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PyTorch 2.5 introduces the torch.onnx.export(..., dynamo=True) option and an improved export logic for converting models to ONNX. We recommend optimum to leverage this feature.
Motivation
The torch.onnx.export(..., dynamo=True) logic leverages new model capturing mechanism offered by torch.export. It is how PyTorch will capture models moving forward. Additionally, we have better optimization and external data support built into this logic path.
Hi! The dynamo=True option in PyTorch 2.5 uses a new logic the leverages torch.export ExportedProgram and the ONNX IR for capturing graph and constructing ONNX models. It is more robust and produces more optimized graphs than the current dynamo_export. dynamo_export will be updated to use the same logic starting from PyTorch 2.6 (tentative).
Feature request
PyTorch 2.5 introduces the
torch.onnx.export(..., dynamo=True)
option and an improved export logic for converting models to ONNX. We recommend optimum to leverage this feature.Motivation
The
torch.onnx.export(..., dynamo=True)
logic leverages new model capturing mechanism offered bytorch.export
. It is how PyTorch will capture models moving forward. Additionally, we have better optimization and external data support built into this logic path.This is a continuation of #1712
Your contribution
I can create a PR
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