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@KumoLiu KumoLiu released this 21 May 08:24
· 145 commits to dev since this release
1.3.1
96bfda0
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Learn about vigilant mode.

Added

  • Support for by_measure argument in RemoveSmallObjects (#7137)
  • Support for pretrained flag in ResNet (#7095)
  • Support for uploading and downloading bundles to and from the Hugging Face Hub (#6454)
  • Added weight parameter in DiceLoss to apply weight to voxels of each class (#7158)
  • Support for returning dice for each class in DiceMetric (#7163)
  • Introduced ComponentStore for storage purposes (#7159)
  • Added utilities used in MONAI Generative (#7134)
  • Enabled Python 3.11 support for convert_to_torchscript and convert_to_onnx (#7182)
  • Support for MLflow in AutoRunner (#7176)
  • fname_regex option in PydicomReader (#7181)
  • Allowed setting AutoRunner parameters from config (#7175)
  • VoxelMorphUNet and VoxelMorph (#7178)
  • Enabled cache option in GridPatchDataset (#7180)
  • Introduced class_labels option in write_metrics_reports for improved readability (#7249)
  • DiffusionLoss for image registration task (#7272)
  • Supported specifying filename in Saveimage (#7318)
  • Compile support in SupervisedTrainer and SupervisedEvaluator (#7375)
  • mlflow_experiment_name support in Auto3DSeg (#7442)
  • Arm support (#7500)
  • BarlowTwinsLoss for representation learning (#7530)
  • SURELoss and ConjugateGradient for diffusion models (#7308)
  • Support for CutMix, CutOut, and MixUp augmentation techniques (#7198)
  • meta_file and logging_file options to BundleWorkflow (#7549)
  • properties_path option to BundleWorkflow for customized properties (#7542)
  • Support for both soft and hard clipping in ClipIntensityPercentiles (#7535)
  • Support for not saving artifacts in MLFlowHandler (#7604)
  • Support for multi-channel images in PerceptualLoss (#7568)
  • Added ResNet backbone for FlexibleUNet (#7571)
  • Introduced dim_head option in SABlock to set dimensions for each head (#7664)
  • Direct links to github source code to docs (#7738, #7779)

misc.

  • Refactored list_data_collate and collate_meta_tensor to utilize the latest PyTorch API (#7165)
  • Added str method in Metric base class (#7487)
  • Made enhancements for testing files (#7662, #7670, #7663, #7671, #7672)
  • Improved documentation for bundles (#7116)

Fixed

transforms

  • Addressed issue where lazy mode was ignored in SpatialPadd (#7316)
  • Tracked applied operations in ImageFilter (#7395)
  • Warnings are now given only if missing class is not set to 0 in generate_label_classes_crop_centers (#7602)
  • Input is now always converted to C-order in distance_transform_edt to ensure consistent behavior (#7675)

data

  • Modified .npz file behavior to use keys in NumpyReader (#7148)
  • Handled corrupted cached files in PersistentDataset (#7244)
  • Corrected affine update in NrrdReader (#7415)

metrics and losses

  • Addressed precision issue in get_confusion_matrix (#7187)
  • Harmonized and clarified documentation and tests for dice losses variants (#7587)

networks

  • Removed hard-coded spatial_dims in SwinTransformer (#7302)
  • Fixed learnable position_embeddings in PatchEmbeddingBlock (#7564, #7605)
  • Removed memory_pool_limit in TRT config (#7647)
  • Propagated kernel_size to ConvBlocks within AttentionUnet (#7734)
  • Addressed hard-coded activation layer in ResNet (#7749)

bundle

  • Resolved bundle download issue (#7280)
  • Updated bundle_root directory for NNIGen (#7586)
  • Checked for num_fold and failed early if incorrect (#7634)
  • Enhanced logging logic in ConfigWorkflow (#7745)

misc.

  • Enabled chaining in Auto3DSeg CLI (#7168)
  • Addressed useless error message in nnUNetV2Runner (#7217)
  • Resolved typing and deprecation issues in Mypy (#7231)
  • Quoted $PY_EXE variable to handle Python path that contains spaces in Bash (#7268)
  • Improved documentation, code examples, and warning messages in various modules (#7234, #7213, #7271, #7326, #7569, #7584)
  • Fixed typos in various modules (#7321, #7322, #7458, #7595, #7612)
  • Enhanced docstrings in various modules (#7245, #7381, #7746)
  • Handled error when data is on CPU in DataAnalyzer (#7310)
  • Updated version requirements for third-party packages (#7343, #7344, #7384, #7448, #7659, #7704, #7744, #7742, #7780)
  • Addressed incorrect slice compute in ImageStats (#7374)
  • Avoided editing a loop's mutable iterable to address B308 (#7397)
  • Fixed issue with CUDA_VISIBLE_DEVICES setting being ignored (#7408, #7581)
  • Avoided changing Python version in CICD (#7424)
  • Renamed partial to callable in instantiate mode (#7413)
  • Imported AttributeError for Python 3.12 compatibility (#7482)
  • Updated nnUNetV2Runner to support nnunetv2 2.2 (#7483)
  • Used uint8 instead of int8 in LabelStats (#7489)
  • Utilized subprocess for nnUNet training (#7576)
  • Addressed deprecated warning in ruff (#7625)
  • Fixed downloading failure on FIPS machine (#7698)
  • Updated torch_tensorrt compile parameters to avoid warning (#7714)
  • Restrict Auto3DSeg fold input based on datalist (#7778)

Changed

  • Base Docker image upgraded to nvcr.io/nvidia/pytorch:24.03-py3 from nvcr.io/nvidia/pytorch:23.08-py3

Removed

  • Removed unrecommended star-arg unpacking after a keyword argument, addressed B026 (#7262)
  • Skipped old PyTorch version test for SwinUNETR (#7266)
  • Dropped docker build workflow and migrated to Nvidia Blossom system (#7450)
  • Dropped Python 3.8 test on quick-py3 workflow (#7719)
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