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02e30a09f7
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/74845 This PR adds support for quantization flow to detect parametrized modules and match them using their original module types. This mainly involved using the new type_before_parametrizations function rather than type to check for module mathcing Test Plan: python test/test_ao_sparsity.py TestComposability Imported from OSS Reviewed By: jerryzh168 Differential Revision: D35240274 fbshipit-source-id: 7294d89c9c2e069e51d8b9bafa45c15f92bed124 (cherry picked from commit ed5cdb7b636c42e040d1b4a67b6b94604d06e1ff)
28 lines
835 B
Python
28 lines
835 B
Python
# -*- coding: utf-8 -*-
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# Owner(s): ["module: unknown"]
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from torch.testing._internal.common_utils import run_tests
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# Kernels
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from ao.sparsity.test_kernels import TestQuantizedSparseKernels # noqa: F401
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from ao.sparsity.test_kernels import TestQuantizedSparseLayers # noqa: F401
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# Parametrizations
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from ao.sparsity.test_parametrization import TestFakeSparsity # noqa: F401
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# Sparsifier
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from ao.sparsity.test_sparsifier import TestBaseSparsifier # noqa: F401
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from ao.sparsity.test_sparsifier import TestWeightNormSparsifier # noqa: F401
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# Pruner
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from ao.sparsity.test_pruner import TestBasePruner # noqa: F401
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# Scheduler
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from ao.sparsity.test_scheduler import TestScheduler # noqa: F401
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# Composability
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from ao.sparsity.test_composability import TestComposability # noqa: F401
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if __name__ == '__main__':
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run_tests()
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