0.3.0
版本发布时间: 2020-10-05 18:55:34
Project-MONAI/MONAI最新发布版本:1.4.0(2024-10-17 08:54:28)
Added
- Overview document for feature highlights in v0.3.0
- Automatic mixed precision support
- Multi-node, multi-GPU data parallel model training support
- 3 new evaluation metric functions
- 11 new network layers and blocks
- 6 new network architectures
- 14 new transforms, including an I/O adaptor
- Cross validation module for
DecathlonDataset
- Smart Cache module in dataset
-
monai.optimizers
module -
monai.csrc
module - Experimental feature of ImageReader using ITK, Nibabel, Numpy, Pillow (PIL Fork)
- Experimental feature of differentiable image resampling in C++/CUDA
- Ensemble evaluator module
- GAN trainer module
- Initial cross-platform CI environment for C++/CUDA code
- Code style enforcement now includes isort and clang-format
- Progress bar with tqdm
Changed
- Now fully compatible with PyTorch 1.6
- Base Docker image upgraded to
nvcr.io/nvidia/pytorch:20.08-py3
fromnvcr.io/nvidia/pytorch:20.03-py3
- Code contributions now require signing off on the Developer Certificate of Origin (DCO)
- Major work in type hinting finished
- Remote datasets migrated to Open Data on AWS
- Optionally depend on PyTorch-Ignite v0.4.2 instead of v0.3.0
- Optionally depend on torchvision, ITK
- Enhanced CI tests with 8 new testing environments
Removed
-
MONAI/examples
folder (relocated intoProject-MONAI/tutorials
) -
MONAI/research
folder (relocated toProject-MONAI/research-contributions
)
Fixed
-
dense_patch_slices
incorrect indexing - Data type issue in
GeneralizedWassersteinDiceLoss
-
ZipDataset
return value inconsistencies -
sliding_window_inference
indexing anddevice
issues - importing monai modules may cause namespace pollution
- Random data splits issue in
DecathlonDataset
- Issue of randomising a
Compose
transform - Various issues in function type hints
- Typos in docstring and documentation
-
PersistentDataset
issue with existing file folder - Filename issue in the output writers