[ONNX] Drop draft_export in exporter API #161454
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/161454
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 94ffaa7 with merge base ca9fe01 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Use `TORCH_ONNX_ENABLE_DRAFT_EXPORT` to control whether draft_export should be used as a strategy in onnx export. Follow up of #161454 Pull Request resolved: #162225 Approved by: https://github.com/xadupre, https://github.com/titaiwangms
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Use `TORCH_ONNX_ENABLE_DRAFT_EXPORT` to control whether draft_export should be used as a strategy in onnx export. Follow up of pytorch#161454 Pull Request resolved: pytorch#162225 Approved by: https://github.com/xadupre, https://github.com/titaiwangms
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If onnx exporter fallbacks to draft_export with big models, this is taking forever for users, and possibly spam the printout, which keeps users from their stack trace with strict=False. We could consider make another API for draft_export as debugging tool, or combine it with report=True when "model is small"? Pull Request resolved: pytorch#161454 Approved by: https://github.com/justinchuby
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Use `TORCH_ONNX_ENABLE_DRAFT_EXPORT` to control whether draft_export should be used as a strategy in onnx export. Follow up of pytorch#161454 Pull Request resolved: pytorch#162225 Approved by: https://github.com/xadupre, https://github.com/titaiwangms
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Use `TORCH_ONNX_ENABLE_DRAFT_EXPORT` to control whether draft_export should be used as a strategy in onnx export. Follow up of pytorch#161454 Pull Request resolved: pytorch#162225 Approved by: https://github.com/xadupre, https://github.com/titaiwangms
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Use `TORCH_ONNX_ENABLE_DRAFT_EXPORT` to control whether draft_export should be used as a strategy in onnx export. Follow up of pytorch#161454 Pull Request resolved: pytorch#162225 Approved by: https://github.com/xadupre, https://github.com/titaiwangms
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Use `TORCH_ONNX_ENABLE_DRAFT_EXPORT` to control whether draft_export should be used as a strategy in onnx export. Follow up of pytorch#161454 Pull Request resolved: pytorch#162225 Approved by: https://github.com/xadupre, https://github.com/titaiwangms
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If onnx exporter fallbacks to draft_export with big models, this is taking forever for users, and possibly spam the printout, which keeps users from their stack trace with strict=False.
We could consider make another API for draft_export as debugging tool, or combine it with report=True when "model is small"?
cc @justinchuby