diff --git a/Dataset260/nnUNetTrainerMRCT_loss_masked_perception_masked__nnUNetResEncUNetLPlans__3d_fullres/fold_4/checkpoint_final.pth b/Dataset260/nnUNetTrainerMRCT_loss_masked_perception_masked__nnUNetResEncUNetLPlans__3d_fullres/fold_4/checkpoint_final.pth deleted file mode 100644 index 634582496060a20e55d266ca368baf9ac77db870..0000000000000000000000000000000000000000 --- a/Dataset260/nnUNetTrainerMRCT_loss_masked_perception_masked__nnUNetResEncUNetLPlans__3d_fullres/fold_4/checkpoint_final.pth +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:618a99dd20532d8eda6510194973c0d48c4914122d8f2a32aae4d177b9a7e586 -size 815581869 diff --git a/Dataset260/nnUNetTrainerMRCT_loss_masked_perception_masked__nnUNetResEncUNetLPlans__3d_fullres/fold_4/debug.json b/Dataset260/nnUNetTrainerMRCT_loss_masked_perception_masked__nnUNetResEncUNetLPlans__3d_fullres/fold_4/debug.json deleted file mode 100644 index 72d2abcf7dce070bdf4f2785a68d23c93a0b73ba..0000000000000000000000000000000000000000 --- a/Dataset260/nnUNetTrainerMRCT_loss_masked_perception_masked__nnUNetResEncUNetLPlans__3d_fullres/fold_4/debug.json +++ /dev/null @@ -1,58 +0,0 @@ -{ - "_best_ema": "None", - "aim_run": ">", - "batch_size": "2", - "configuration_manager": "{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [40, 192, 224], 'median_image_size_in_voxels': [99.0, 442.0, 465.0], 'spacing': [3.0, 1.0, 1.0], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [False], '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', 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Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (4): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (5): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (4): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 320, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 320, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[2, 2, 2], stride=[2, 2, 2], padding=0)\n (1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 320, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 320, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (4): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (5): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (5): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[1, 2, 2], stride=[1, 2, 2], padding=0)\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (4): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (5): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n )\n (decoder): UNetDecoder(\n (encoder): ResidualEncoder(\n (stem): StackedConvBlocks(\n (convs): Sequential(\n (0): ConvDropoutNormReLU(\n (conv): Conv3d(1, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (norm): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(1, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (1): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n (stages): Sequential(\n (0): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(32, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (norm): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(32, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (1): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(32, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (norm): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(32, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (1): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (1): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(32, 64, kernel_size=(3, 3, 3), stride=(1, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(32, 64, kernel_size=(3, 3, 3), stride=(1, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[1, 2, 2], stride=[1, 2, 2], padding=0)\n (1): ConvDropoutNormReLU(\n (conv): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(32, 64, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(64, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (2): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(64, 128, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(64, 128, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[2, 2, 2], stride=[2, 2, 2], padding=0)\n (1): ConvDropoutNormReLU(\n (conv): Conv3d(64, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(64, 128, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(128, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (3): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(128, 256, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(128, 256, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[2, 2, 2], stride=[2, 2, 2], padding=0)\n (1): ConvDropoutNormReLU(\n (conv): Conv3d(128, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(128, 256, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (4): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (5): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (4): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 320, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 320, kernel_size=(3, 3, 3), stride=(2, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[2, 2, 2], stride=[2, 2, 2], padding=0)\n (1): ConvDropoutNormReLU(\n (conv): Conv3d(256, 320, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(256, 320, kernel_size=(1, 1, 1), stride=(1, 1, 1), bias=False)\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (4): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (5): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n (5): StackedResidualBlocks(\n (blocks): Sequential(\n (0): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 2, 2), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 2, 2), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n (skip): Sequential(\n (0): AvgPool3d(kernel_size=[1, 2, 2], stride=[1, 2, 2], padding=0)\n )\n )\n (1): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (2): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (3): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (4): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n (5): BasicBlockD(\n (conv1): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n (conv2): ConvDropoutNormReLU(\n (conv): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (all_modules): Sequential(\n (0): Conv3d(320, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n )\n )\n (nonlin2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n )\n (stages): ModuleList(\n (0): StackedConvBlocks(\n (convs): Sequential(\n (0): ConvDropoutNormReLU(\n (conv): Conv3d(640, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(640, 320, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(320, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n (1): StackedConvBlocks(\n (convs): Sequential(\n (0): ConvDropoutNormReLU(\n (conv): Conv3d(512, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(512, 256, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n (2): StackedConvBlocks(\n (convs): Sequential(\n (0): ConvDropoutNormReLU(\n (conv): Conv3d(256, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(256, 128, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n (3): StackedConvBlocks(\n (convs): Sequential(\n (0): ConvDropoutNormReLU(\n (conv): Conv3d(128, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (norm): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(128, 64, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1))\n (1): InstanceNorm3d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n (4): StackedConvBlocks(\n (convs): Sequential(\n (0): ConvDropoutNormReLU(\n (conv): Conv3d(64, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (norm): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (nonlin): LeakyReLU(negative_slope=0.01, inplace=True)\n (all_modules): Sequential(\n (0): Conv3d(64, 32, kernel_size=(1, 3, 3), stride=(1, 1, 1), padding=(0, 1, 1))\n (1): InstanceNorm3d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=False)\n (2): LeakyReLU(negative_slope=0.01, inplace=True)\n )\n )\n )\n )\n )\n (transpconvs): ModuleList(\n (0): ConvTranspose3d(320, 320, kernel_size=(1, 2, 2), stride=(1, 2, 2))\n (1): ConvTranspose3d(320, 256, kernel_size=(2, 2, 2), stride=(2, 2, 2))\n (2): ConvTranspose3d(256, 128, kernel_size=(2, 2, 2), stride=(2, 2, 2))\n (3): ConvTranspose3d(128, 64, kernel_size=(2, 2, 2), stride=(2, 2, 2))\n (4): ConvTranspose3d(64, 32, kernel_size=(1, 2, 2), stride=(1, 2, 2))\n )\n (seg_layers): ModuleList(\n (0): Conv3d(320, 62, kernel_size=(1, 1, 1), stride=(1, 1, 1))\n (1): Conv3d(256, 62, kernel_size=(1, 1, 1), stride=(1, 1, 1))\n (2): Conv3d(128, 62, kernel_size=(1, 1, 1), stride=(1, 1, 1))\n (3): Conv3d(64, 62, kernel_size=(1, 1, 1), stride=(1, 1, 1))\n (4): Conv3d(32, 62, kernel_size=(1, 1, 1), stride=(1, 1, 1))\n )\n )\n )\n (L1): L1Loss()\n (image_loss): myMaskedMSE(\n (mse): myMSE()\n )\n)", - "lr_scheduler": "", - "my_init_kwargs": "{'plans': {'dataset_name': 'Dataset260_synthrad2025_task1_MR_AB_pre_v2r_stitched_masked', 'plans_name': 'nnUNetResEncUNetLPlans', 'original_median_spacing_after_transp': [3.0, 1.0, 1.0], 'original_median_shape_after_transp': [99, 442, 465], 'image_reader_writer': 'SimpleITKIO', 'transpose_forward': [0, 1, 2], 'transpose_backward': [0, 1, 2], 'configurations': {'2d': {'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 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{'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.ResidualEncoderUNet', '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_blocks_per_stage': [1, 3, 4, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1], '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, 'next_stage': '3d_cascade_fullres'}, '3d_fullres': {'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': [40, 192, 224], 'median_image_size_in_voxels': [99.0, 442.0, 465.0], 'spacing': [3.0, 1.0, 1.0], 'normalization_schemes': ['ZScoreNormalization'], 'use_mask_for_norm': [False], '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.ResidualEncoderUNet', 'arch_kwargs': {'n_stages': 6, 'features_per_stage': [32, 64, 128, 256, 320, 320], 'conv_op': 'torch.nn.modules.conv.Conv3d', 'kernel_sizes': [[1, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3], [3, 3, 3]], 'strides': [[1, 1, 1], [1, 2, 2], [2, 2, 2], [2, 2, 2], [2, 2, 2], [1, 2, 2]], 'n_blocks_per_stage': [1, 3, 4, 6, 6, 6], 'n_conv_per_stage_decoder': [1, 1, 1, 1, 1], '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': True}, '3d_cascade_fullres': {'inherits_from': '3d_fullres', 'previous_stage': '3d_lowres'}}, 'experiment_planner_used': 'nnUNetPlannerResEncL', 'label_manager': 'LabelManager', 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