Adds QAT ConvBN fuse pass to utils#17599
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Summary:
When performing QAT with a conv layer (bias=False) followed by batch norm, the fusion process introduces a bias after observers are attached, so the bias remains unquantized. These passes find such biases, compute the correct scale from the input and weight dequantize nodes, and insert proper quantize/dequantize nodes for the bias.
Two pass variants are provided:
- QuantizeFusedConvBnBiasPass (ExportPass) — operates on edge dialect graphs after to_edge()
- QuantizeFusedConvBnBiasAtenPass (PassBase) — operates on aten dialect graphs, supporting both plain GraphModules (get_attr nodes) and ExportedPrograms (placeholder nodes)
Differential Revision: D92733079
Summary: Make the NXP test_batch_norm_fusion tests compatible with the BUCK build system. The tflite import in executors.py is made optional since tensorflow/tflite_runtime are not available in the BUCK environment. The tests enabled do not rely on the functionality enabled by tflite. Differential Revision: D93880277
Summary: Earlier PR adds support for a pass that quantizes the bias resulting from QAT ConvBN fusion without an initial bias. This PR adds it to the NXP calibrate_and_quantize method. Differential Revision: D93904683
JakeStevens
requested review from
kimishpatel and
robert-kalmar
as code owners
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/17599
Note: Links to docs will display an error until the docs builds have been completed. ❌ 12 New Failures, 1 Unrelated FailureAs of commit 4eb68eb with merge base 89341d7 ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Summary:
Earlier PR adds support for a pass that quantizes the bias resulting from QAT ConvBN fusion without an initial bias.
This PR adds it to the NXP calibrate_and_quantize method.
Differential Revision: D93904683