未验证 提交 8a6ac4db 编写于 作者: T tensor-tang 提交者: GitHub

Merge pull request #14973 from xiaolil1/dequantize

Add Dequantize OP
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "mkldnn.hpp"
#include "paddle/fluid/framework/data_layout_transform.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/dequantize_op.h"
#include "paddle/fluid/platform/mkldnn_helper.h"
namespace paddle {
namespace operators {
using mkldnn::memory;
using mkldnn::primitive;
using mkldnn::reorder;
using platform::to_void_cast;
using Tensor = framework::Tensor;
using framework::DataLayout;
using mkldnn::stream;
using platform::GetMKLDNNFormat;
template <typename T>
class DeQuantOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto* input = ctx.Input<Tensor>("Input");
auto scale_data = ctx.Attr<float>("Scale");
auto* output = ctx.Output<Tensor>("Output");
auto& dev_ctx =
ctx.template device_context<platform::MKLDNNDeviceContext>();
const auto& engine = dev_ctx.GetEngine();
const T* input_data = input->data<T>();
float* output_data = output->mutable_data<float>(ctx.GetPlace());
std::vector<float> reorder_scale = {1.0f / scale_data};
std::vector<primitive> pipeline;
std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
mkldnn::memory::data_type src_dt =
paddle::framework::ToMKLDNNDataType(input->type());
mkldnn::memory::format src_fmt = input->format();
mkldnn::primitive_attr attri;
int mask = 0;
attri.set_output_scales(mask, reorder_scale);
auto src_md = platform::MKLDNNMemDesc({src_tz}, src_dt, src_fmt);
auto src_pd = mkldnn::memory::primitive_desc(src_md, engine);
auto src_memory =
std::make_shared<mkldnn::memory>(src_pd, to_void_cast<T>(input_data));
std::shared_ptr<primitive::at> src_memory_p =
std::shared_ptr<primitive::at>(new primitive::at(*src_memory));
auto dst_md = platform::MKLDNNMemDesc({dst_tz}, memory::data_type::f32,
memory::format::nchw);
auto dst_pd = mkldnn::memory::primitive_desc(dst_md, engine);
auto dst_memory = mkldnn::memory(dst_pd, to_void_cast<float>(output_data));
auto reorder_pd = std::shared_ptr<reorder::primitive_desc>(
new reorder::primitive_desc(src_pd, dst_pd, attri));
auto reorder_p = std::shared_ptr<reorder>(
new reorder(*reorder_pd, *src_memory_p, dst_memory));
pipeline.push_back(*reorder_p);
stream(stream::kind::eager).submit(pipeline).wait();
output->set_format(GetMKLDNNFormat(dst_memory));
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP_KERNEL(dequantize, MKLDNN, ::paddle::platform::CPUPlace,
ops::DeQuantOpKernel<uint8_t>, ops::DeQuantOpKernel<int8_t>);
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/dequantize_op.h"
#ifdef PADDLE_WITH_MKLDNN
#include "paddle/fluid/platform/mkldnn_helper.h"
#endif
namespace paddle {
namespace operators {
framework::OpKernelType DeQuantOp::GetExpectedKernelType(
const framework::ExecutionContext& ctx) const {
framework::LibraryType library_ = framework::LibraryType::kMKLDNN;
framework::DataLayout layout_ = framework::DataLayout::kMKLDNN;
return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
ctx.GetPlace(), layout_, library_);
}
void DeQuantOpMaker::Make() {
AddInput("Input", "input data");
AddOutput("Output", "output data");
AddAttr<float>("Scale", "scale data").SetDefault({1.0f});
AddComment(R"DOC(This op will dequantize data from INT8 to FP32)DOC");
}
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(dequantize, ops::DeQuantOp, ops::DeQuantOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace paddle {
namespace operators {
using framework::OpKernelType;
using framework::Tensor;
class DeQuantOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
ctx->SetOutputDim("Output", ctx->GetInputDim("Input"));
ctx->ShareLoD("Input", /*->*/ "Output");
}
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override;
};
class DeQuantOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override;
};
class DeQuantGradOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {}
};
} // namespace operators
} // namespace paddle
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import unittest
import numpy as np
from op_test import OpTest
class TestDeQuantizeOp(OpTest):
def setUp(self):
self.op_type = 'dequantize'
self.scale = 2.0
self.input_size = [1, 1, 5, 5] #Naive nChw16c
self.data_type = 'int8'
self.set_scale()
self.set_data_type()
if self.data_type == 'int8':
input = (np.random.randint(0, 100, self.input_size) - 50
).astype(self.data_type)
output = (input * (1 / self.scale)).astype('float')
else:
input = (np.random.randint(0, 100,
self.input_size)).astype(self.data_type)
output = (input * (1 / self.scale)).astype('float')
self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
self.outputs = {'Output': output}
self.attrs = {'Scale': self.scale, }
def test_check_output(self):
self.check_output()
def set_scale(self):
pass
def set_data_type(OpTest):
pass
class TestDeQuantizeOp1(TestDeQuantizeOp):
def set_scale(self):
self.scale = 1.5
def set_data_type(self):
self.data_type = 'int8'
class TestDeQuantizeOp2(TestDeQuantizeOp):
def set_scale(self):
self.scale = 0.8
def set_data_type(self):
self.data_type = 'uint8'
if __name__ == '__main__':
unittest.main()
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