[quant][pt2e] Fix conv-bn weight + bias per channel QAT #125208
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Summary: This commit fixes the pattern matching for conv-bn during QAT fusion where both weight and bias are quantized per channel. Previously this failed because weights and biases used the same example kwargs for their scales and zero points, causing these qparams to be tied during pattern matching. Test Plan: python test/test_quantization.py TestQuantizePT2EQAT_ConvBn1d.test_qat_conv_bn_per_channel_weight_bias python test/test_quantization.py TestQuantizePT2EQAT_ConvBn2d.test_qat_conv_bn_per_channel_weight_bias Reviewers: jerryzh168, angelayi Subscribers: jerryzh168, angelayi, supriyar [ghstack-poisoned]
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/125208
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andrewor14
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Summary: This commit fixes the pattern matching for conv-bn during QAT fusion where both weight and bias are quantized per channel. Previously this failed because weights and biases used the same example kwargs for their scales and zero points, causing these qparams to be tied during pattern matching. Test Plan: python test/test_quantization.py TestQuantizePT2EQAT_ConvBn1d.test_qat_conv_bn_per_channel_weight_bias python test/test_quantization.py TestQuantizePT2EQAT_ConvBn2d.test_qat_conv_bn_per_channel_weight_bias Reviewers: jerryzh168, angelayi Subscribers: jerryzh168, angelayi, supriyar ghstack-source-id: 3240532629453a7ab80e3990340f95d98858dcc5 Pull Request resolved: #125208
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angelayi
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Apr 30, 2024
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@pytorchbot merge |
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@pytorchbot merge -f 'Landed internally' (Initiating merge automatically since Phabricator Diff has merged, using force because this PR might not pass merge_rules.json but landed internally) |
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andoorve
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May 1, 2024
Summary: This commit fixes the pattern matching for conv-bn during QAT fusion where both weight and bias are quantized per channel. Previously this failed because weights and biases used the same example kwargs for their scales and zero points, causing these qparams to be tied during pattern matching. Test Plan: python test/test_quantization.py TestQuantizePT2EQAT_ConvBn1d.test_qat_conv_bn_per_channel_weight_bias python test/test_quantization.py TestQuantizePT2EQAT_ConvBn2d.test_qat_conv_bn_per_channel_weight_bias Reviewers: jerryzh168, angelayi Subscribers: jerryzh168, angelayi, supriyar Differential Revision: [D56740694](https://our.internmc.facebook.com/intern/diff/D56740694) Pull Request resolved: pytorch#125208 Approved by: https://github.com/angelayi
petrex
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May 3, 2024
Summary: This commit fixes the pattern matching for conv-bn during QAT fusion where both weight and bias are quantized per channel. Previously this failed because weights and biases used the same example kwargs for their scales and zero points, causing these qparams to be tied during pattern matching. Test Plan: python test/test_quantization.py TestQuantizePT2EQAT_ConvBn1d.test_qat_conv_bn_per_channel_weight_bias python test/test_quantization.py TestQuantizePT2EQAT_ConvBn2d.test_qat_conv_bn_per_channel_weight_bias Reviewers: jerryzh168, angelayi Subscribers: jerryzh168, angelayi, supriyar Differential Revision: [D56740694](https://our.internmc.facebook.com/intern/diff/D56740694) Pull Request resolved: pytorch#125208 Approved by: https://github.com/angelayi
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Stack from ghstack (oldest at bottom):
Summary: This commit fixes the pattern matching for conv-bn
during QAT fusion where both weight and bias are quantized per
channel. Previously this failed because weights and biases used
the same example kwargs for their scales and zero points,
causing these qparams to be tied during pattern matching.
Test Plan:
python test/test_quantization.py TestQuantizePT2EQAT_ConvBn1d.test_qat_conv_bn_per_channel_weight_bias
python test/test_quantization.py TestQuantizePT2EQAT_ConvBn2d.test_qat_conv_bn_per_channel_weight_bias
Reviewers: jerryzh168, angelayi
Subscribers: jerryzh168, angelayi, supriyar
Differential Revision: D56740694