[quant] quantized reflection_pad1d#37452
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💊 Build failures summary and remediationsAs of commit 456470c (more details on the Dr. CI page):
ci.pytorch.org: 1 failedThis comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions on the GitHub issue tracker. This comment has been revised 13 times. |
vkuzo
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Apr 28, 2020
| channels=st.integers(1, 64), | ||
| width=st.integers(16, 128), | ||
| qtype=st.sampled_from(hu._ALL_QINT_TYPES)) | ||
| def test_reflection_pad1d(self, batch_size, channels, width, qtype): |
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Is this also tested for QNNPACK? Do you need to explicitly loop over qengines?
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Does it need qnnpack testing? It was not implemented in qnnpack, neither is it implemented in fbgemm. The implementation is purely in memory manipulation, and should be qengine agnostic
raghuramank100
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Question on qnnpack coverage.
Differential Revision: [D21286659](https://our.internmc.facebook.com/intern/diff/D21286659)
Differential Revision: [D21286659](https://our.internmc.facebook.com/intern/diff/D21286659)
Differential Revision: [D21286659](https://our.internmc.facebook.com/intern/diff/D21286659)
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Apr 24, 2026
Summary: Pull Request resolved: pytorch#37452 Test Plan: Imported from OSS Differential Revision: D21286659 Pulled By: z-a-f fbshipit-source-id: f9f4de497a790b296149313562d09f8ead5facee
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Differential Revision: D21286659