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90 lines
3.3 KiB
90 lines
3.3 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/fake_dequantize_op.h"
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#include <string>
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namespace paddle {
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namespace operators {
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template <typename T>
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struct DequantizeFunctor<platform::CPUDeviceContext, T> {
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void operator()(const platform::CPUDeviceContext& dev_ctx,
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const framework::Tensor* in, const framework::Tensor* scale,
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T max_range, framework::Tensor* out) {
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auto in_e = framework::EigenVector<T>::Flatten(*in);
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const T* scale_factor = scale->data<T>();
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auto out_e = framework::EigenVector<T>::Flatten(*out);
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auto& dev = *dev_ctx.eigen_device();
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out_e.device(dev) = (scale_factor[0] / max_range) * in_e;
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}
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};
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template struct DequantizeFunctor<platform::CPUDeviceContext, float>;
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template struct DequantizeFunctor<platform::CPUDeviceContext, double>;
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class FakeDequantizeMaxAbsOp : public framework::OperatorWithKernel {
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public:
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FakeDequantizeMaxAbsOp(const std::string& type,
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const framework::VariableNameMap& inputs,
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const framework::VariableNameMap& outputs,
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const framework::AttributeMap& attrs)
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: OperatorWithKernel(type, inputs, outputs, attrs) {}
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void InferShape(framework::InferShapeContext* ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of FakeDequantizeMaxAbsOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of FakeDequantizeMaxAbsOp should not be null.");
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};
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class FakeDequantizeMaxAbsOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X",
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"(Tensor) The input with float-32/64 type is the "
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"low precision tensor.");
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AddInput("Scale", "(float) The scale in quantization stage.");
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AddOutput("Out",
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"(Tensor) The output is the dequantized high "
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"precision tensor.");
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AddAttr<float>("max_range", "(float) The max range in quantization stage.");
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AddComment(R"DOC(
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FakeDequantizeMaxAbsOp operator.
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This calculation is an opposite operation of FakeQuantizeMaxAbsOp:
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$$Out = \frac{scale*X}{ max_range }$$
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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using CPU = paddle::platform::CPUDeviceContext;
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REGISTER_OPERATOR(fake_dequantize_max_abs, ops::FakeDequantizeMaxAbsOp,
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ops::FakeDequantizeMaxAbsOpMaker,
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paddle::framework::EmptyGradOpMaker);
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REGISTER_OP_CPU_KERNEL(fake_dequantize_max_abs,
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ops::FakeDequantizeMaxAbsKernel<CPU, float>,
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ops::FakeDequantizeMaxAbsKernel<CPU, double>);
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