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Runner changes for TorchTune Llama3.2 vision text decoder #6610
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Summary: Specify model to export in the CLI. Test Plan: Exported the stories 110M model. ``` python -m examples.models.llama.export_llama -c stories110M/stories110M.pt -p stories110M/params.json -X -kv ``` PR chain: - [Add kwarg example inputs to eager model base](#5765) - [Llama2 model cleanup](#5859) - **YOU ARE HERE ~>** [Accept model type parameter in export_llama](#5910) - [Export TorchTune llama3_2_vision in ET](#5911) - [Runner changes for TorchTune Llama3.2 vision text decoder](#6610) - [Add et version of TorchTune MHA for swapping with custom op](#5912) Differential Revision: D65612837 Pulled By: dvorjackz
Summary: Specify model to export in the CLI. Test Plan: Exported the stories 110M model. ``` python -m examples.models.llama.export_llama -c stories110M/stories110M.pt -p stories110M/params.json -X -kv ``` PR chain: - [Add kwarg example inputs to eager model base](#5765) - [Llama2 model cleanup](#5859) - **YOU ARE HERE ~>** [Accept model type parameter in export_llama](#5910) - [Export TorchTune llama3_2_vision in ET](#5911) - [Runner changes for TorchTune Llama3.2 vision text decoder](#6610) - [Add et version of TorchTune MHA for swapping with custom op](#5912) Reviewed By: helunwencser Differential Revision: D65612837 Pulled By: dvorjackz
Summary: Specify model to export in the CLI. Test Plan: Exported the stories 110M model. ``` python -m examples.models.llama.export_llama -c stories110M/stories110M.pt -p stories110M/params.json -X -kv ``` PR chain: - [Add kwarg example inputs to eager model base](#5765) - [Llama2 model cleanup](#5859) - **YOU ARE HERE ~>** [Accept model type parameter in export_llama](#5910) - [Export TorchTune llama3_2_vision in ET](#5911) - [Runner changes for TorchTune Llama3.2 vision text decoder](#6610) - [Add et version of TorchTune MHA for swapping with custom op](#5912) Reviewed By: helunwencser Differential Revision: D65612837 Pulled By: dvorjackz
Summary: Specify model to export in the CLI. Test Plan: Exported the stories 110M model. ``` python -m examples.models.llama.export_llama -c stories110M/stories110M.pt -p stories110M/params.json -X -kv ``` PR chain: - [Add kwarg example inputs to eager model base](#5765) - [Llama2 model cleanup](#5859) - **YOU ARE HERE ~>** [Accept model type parameter in export_llama](#5910) - [Export TorchTune llama3_2_vision in ET](#5911) - [Runner changes for TorchTune Llama3.2 vision text decoder](#6610) - [Add et version of TorchTune MHA for swapping with custom op](#5912) Reviewed By: helunwencser Differential Revision: D65612837 Pulled By: dvorjackz
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@@ -89,7 +101,6 @@ def build_args_parser() -> argparse.ArgumentParser: | |||
parser.add_argument( | |||
"-kv", | |||
"--kv_cache", |
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I think we'd want the default to still be True?
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Oh yeah this was weird since "store_true" works by having a default of False, but the default is here set to True so it's just always True regardless of what you put
Summary
Changes to eager (Python) and native (ET) runners to run TorchTune's
llama3_2_vision
text decoder without KV cache (KV cache in progress). Should extend to the regular TorchTunellama3_2
model as well, will add support in following PRs.Native runner relies on #6670 to get in.
PR chain:
Test plan
Download the model from torchtune:
tune download meta-llama/Llama-3.2-11B-Vision-Instruct --output-dir /tmp/Llama-3.2-11B-Vision-Instruct
.Run eager:
Run executorch on portable lib (doesn't work until #6670 gets in, can test for now by adding pytorch/pytorch#137662 following to PyTorch installation):