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ea558b2135
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/49717 Quantization of `ConvTranpose{n}d` is supported in Eager mode. This PR adds the support for FX graph mode. Note: this currenlty only works in `qnnpack` because per-channel weights are not supported by quantized conv transpose. In a future PR we should throw an error when someone tries to quantize a ConvTranspose model with per-channel weight observers until this is fixed. Test Plan: ``` python test/test_quantization.py TestQuantizeFxOps.test_conv_transpose_1d python test/test_quantization.py TestQuantizeFxOps.test_conv_transpose_2d ``` Imported from OSS Reviewed By: jerryzh168 Differential Revision: D25674636 fbshipit-source-id: b6948156123ed55db77e6337bea10db956215ae6 |
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| .. | ||
| serialized | ||
| __init__.py | ||
| test_backward_compatibility.py | ||
| test_bias_correction.py | ||
| test_equalize.py | ||
| test_fusion_passes.py | ||
| test_numeric_suite.py | ||
| test_numeric_suite_fx.py | ||
| test_qat_module.py | ||
| test_quantize.py | ||
| test_quantize_fx.py | ||
| test_quantize_jit.py | ||
| test_quantized_functional.py | ||
| test_quantized_module.py | ||
| test_quantized_op.py | ||
| test_quantized_tensor.py | ||
| test_workflow_module.py | ||