PyTorch 2.10.0 Release

# PyTorch 2.10.0 Release Notes - [Highlights](#highlights) - [Backwards Incompatible Changes](#backwards-incompatible-changes) - [Deprecations](#deprecations) - [New Features](#new-features) - [Improvements](#improvements) - [Bug fixes](#bug-fixes) - [Performance](#performance) - [Documentation](#documentation) - [Developers](#developers) - [Security](#security) # Highlights Python 3.14 support for torch.compile(). Python 3.14t (freethreaded build) is experimentally supported as well. Reduced kernel launch overhead with combo-kernels horizontal fusion in torchinductor A new varlen_attn() op providing support for ragged and packed sequences Efficient eigenvalue decompositions with DnXgeev torch.compile() now respects use_deterministic_mode DebugMode for tracking dispatched calls and debugging numerical divergence - This makes it simpler to track down subtle numerical bugs. Intel GPUs support: Expand PyTorch support to the latest Panther Lake on Windows and Linux by enabling FP8 (core ops and scaled matmul) and complex MatMul support, and extending SYCL support in the C++ Extension API for Windows custom ops. For more details about these highlighted features, you can look at the [...