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Lightning-AI / torchmetrics

Machine learning metrics for distributed, scalable PyTorch applications.
https://lightning.ai/docs/torchmetrics/
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build(deps): update onnxruntime requirement from <1.20,>=1.12.0 to >=1.12.0,<1.21 in /requirements #2823

Closed dependabot[bot] closed 3 weeks ago

dependabot[bot] commented 3 weeks ago

Updates the requirements on onnxruntime to permit the latest version.

Release notes

Sourced from onnxruntime's releases.

ONNX Runtime v1.20.0

Release Manager: @​apsonawane

Announcements

  • All ONNX Runtime Training packages have been deprecated. ORT 1.19.2 was the last release for which onnxruntime-training (PyPI), onnxruntime-training-cpu (PyPI), Microsoft.ML.OnnxRuntime.Training (Nuget), onnxruntime-training-c (CocoaPods), onnxruntime-training-objc (CocoaPods), and onnxruntime-training-android (Maven Central) were published.
  • ONNX Runtime packages will stop supporting Python 3.8 and Python 3.9. This decision aligns with NumPy Python version support. To continue using ORT with Python 3.8 and Python 3.9, you can use ORT 1.19.2 and earlier.
  • ONNX Runtime 1.20 CUDA packages will include new dependencies that were not required in 1.19 packages. The following dependencies are new: libcudnn_adv.so.9, libcudnn_cnn.so.9, libcudnn_engines_precompiled.so.9, libcudnn_engines_runtime_compiled.so.9, libcudnn_graph.so.9, libcudnn_heuristic.so.9, libcudnn_ops.so.9, libnvrtc.so.12, and libz.so.1.

Build System & Packages

  • Python 3.13 support is included in PyPI packages.
  • ONNX 1.17 support will be delayed until a future release, but the ONNX version used by ONNX Runtime has been patched to include a shape inference change to the Einsum op.
  • DLLs in the Maven build are now digitally signed (fix for issue reported here).
  • (Experimental) vcpkg support added for the CPU EP. The DML EP does not yet support vcpkg, and other EPs have not been tested.

Core

  • MultiLoRA support.
  • Reduced memory utilization.
    • Fixed alignment that was causing mmap to fail for external weights.
    • Eliminated double allocations when deserializing external weights.
    • Added ability to serialize pre-packed weights so that they don’t cause an increase in memory utilization when the model is loaded.
  • Support bfloat16 and float8 data types in python I/O binding API.

Performance

  • INT4 quantized embedding support on CPU and CUDA EPs.
  • Miscellaneous performance improvements and bug fixes.

EPs

CPU

  • FP16 support for MatMulNbits, Clip, and LayerNormalization ops.

CUDA

  • Added support of cuDNN Flash Attention and Lean Attention in MultiHeadAttention op.

TensorRT

QNN

  • QNN HTP support for weight sharing across multiple ORT inference sessions. (See ORT QNN EP documentation for more information.)
  • Support for QNN SDK 2.27.

OpenVINO

  • Added support up to OpenVINO 2024.4.1.
  • Compile-time memory optimizations.
  • Enhancement of ORT EPContext Session option for optimized first inference latency.
  • Added remote tensors to ensure direct memory access for inferencing on NPU.

DirectML

... (truncated)

Commits


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📚 Documentation preview 📚: https://torchmetrics--2823.org.readthedocs.build/en/2823/

codecov[bot] commented 3 weeks ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 99%. Comparing base (fc6b235) to head (259653c).

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #2823 +/- ## ========================================= + Coverage 69% 99% +31% ========================================= Files 344 14 -330 Lines 18828 175 -18653 ========================================= - Hits 12975 174 -12801 + Misses 5853 1 -5852 ```