.. include:: /content/common.rsts

Release Notes |ndash| Release 2.5
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Key Features and Enhancements
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- [Jax] Added support for sliding window attention (SWA)
  in context parallel ring attention using THD format and striped sharding.
- [Jax] Improved performance for per-tensor scaling FP8 recipe.
- [PyTorch] Enabled FP8 tensor-parallel communication for FP8 block scaling recipe
  for Hopper by supporting coalesced gather of FP8 quantized tensors.
- [PyTorch] Optimized MXFP8 Userbuffers implementation by overlapping wgrad NCCL all-gather with dgrad GEMM..
- [PyTorch] Added support for CPU offloading
  when using FP8 parameters.
- [PyTorch] Added support for
  Context Parallel for Multi Latent Attention (MLA).
- [PyTorch] Reduced CPU overhead in MoE.
- [C][PyTorch] Improved performance for FP8 padding
  and unpadding kernels for MoE.
- [Jax] Added MXFP8 support for the ``GroupedDense`` module
  and handle the case with zero input tokens.
- Added support for Python 3.12+
- Added support for head dimension (``head_dim``) > 128 for attention
  for all architectures.
- [PyTorch] Added support for FP8 current scaling
  in operation-based API.



Fixed Issues
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- [Jax] Fixed a numerical error in the scaled masked softmax kernel.
- [Jax] Fixed output dtype for FP8 GEMM.
- [PyTorch] Fixed a bug that appeared when the FP8 recipe is changed
  in between training steps.
- [PyTorch] Made miscellaneous fixes in ``TransformerLayer``:
  Pass missing arguments *cu_seqlens* and *max_seqlen* to cross-attention and allow ``attn_input_format=thd``.
- [PyTorch] Fixed a crash when loading checkpoints
  from previously generated Transformer Engine versions.
- [PyTorch] Made miscellaneous fixes in CPU offloading logic.
- [PyTorch] Fixed a numerical issue in cross-entropy loss.
- [C][PyTorch][Jax] Fixed source installation
  when using ``NVTE_FRAMEWORK=all``.
- [PyTorch] Fixed a crash in ``GroupedLinear`` when using CUDA graphs.
   

Known Issues in This Release
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There are no known issues in this release.


Breaking Changes in This Release
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There are no breaking changes in this release.


Deprecated Features
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There are no deprecated features in this release.


Miscellaneous
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There are no miscellaneous issues in this release.