Skip quantization when channels_out / channels_in are not multiple of 16 #3309
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/3309
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 New FailureAs of commit 3e52ad2 with merge base 6259e98 ( NEW FAILURE - The following job has failed:
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Summary: The underlying fbgemm conv3d kernel for float8 only supports channels_out/channels_in are both multiples of 16 so we skip the shapes that doesn't satisfy the requirements for now, we can expand the support to do padding if needed in the future Test Plan: python test/quantization/quantize_/workflows/float8/test_float8_tensor.py -k test_fp8_conv_skip_quant
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andrewor14
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| compile: bool, | ||
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| inference_mode: bool, | ||
| kernel_preference: KernelPreference, |
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sorry just noticed that this is not removed, the test is skipped in CI so should not be ran for now, will remove in next PR
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… 16 (#3309) Summary: The underlying fbgemm conv3d kernel for float8 only supports channels_out/channels_in are both multiples of 16 so we skip the shapes that doesn't satisfy the requirements for now, we can expand the support to do padding if needed in the future Test Plan: python test/quantization/quantize_/workflows/float8/test_float8_tensor.py -k test_fp8_conv_skip_quant
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… 16 (pytorch#3309) Summary: The underlying fbgemm conv3d kernel for float8 only supports channels_out/channels_in are both multiples of 16 so we skip the shapes that doesn't satisfy the requirements for now, we can expand the support to do padding if needed in the future Test Plan: python test/quantization/quantize_/workflows/float8/test_float8_tensor.py -k test_fp8_conv_skip_quant
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Summary:
The underlying fbgemm conv3d kernel for float8 only supports channels_out/channels_in are both multiples of 16 so we skip the shapes that doesn't satisfy the requirements for now, we can expand the support to do padding if needed in the future
Test Plan:
(in B200 machine) python test/quantization/quantize_/workflows/float8/test_float8_tensor.py -k test_fp8_conv_skip_quant