add env setup and log for nnunet training

model_training/env_snapshot.txt

@@ -0,0 +1,106 @@
+acvl_utils==0.2.5
+batchgenerators==0.25.1
+batchgeneratorsv2==0.3.0
+blosc2==3.10.0
+certifi==2022.12.7
+charset-normalizer==2.1.1
+connected-components-3d==3.25.0
+contourpy==1.3.2
+cycler==0.12.1
+dynamic_network_architectures==0.4.2
+einops==0.8.1
+fft-conv-pytorch==1.2.0
+filelock==3.13.1
+fonttools==4.60.1
+fsspec==2024.6.1
+future==1.0.0
+graphviz==0.21
+hf-xet==1.1.10
+huggingface-hub==0.35.3
+idna==3.4
+imagecodecs==2025.3.30
+imageio==2.37.0
+importlib_resources==6.5.2
+Jinja2==3.1.4
+joblib==1.5.2
+kiwisolver==1.4.9
+lazy_loader==0.4
+linecache2==1.0.0
+MarkupSafe==2.1.5
+matplotlib==3.10.7
+monai==1.5.1
+mpmath==1.3.0
+msgpack==1.1.2
+ndindex==1.10.0
+networkx==3.3
+nibabel==5.3.2
+nnunetv2==2.6.2
+numexpr==2.13.1
+numpy==2.1.2
+packaging==25.0
+pandas==2.3.3
+pillow==11.0.0
+platformdirs==4.5.0
+py-cpuinfo==9.0.0
+pyparsing==3.2.5
+python-dateutil==2.9.0.post0
+pytz==2025.2
+PyYAML==6.0.3
+requests==2.28.1
+safetensors==0.6.2
+scikit-image==0.25.2
+scikit-learn==1.7.2
+scipy==1.15.3
+seaborn==0.13.2
+simpleitk==2.5.2
+six==1.17.0
+sympy==1.13.3
+threadpoolctl==3.6.0
+tifffile==2025.5.10
+timm==1.0.20
+torch==2.7.1+cu128
+torchaudio==2.7.1
+torchvision==0.22.1
+tqdm==4.67.1
+traceback2==1.4.0
+triton==3.3.1
+typing_extensions==4.12.2
+tzdata==2025.2
+unittest2==1.1.0
+urllib3==1.26.13
+yacs==0.1.8
+==== nnU-Net Environment Snapshot ====
+Timestamp: 2025-10-10T00:46:14.777088
+
+--- System ---
+OS: Linux-6.8.0-1013-nvidia-64k-aarch64-with-glibc2.35
+Architecture: aarch64
+Python: 3.10.12 (main, May 27 2025, 17:12:29) [GCC 11.4.0]
+
+--- CUDA / GPU ---
+Torch: 2.7.1+cu128
+CUDA available: True
+CUDA version: 12.8
+cuDNN version: 90800
+GPU 0: NVIDIA GH200 480GB
+
+--- nnU-Net Environment Variables ---
+CUDA_MODULE_LOADING=LAZY
+LD_LIBRARY_PATH=/usr/mpi/gcc/openmpi-4.1.7rc1/lib:/usr/mpi/gcc/openmpi-4.1.7rc1/lib64
+PATH=/home/ubuntu/wcm/env/nnunet/bin:/home/ubuntu/.local/bin:/usr/mpi/gcc/openmpi-4.1.7rc1/bin:/home/ubuntu/.local/bin:/home/ubuntu/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
+nnUNet_preprocessed=nnUNet_preprocessed
+nnUNet_raw=nnUNet_raw
+nnUNet_results=nnUNet_results
+
+--- Installed Key Packages ---
+nnunetv2: 2.6.2
+torch: 2.7.1+cu128
+torchvision: 0.22.1
+numpy: 2.1.2
+scipy: 1.15.3
+nibabel: 5.3.2
+pandas: 2.3.3
+opencv-python: not found
+matplotlib: 3.10.7
+
+--- All Installed Packages ---

model_training/preprocess_D101.log

@@ -0,0 +1,164 @@
+Fingerprint extraction...
+Dataset101_FinalSet
+Using <class 'nnunetv2.imageio.simpleitk_reader_writer.SimpleITKIO'> as reader/writer
+
+####################
+verify_dataset_integrity Done. 
+If you didn't see any error messages then your dataset is most likely OK!
+####################
+
+Using <class 'nnunetv2.imageio.simpleitk_reader_writer.SimpleITKIO'> as reader/writer
+Experiment planning...
+
+############################
+INFO: You are using the old nnU-Net default planner. We have updated our recommendations. Please consider using those instead! Read more here: https://github.com/MIC-DKFZ/nnUNet/blob/master/documentation/resenc_presets.md
+############################
+
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        0.89722656 0.89722656]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         497.08737864 497.08737864]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        0.92414336 0.92414336]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         482.60910548 482.60910548]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        0.95186766 0.95186766]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         468.55252959 468.55252959]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        0.98042369 0.98042369]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         454.90536853 454.90536853]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5       1.0098364 1.0098364]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.        441.6556976 441.6556976]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        1.04013149 1.04013149]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         428.79193942 428.79193942]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        1.07133544 1.07133544]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         416.30285381 416.30285381]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5       1.1034755 1.1034755]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         404.17752797 404.17752797]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        1.13657977 1.13657977]. 
+Current patch size: (np.int64(112), np.int64(128), np.int64(128)). 
+Current median shape: [391.         392.40536696 392.40536696]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        1.17067716 1.17067716]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(112)). 
+Current median shape: [391.         380.97608443 380.97608443]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        1.20579747 1.20579747]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(112)). 
+Current median shape: [391.         369.87969362 369.87969362]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5       1.2419714 1.2419714]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(112)). 
+Current median shape: [391.         359.10649866 359.10649866]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.5        1.27923054 1.27923054]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [391.         348.64708608 348.64708608]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.575      1.31760746 1.31760746]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [379.61165049 338.49231658 338.49231658]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.65225    1.35713568 1.35713568]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [368.55500047 328.63331707 328.63331707]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.7318175  1.39784975 1.39784975]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [357.82038881 319.06147288 319.06147288]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.81377203 1.43978524 1.43978524]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [347.39843574 309.76842027 309.76842027]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.89818519 1.4829788  1.4829788 ]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [337.28003469 300.7460391  300.7460391 ]
+Attempting to find 3d_lowres config. 
+Current spacing: [2.98513074 1.52746816 1.52746816]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [327.45634436 291.98644573 291.98644573]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.07468466 1.57329221 1.57329221]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [317.91878094 283.48198614 283.48198614]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.1669252  1.62049097 1.62049097]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [308.65901062 275.22522927 275.22522927]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.26193296 1.6691057  1.6691057 ]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [299.66894235 267.20896045 267.20896045]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.35979095 1.71917887 1.71917887]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [290.94072072 259.4261752  259.4261752 ]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.46058468 1.77075424 1.77075424]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [282.46671915 251.87007301 251.87007301]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.56440222 1.82387687 1.82387687]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [274.23953316 244.53405146 244.53405146]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.67133428 1.87859317 1.87859317]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [266.25197394 237.41170045 237.41170045]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.78147431 1.93495097 1.93495097]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [258.49706208 230.49679655 230.49679655]
+Attempting to find 3d_lowres config. 
+Current spacing: [3.89491854 1.9929995  1.9929995 ]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [250.96802143 223.78329762 223.78329762]
+Attempting to find 3d_lowres config. 
+Current spacing: [4.0117661  2.05278948 2.05278948]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [243.65827324 217.2653375  217.2653375 ]
+Attempting to find 3d_lowres config. 
+Current spacing: [4.13211908 2.11437317 2.11437317]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [236.56143033 210.93722087 210.93722087]
+Attempting to find 3d_lowres config. 
+Current spacing: [4.25608265 2.17780436 2.17780436]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [229.67129158 204.79341832 204.79341832]
+Attempting to find 3d_lowres config. 
+Current spacing: [4.38376513 2.24313849 2.24313849]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [222.98183648 198.82856148 198.82856148]
+Attempting to find 3d_lowres config. 
+Current spacing: [4.51527809 2.31043265 2.31043265]. 
+Current patch size: (np.int64(128), np.int64(128), np.int64(128)). 
+Current median shape: [216.48721989 193.03743833 193.03743833]
+2D U-Net configuration:
+{'data_identifier': 'nnUNetPlans_2d', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 12, 'patch_size': (np.int64(512), np.int64(512)), 'median_image_size_in_voxels': array([512., 512.]), 'spacing': array([0.87109375, 0.87109375]), 'normalization_schemes': ['CTNormalization'], '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.PlainConvUNet', 'arch_kwargs': {'n_stages': 8, 'features_per_stage': (32, 64, 128, 256, 512, 512, 512, 512), 'conv_op': 'torch.nn.modules.conv.Conv2d', 'kernel_sizes': ((3, 3), (3, 3), (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), (2, 2), (2, 2)), 'n_conv_per_stage': (2, 2, 2, 2, 2, 2, 2, 2), 'n_conv_per_stage_decoder': (2, 2, 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}
+
+Using <class 'nnunetv2.imageio.simpleitk_reader_writer.SimpleITKIO'> as reader/writer
+3D lowres U-Net configuration:
+{'data_identifier': 'nnUNetPlans_3d_lowres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': (np.int64(128), np.int64(128), np.int64(128)), 'median_image_size_in_voxels': (216, 193, 193), 'spacing': array([4.51527809, 2.31043265, 2.31043265]), 'normalization_schemes': ['CTNormalization'], '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.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), (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.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 U-Net configuration:
+{'data_identifier': 'nnUNetPlans_3d_fullres', 'preprocessor_name': 'DefaultPreprocessor', 'batch_size': 2, 'patch_size': (np.int64(112), np.int64(128), np.int64(128)), 'median_image_size_in_voxels': array([391., 512., 512.]), 'spacing': array([2.5       , 0.87109375, 0.87109375]), 'normalization_schemes': ['CTNormalization'], '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.PlainConvUNet', '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), (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.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}
+
+Plans were saved to nnUNet_preprocessed/Dataset101_FinalSet/nnUNetPlans.json
+Preprocessing...
+Preprocessing dataset Dataset101_FinalSet
+Configuration: 2d...
+Configuration: 3d_fullres...
+Configuration: 3d_lowres...