Added

• Overview of new features in v0.7
• Initial phase of major usability improvements in monai.transforms to support input and backend in PyTorch and NumPy
• Performance enhancements, with profiling and tuning guides for typical use cases
• Reproducing training modules and workflows of state-of-the-art Kaggle competition solutions
• 24 new transforms, including
  • OneOf meta transform
  • DeepEdit guidance signal transforms for interactive segmentation
  • Transforms for self-supervised pre-training
  • Integration of NVIDIA Tools Extension (NVTX)
  • Integration of cuCIM
  • Stain normalization and contextual grid for digital pathology
• Transchex network for vision-language transformers for chest X-ray analysis
• DatasetSummary utility in monai.data
• WarmupCosineSchedule
• Deprecation warnings and documentation support for better backwards compatibility
• Padding with additional kwargs and different backend API
• Additional options such as dropout and norm in various networks and their submodules

Changed

• Base Docker image upgraded to nvcr.io/nvidia/pytorch:21.08-py3 from nvcr.io/nvidia/pytorch:21.06-py3
• Deprecated input argument n_classes, in favor of num_classes
• Deprecated input argument dimensions and ndims, in favor of spatial_dims
• Updated the Sphinx-based documentation theme for better readability
• NdarrayTensor type is replaced by NdarrayOrTensor for simpler annotations
• Self-attention-based network blocks now support both 2D and 3D inputs

Removed

• The deprecated TransformInverter, in favor of monai.transforms.InvertD
• GitHub self-hosted CI/CD pipelines for nightly and post-merge tests
• monai.handlers.utils.evenly_divisible_all_gather
• monai.handlers.utils.string_list_all_gather

Fixed

• A Multi-thread cache writing issue in LMDBDataset
• Output shape convention inconsistencies of the image readers
• Output directory and file name flexibility issue for NiftiSaver, PNGSaver
• Requirement of the label field in test-time augmentation
• Input argument flexibility issues for ThreadDataLoader
• Decoupled Dice and CrossEntropy intermediate results in DiceCELoss
• Improved documentation, code examples, and warning messages in various modules
• Various usability issues reported by users