Cleanup Quantized ShuffleNet #4854
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datumbox
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enhancement
module: models.quantization
💊 CI failures summary and remediationsAs of commit fb92493 (more details on the Dr. CI page):
1 failure not recognized by patterns:
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This comment was automatically generated by Dr. CI (expand for details).Please report bugs/suggestions to the (internal) Dr. CI Users group. |
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The single failed tests is unrelated and caused by network flakiness. Merging. |
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Summary: * Clean up unnecessary quant builders and add quant weights for 0.5 * Fixing mypy. Reviewed By: kazhang Differential Revision: D32216668 fbshipit-source-id: 16e4c817cde3e0138685a5989b266a2936ca3f42
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…67836) Summary: TorchVision accidentally included model builders for quantized models without weights; this was an old bug. These builders were largely unusable and caused issues to the users. Commonly they were filtered out to avoid causing issues. We've recently fixed that (pytorch/vision#4854) by either removing those unnecessary builders or by providing quantized weights. This PR removes the no-longer necessary filtering of the methods. **It should be merged after TorchVision is synced on FBCode.** Pull Request resolved: #67836 Reviewed By: jerryzh168 Differential Revision: D32230658 Pulled By: datumbox fbshipit-source-id: 797ca6d6a42474c14eeee1ad05c75e3ff05d1930
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…67836) Summary: TorchVision accidentally included model builders for quantized models without weights; this was an old bug. These builders were largely unusable and caused issues to the users. Commonly they were filtered out to avoid causing issues. We've recently fixed that (pytorch/vision#4854) by either removing those unnecessary builders or by providing quantized weights. This PR removes the no-longer necessary filtering of the methods. **It should be merged after TorchVision is synced on FBCode.** Pull Request resolved: #67836 Reviewed By: jerryzh168 Differential Revision: D32230658 Pulled By: datumbox fbshipit-source-id: 01cd425b1bda3b4591a25840593b3b5dde3a0f12
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Nov 16, 2021
* Clean up unnecessary quant builders and add quant weights for 0.5 * Fixing mypy.
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This PR:
shufflenet_v2_x1_5andshufflenet_v2_x2_0. These two were added by mistake and they are unusable because we have neither quantized weights nor normal weights.shufflenet_v2_x0_5variant, so that the equivalent model builder makes sense.Verified by:
The above builders caused problems to users and quite often on FBcode you can find code that tries to skip/ignore it. See this for example: pytorch/pytorch#67836
With the removal of the problematic methods, we can now clean up the skips non the next fbsync.