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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
40 lines
1.4 KiB
C++
40 lines
1.4 KiB
C++
// Copyright 2004-present Facebook. All Rights Reserved.
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#include "caffe2/quantization/server/int8_gen_quant_params.h"
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#include <functional>
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namespace caffe2 {
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using namespace std;
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using namespace dnnlowp;
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// Expilictly register TypeMeta
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CAFFE_KNOWN_TYPE(unique_ptr<Int8QuantSchemeBlob>);
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CAFFE_KNOWN_TYPE(unique_ptr<Int8QuantParamsBlob>);
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REGISTER_CPU_OPERATOR(
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Int8GenQuantParams,
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Int8GenQuantParamsOp<CPUContext, DefaultEngine>);
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OPERATOR_SCHEMA(Int8GenQuantParams)
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.NumInputs(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(1);
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out[0].set_data_type(TensorProto_DataType_FLOAT);
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out[0].add_dims(1);
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return out;
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})
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.Input(
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0,
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"X",
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"The input data, or last N samples of the output activations.")
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.Input(
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1,
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"quant_scheme",
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"Int8QuantSchemeBlob that specifies the quantization kind and preserve_sparsity options when generating the quant params.")
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.Output(
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0,
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"quant_param",
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"Int8QuantParamsBlob that contains the scale and zero_point info in TensorQuantizationParams type.")
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.SetDoc(
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R"DOC(Operator wrapper for generating int8 tensor quantization parameters given the input data and quant scheme)DOC");
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} // namespace caffe2
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