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add custom annoatation for new model export #12126
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/12126
Note: Links to docs will display an error until the docs builds have been completed. ❌ 2 Cancelled Jobs, 1 Unrelated FailureAs of commit b79262b with merge base 5cc5421 ( CANCELLED JOBS - The following jobs were cancelled. Please retry:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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This pull request was exported from Phabricator. Differential Revision: D77569950 |
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@pytorchbot label "topic: not user facing" |
Summary: add custom annoatation for new model export Reviewed By: limintang Differential Revision: D77569950
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Summary: add custom annoatation for new model export Reviewed By: limintang Differential Revision: D77569950
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This pull request was exported from Phabricator. Differential Revision: D77569950 |
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This pull request was exported from Phabricator. Differential Revision: D77569950 |
Summary: Pull Request resolved: pytorch#12126 add custom annoatation for new model export Reviewed By: limintang Differential Revision: D77569950
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winskuo-quic
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LGTM. Thanks
| ) -> Dict[int, TensorConstant]: | ||
| tensor_args = {} | ||
| for i, arg in enumerate(node.args): | ||
| if hasattr(node.target, "_schema"): |
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Curious under what situation a node has no schema.
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I will remove this lines, this issue happen when I apply get_quant_embedding_transform for the model embedding layers and export model with -E "4,32"
Summary: add custom annoatation for new model export Reviewed By: limintang Differential Revision: D77569950
1952990 to
b79262b
Compare
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This pull request was exported from Phabricator. Differential Revision: D77569950 |
Differential Revision: D77569950 Pull Request resolved: pytorch#12126
Differential Revision: D77569950 Pull Request resolved: pytorch#12126
Summary: add custom annoatation for new model export
Differential Revision: D77569950