Fix output spec + insert clone for constant_prop_pass. #11209
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/11209
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: Pull Request resolved: pytorch#11209 In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: Pull Request resolved: pytorch#11209 In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: Pull Request resolved: pytorch#11209 In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: Pull Request resolved: pytorch#11209 In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Reviewed By: angelayi Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Reviewed By: angelayi Differential Revision: D75473310
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Summary: Pull Request resolved: pytorch#11209 In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Reviewed By: angelayi Differential Revision: D75473310
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Summary: In case where a constant propagated node is returned by the exported program, `_validate()` fails with `SpecViolationError` with signature: ``` User output <SOME_CONSTANT_PROP_NODE> is not in the correct order or is not found in the exported program's user_output list. ``` This diff does two things: 1. Update output spec when propagated constants are output of the program. 2. Insert clone op on the constant prop tensor before sending them to output node. This avoid memory planning related errors. Reviewed By: angelayi Differential Revision: D75473310
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Summary:
In case where a constant propagated node is returned by the exported program,
_validate()fails withSpecViolationErrorwith signature:This diff does two things:
Differential Revision: D75473310