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https://github.com/saymrwulf/pytorch.git
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a9b0a921d5
Summary: As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH` All changes but the ones to `.clang-tidy` are generated using following script: ``` for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008 Reviewed By: driazati, r-barnes Differential Revision: D29838584 Pulled By: malfet fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
28 lines
975 B
C++
28 lines
975 B
C++
#include "caffe2/operators/quantized/int8_quantize_op.h"
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namespace caffe2 {
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REGISTER_CPU_OPERATOR(Int8Quantize, int8::Int8QuantizeOp);
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OPERATOR_SCHEMA(Int8Quantize)
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.Arg("Y_scale", "Output tensor quantization scale")
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.Arg("Y_zero_point", "Output tensor quantization offset")
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.NumInputs(1, 2)
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.NumOutputs(1)
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.TensorInferenceFunction([](const OperatorDef& def,
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const vector<TensorShape>& in) {
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vector<TensorShape> out;
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TensorShape X = in[0];
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out.emplace_back(std::move(X));
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out[0].set_data_type(TensorProto_DataType_UINT8);
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return out;
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})
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.Input(0, "X", "FP32 Tensor X.")
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.Input(
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1,
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"Qparam",
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"Optional Qparam blob that contains quant param computed on activation histogram data"
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"Will overwrite Y_scale and Y_zero_point argument if specified")
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.Output(0, "Y", "Int8 Tensor qX representing X with linear quantization.");
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} // namespace caffe2
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