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/aosp_15_r20/external/pytorch/aten/src/ATen/native/quantized/cpu/
H A Dqconv_prepack.cpp56 "quantized::conv_prepack: Specify top/left output padding " in prepack()
211 "quantized::conv_prepack (qnnpack): Weights are expected to have ", in prepack()
215 "quantized::conv_prepack (qnnpack): ", in prepack()
220 "quantized::conv_prepack (qnnpack): Specify top/left input padding " in prepack()
224 "quantized::conv_prepack (qnnpack): Specify top/left output padding " in prepack()
228 "quantized::conv_prepack (qnnpack): ", in prepack()
351 "quantized::conv_prepack: Specify top/left output padding " in prepack()
359 "quantized::conv_prepack: ONEDNN only supports zero output_padding."); in prepack()
830 // conv_prepack is deprecated, please use conv2d_prepack for 2D conv. in TORCH_LIBRARY_IMPL()
831 …m.impl(TORCH_SELECTIVE_NAME("quantized::conv_prepack"), TORCH_FN(QConvPackWeightInt8<2>::run_conv)… in TORCH_LIBRARY_IMPL()
H A Dqconv.cpp583 * [de]conv_prepack prepares weights (values, scale, and zero_points) ahead of in apply_impl_xnnp()
/aosp_15_r20/external/pytorch/torch/_export/passes/
H A Dreplace_quantized_ops_with_standard_ops_pass.py311 # Using Conv2dPrepackParam from conv_prepack.
551 One exception in the transformation is conv_prepack and linear_prepack. Those calls pack
553 …During transformation, we directly skip transforming conv_prepack or linear_prepack. We check whet…
554 …quantized::conv2d or linear is from conv_prepack or linear_prepack. If it is, we then inline those…
575 "conv_prepack",
/aosp_15_r20/external/pytorch/aten/src/ATen/native/quantized/cudnn/
H A DConvPrepack.cpp56 "quantized::conv_prepack (cudnn): Specify front/top/left padding only. " in prepack()
60 "quantized::conv_prepack: Specify top/left output padding " in prepack()
64 "quantized::conv_prepack (cudnn): dilation should contain ", in prepack()
/aosp_15_r20/external/pytorch/torch/onnx/
H A Dsymbolic_caffe2.py81 def conv_prepack( function
/aosp_15_r20/external/pytorch/aten/src/ATen/native/quantized/
H A Dlibrary.cpp77 // conv_prepack is deprecated, please use conv2d_prepack for 2D conv. in TORCH_LIBRARY()
78 …m.def(TORCH_SELECTIVE_SCHEMA("quantized::conv_prepack(Tensor weight, Tensor? bias, int[] stride, i… in TORCH_LIBRARY()
/aosp_15_r20/external/pytorch/test/mobile/model_test/
H A Dmodel_ops.yaml426 quantized::conv_prepack: 3
H A Dcoverage.yaml1089 quantized::conv_prepack: 5
/aosp_15_r20/external/pytorch/docs/source/
H A Dconf.py1247 "conv_prepack",