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211bac53ef
Summary: Freezing exists as a pass which partially evaluates your model and applies generic optimizations which should speed it up. Optimize for inference is a counterpart to these optimizations which runs build & server specific optimizations. The interaction with existing `optimize_frozen_module` is not great, I guess we could just deprecate the API entirely? it was never officially released but just existed to document the `optimize_numerics` keyword. Eventually, I would like to add a way of adding example inputs but I didnt add that here because they are not being used at all yet. I also have not yet included a way to blacklist individual optimizations, and would like to wait until we move this to Beta and have a little more clarity on how everything will fit together. I also think blacklisting will be an uncommon use case for the current optimizations. Pull Request resolved: https://github.com/pytorch/pytorch/pull/58193 Reviewed By: bertmaher, navahgar Differential Revision: D28443714 Pulled By: eellison fbshipit-source-id: b032355bb2585720a6d2f00c89d0d9a7ef60e649 |
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| tensorexpr | ||
| __init__.py | ||