": {
+                "network_class_name": "dynamic_network_architectures.architectures.unet.PlainConvUNet",
+                "arch_kwargs": {
+                    "n_stages": 6,
+                    "features_per_stage": [
+                        32,
+                        64,
+                        128,
+                        256,
+                        320,
+                        320
+                    ],
+                    "conv_op": "torch.nn.modules.conv.Conv3d",
+                    "kernel_sizes": [
+                        [
+                            3,
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3,
+                            3
+                        ],
+                        [
+                            3,
+                            3,
+                            3
+                        ]
+                    ],
+                    "strides": [
+                        [
+                            1,
+                            1,
+                            1
+                        ],
+                        [
+                            2,
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2,
+                            2
+                        ],
+                        [
+                            2,
+                            2,
+                            2
+                        ],
+                        [
+                            1,
+                            2,
+                            2
+                        ]
+                    ],
+                    "n_conv_per_stage": [
+                        2,
+                        2,
+                        2,
+                        2,
+                        2,
+                        2
+                    ],
+                    "n_conv_per_stage_decoder": [
+                        2,
+                        2,
+                        2,
+                        2,
+                        2
+                    ],
+                    "conv_bias": true,
+                    "norm_op": "torch.nn.modules.instancenorm.InstanceNorm3d",
+                    "norm_op_kwargs": {
+                        "eps": 1e-05,
+                        "affine": true
+                    },
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+                    "dropout_op_kwargs": null,
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+}