There is a release note of NAME_1, try to extract the key updates for the release and summarized it as a promotion paragraph to developers

"

### Added

- Hover-Net based digital pathology workflows including new network, loss, postprocessing, metric, training, and inference modules
- Various enhancements for Auto3dSeg `AutoRunner` including template caching, selection, and a dry-run mode `nni_dry_run`
- Various enhancements for Auto3dSeg algo templates including new state-of-the-art configurations, optimized GPU memory utilization
- New bundle API and configurations to support experiment management including `MLFlowHandler`
- New `bundle.script` API to support model zoo query and download
- `LossMetric` metric to compute loss as cumulative metric measurement
- Transforms and base transform APIs including `RandomizableTrait` and `MedianSmooth`
- `runtime_cache` option for `CacheDataset` and the derived classes to allow for shared caching on the fly
- Flexible name formatter for `SaveImage` transform
- `pending_operations` MetaTensor property and basic APIs for lazy image resampling
- Contrastive sensitivity for SSIM metric
- Extensible backbones for `FlexibleUNet`
- Generalize `SobelGradients` to 3D and any spatial axes
- `warmup_multiplier` option for `WarmupCosineSchedule`
- F beta score metric based on confusion matrix metric
- Support of key overwriting in `LambdaD`
- Basic premerge tests for Python 3.11
- Unit and integration tests for CUDA 11.6, 11.7 and A100 GPU
- `DataAnalyzer` handles minor image-label shape inconsistencies

### Fixed

- Review and enhance previously untyped APIs with additional type annotations and casts
- `switch_endianness` in LoadImage now supports tensor input
- Reduced memory footprint for various Auto3dSeg tests
- Issue of `@` in `NAME_1.bundle.ReferenceResolver`
- Compatibility issue with ITK-Python 5.3 (converting `itkMatrixF44` for default collate)
- Inconsistent of sform and qform when using different backends for `SaveImage`
- `MetaTensor.shape` call now returns a `torch.Size` instead of tuple
- Issue of channel reduction in `GeneralizedDiceLoss`
- Issue of background handling before softmax in `DiceFocalLoss`
- Numerical issue of `LocalNormalizedCrossCorrelationLoss`
- Issue of incompatible view size in `ConfusionMatrixMetric`
- `NetAdapter` compatibility with Torchscript
- Issue of `extract_levels` in `RegUNet`
- Optional `bias_downsample` in `ResNet`
- `dtype` overflow for `ShiftIntensity` transform
- Randomized transforms such as `RandCuCIM` now inherit `RandomizableTrait`
- Please reply with exactly 5 paragraphs and separate each paragraph with two new lines. The very first paragraph must start with the word "name".
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