Merge pull request #14973 from xiaolil1/dequantize
Add Dequantize OPrevert-15207-remove_op_handle_lock_and_fix_var
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8a6ac4dba7
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/* 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 "mkldnn.hpp"
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#include "paddle/fluid/framework/data_layout_transform.h"
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/operators/dequantize_op.h"
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#include "paddle/fluid/platform/mkldnn_helper.h"
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namespace paddle {
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namespace operators {
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using mkldnn::memory;
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using mkldnn::primitive;
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using mkldnn::reorder;
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using platform::to_void_cast;
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using Tensor = framework::Tensor;
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using framework::DataLayout;
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using mkldnn::stream;
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using platform::GetMKLDNNFormat;
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template <typename T>
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class DeQuantOpKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* input = ctx.Input<Tensor>("Input");
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auto scale_data = ctx.Attr<float>("Scale");
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auto* output = ctx.Output<Tensor>("Output");
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auto& dev_ctx =
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ctx.template device_context<platform::MKLDNNDeviceContext>();
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const auto& engine = dev_ctx.GetEngine();
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const T* input_data = input->data<T>();
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float* output_data = output->mutable_data<float>(ctx.GetPlace());
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std::vector<float> reorder_scale = {1.0f / scale_data};
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std::vector<primitive> pipeline;
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std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
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std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
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mkldnn::memory::data_type src_dt =
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paddle::framework::ToMKLDNNDataType(input->type());
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mkldnn::memory::format src_fmt = input->format();
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mkldnn::primitive_attr attri;
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int mask = 0;
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attri.set_output_scales(mask, reorder_scale);
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auto src_md = platform::MKLDNNMemDesc({src_tz}, src_dt, src_fmt);
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auto src_pd = mkldnn::memory::primitive_desc(src_md, engine);
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auto src_memory =
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std::make_shared<mkldnn::memory>(src_pd, to_void_cast<T>(input_data));
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std::shared_ptr<primitive::at> src_memory_p =
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std::shared_ptr<primitive::at>(new primitive::at(*src_memory));
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auto dst_md = platform::MKLDNNMemDesc({dst_tz}, memory::data_type::f32,
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memory::format::nchw);
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auto dst_pd = mkldnn::memory::primitive_desc(dst_md, engine);
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auto dst_memory = mkldnn::memory(dst_pd, to_void_cast<float>(output_data));
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auto reorder_pd = std::shared_ptr<reorder::primitive_desc>(
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new reorder::primitive_desc(src_pd, dst_pd, attri));
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auto reorder_p = std::shared_ptr<reorder>(
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new reorder(*reorder_pd, *src_memory_p, dst_memory));
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pipeline.push_back(*reorder_p);
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stream(stream::kind::eager).submit(pipeline).wait();
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output->set_format(GetMKLDNNFormat(dst_memory));
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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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REGISTER_OP_KERNEL(dequantize, MKLDNN, ::paddle::platform::CPUPlace,
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ops::DeQuantOpKernel<uint8_t>, ops::DeQuantOpKernel<int8_t>);
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/* 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/dequantize_op.h"
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#ifdef PADDLE_WITH_MKLDNN
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#include "paddle/fluid/platform/mkldnn_helper.h"
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#endif
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namespace paddle {
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namespace operators {
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framework::OpKernelType DeQuantOp::GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const {
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framework::LibraryType library_ = framework::LibraryType::kMKLDNN;
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framework::DataLayout layout_ = framework::DataLayout::kMKLDNN;
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return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
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ctx.GetPlace(), layout_, library_);
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}
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void DeQuantOpMaker::Make() {
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AddInput("Input", "input data");
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AddOutput("Output", "output data");
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AddAttr<float>("Scale", "scale data").SetDefault({1.0f});
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AddComment(R"DOC(This op will dequantize data from INT8 to FP32)DOC");
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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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REGISTER_OPERATOR(dequantize, ops::DeQuantOp, ops::DeQuantOpMaker,
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paddle::framework::DefaultGradOpDescMaker<true>);
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/* 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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#pragma once
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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using framework::OpKernelType;
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using framework::Tensor;
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class DeQuantOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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ctx->SetOutputDim("Output", ctx->GetInputDim("Input"));
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ctx->ShareLoD("Input", /*->*/ "Output");
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override;
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};
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class DeQuantOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override;
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};
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class DeQuantGradOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {}
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};
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} // namespace operators
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} // namespace paddle
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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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from __future__ import print_function
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import unittest
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import numpy as np
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from op_test import OpTest
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class TestDeQuantizeOp(OpTest):
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def setUp(self):
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self.op_type = 'dequantize'
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self.scale = 2.0
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self.input_size = [1, 1, 5, 5] #Naive nChw16c
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self.data_type = 'int8'
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self.set_scale()
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self.set_data_type()
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if self.data_type == 'int8':
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input = (np.random.randint(0, 100, self.input_size) - 50
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).astype(self.data_type)
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output = (input * (1 / self.scale)).astype('float')
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else:
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input = (np.random.randint(0, 100,
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self.input_size)).astype(self.data_type)
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output = (input * (1 / self.scale)).astype('float')
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self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
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self.outputs = {'Output': output}
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self.attrs = {'Scale': self.scale, }
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def test_check_output(self):
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self.check_output()
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def set_scale(self):
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pass
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def set_data_type(OpTest):
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pass
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class TestDeQuantizeOp1(TestDeQuantizeOp):
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def set_scale(self):
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self.scale = 1.5
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def set_data_type(self):
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self.data_type = 'int8'
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class TestDeQuantizeOp2(TestDeQuantizeOp):
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def set_scale(self):
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self.scale = 0.8
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def set_data_type(self):
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self.data_type = 'uint8'
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if __name__ == '__main__':
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unittest.main()
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