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Update on "Integrate torchgen exception boundary with ExecuTorch"
As of #7746, we build with exceptions by default, so we just need to use them. Differential Revision: [D67904052](https://our.internmc.facebook.com/intern/diff/D67904052/) [ghstack-poisoned]
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.ci/scripts/test_eval_llama_mmlu.sh

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--tasks mmlu \
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-f 5 \
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--max_seq_length 2048 \
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--max_context_length 2048 \
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--limit 5 > result.txt
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# Verify result.txt

.ci/scripts/test_eval_llama_wikitext.sh

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-kv \
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-d fp32 \
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--max_context_length 2048 \
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# Verify result.txt

.github/workflows/apple.yml

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id: set_version
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shell: bash
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run: |
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VERSION="0.4.0.$(TZ='PST8PDT' date +%Y%m%d)"
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VERSION="0.5.0.$(TZ='PST8PDT' date +%Y%m%d)"
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echo "version=$VERSION" >> "$GITHUB_OUTPUT"
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build-demo-ios:

.github/workflows/doc-build.yml

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needs: build
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if: github.repository == 'pytorch/executorch' && github.event_name == 'push' && (github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/tags/v'))
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permissions:
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id-token: write
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contents: read
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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.github/workflows/pull.yml

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# install pybind
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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# install Llava requirements
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bash install_executorch.sh --pybind xnnpack --use-pt-pinned-commit
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.github/workflows/trunk.yml

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.ci/scripts/setup-arm-baremetal-tools.sh
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.ci/scripts/setup-arm-baremetal-tools.sh
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.lintrunner.toml

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[[linter]]
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code = 'FLAKE8'

CONTRIBUTING.md

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disclosure of security bugs. In those cases, please go through the process
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outlined on that page and do not file a public issue.
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### Issue Labels
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#### Module/Partner Labels
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[Labels beginning with `module:`](https://github.com/pytorch/executorch/labels?q=%22module%3A+%22)
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indicate the area that the issue relates to. The ExecuTorch oncall will
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typically add this label.
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[Labels beginning with `partner:`](https://github.com/pytorch/executorch/labels?q=%22partner%3A+%22)
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indicate the ExecuTorch partner who owns the issue. The ExecuTorch oncall will
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typically add this label.
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#### Lifecycle Labels
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The ExecuTorch oncall will triage new issues. If the issue requires more
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information from the issue's author, oncall will add the `need-user-input` label
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and wait for the author to respond.
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Once the issue contains enough information, the oncall will:
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- Ensure that the title is descriptive
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- Add one of the labels:
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- `bug`: The issue describes an unexpected problem
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- `feature`: The issue describes a request for new functionality
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- `rfc`: The issue describes a proposed change to functionality
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- Add one `module:` label or one `partner:` label, as described above
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- Add the `triaged` label
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After this point, the oncall has finished the triage process, and the
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module owner or partner is responsible for resolving the issue. (See
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https://github.com/pytorch/executorch/issues/7679 for the mapping of labels to
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owners.)
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### Claiming Issues
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We'd love your help closing out [open
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issues](https://github.com/pytorch/executorch/issues?q=sort%3Aupdated-desc+is%3Aissue+is%3Aopen)

README-wheel.md

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ExecuTorch is to enable wider customization and deployment capabilities of the
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PyTorch programs.
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The `executorch` pip package is in alpha.
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* Supported python versions: 3.10, 3.11
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The `executorch` pip package is in beta.
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* Supported python versions: 3.10, 3.11, 3.12
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* Compatible systems: Linux x86_64, macOS aarch64
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The prebuilt `executorch.extension.pybindings.portable_lib` module included in
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this package provides a way to run ExecuTorch `.pte` files, with some
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restrictions:
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The prebuilt `executorch.runtime` module included in this package provides a way
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to run ExecuTorch `.pte` files, with some restrictions:
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* Only [core ATen
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operators](https://pytorch.org/executorch/stable/ir-ops-set-definition.html)
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are linked into the prebuilt module
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* Only the [XNNPACK backend
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delegate](https://pytorch.org/executorch/main/native-delegates-executorch-xnnpack-delegate.html)
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is linked into the prebuilt module
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* [macOS only] [Core ML](https://pytorch.org/executorch/main/build-run-coreml.html) and [MPS](https://pytorch.org/executorch/main/build-run-mps.html) backend delegates are linked into the prebuilt module.
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is linked into the prebuilt module.
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* \[macOS only] [Core ML](https://pytorch.org/executorch/main/build-run-coreml.html)
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and [MPS](https://pytorch.org/executorch/main/build-run-mps.html) backend
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delegates are also linked into the prebuilt module.
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Please visit the [ExecuTorch website](https://pytorch.org/executorch/) for
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tutorials and documentation. Here are some starting points:

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