Update LLM export to use PyTorch 2.7#24549
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### Description This PR updates ONNX Runtime's LLM conversion tools to use [PyTorch 2.7](https://pytorch.org/blog/pytorch-2-7/) and reduces memory usage during export. ### Motivation and Context Importing the `transformers` package with `import transformers` will take a long time because of the many namespaces it has at the top level. It is more efficient to only import the desired class names. Additionally, the benchmarking of the PyTorch model includes the deep copy of the inputs when it does not need to. The deep copy can be performed before measuring latency.
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Description
This PR updates ONNX Runtime's LLM conversion tools to use PyTorch 2.7 and reduces memory usage during export.
Motivation and Context
Importing the
transformerspackage withimport transformerswill take a long time because of the many namespaces it has at the top level. It is more efficient to only import the desired class names. Additionally, the benchmarking of the PyTorch model includes the deep copy of the inputs when it does not need to. The deep copy can be performed before measuring latency.