Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into shufflechannel
shippingwang
6 years ago
commit
0a0b6f4a22
@ -0,0 +1,88 @@
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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.
|
||||
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. */
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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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@ -0,0 +1,45 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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|
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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,
|
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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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@ -0,0 +1,54 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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|
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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. */
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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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@ -0,0 +1,61 @@
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/*Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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||||
|
||||
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. */
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||||
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#ifdef PADDLE_WITH_NGRAPH
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#pragma once
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#include <string>
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#include <vector>
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#include "ngraph/ngraph.hpp"
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#include "paddle/fluid/platform/ngraph_helper.h"
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namespace paddle {
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namespace operators {
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namespace ngraphs {
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void BuildFillConstantNode(
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const std::shared_ptr<paddle::framework::OperatorBase>& op,
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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ngb_node_map) {
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auto op_attrs = paddle::framework::AttrReader(op->Attrs());
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auto vsp = op_attrs.Get<std::vector<int64_t>>("shape");
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ngraph::Shape shape;
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for (auto& sp : vsp) {
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shape.push_back(sp);
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}
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float value = op_attrs.Get<float>("value");
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ngraph::element::Type ng_dtype;
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auto data_type = static_cast<paddle::framework::proto::VarType::Type>(
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op_attrs.Get<int>("dtype"));
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if (data_type == paddle::framework::proto::VarType::FP32) {
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ng_dtype = ngraph::element::f32;
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} else if (data_type == paddle::framework::proto::VarType::FP64) {
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ng_dtype = ngraph::element::f64;
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} else if (data_type == paddle::framework::proto::VarType::INT64) {
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ng_dtype = ngraph::element::i64;
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} else if (data_type == paddle::framework::proto::VarType::INT32) {
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ng_dtype = ngraph::element::i32;
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} else if (data_type == paddle::framework::proto::VarType::BOOL) {
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ng_dtype = ngraph::element::boolean;
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} else {
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PADDLE_THROW("unsupported data type: %s", data_type);
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}
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auto out = ngraph::op::Constant::create(ng_dtype, shape, {value});
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paddle::platform::SetOutputNode(op, "Out", out, ngb_node_map);
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}
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} // namespace ngraphs
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} // namespace operators
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} // namespace paddle
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#endif
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@ -0,0 +1,51 @@
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/*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. */
|
||||
|
||||
#ifdef PADDLE_WITH_NGRAPH
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#pragma once
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|
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#include <string>
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#include "ngraph/ngraph.hpp"
|
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#include "paddle/fluid/platform/ngraph_helper.h"
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|
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namespace paddle {
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namespace operators {
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namespace ngraphs {
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|
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void BuildTopKNode(
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const std::shared_ptr<paddle::framework::OperatorBase>& op,
|
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std::shared_ptr<
|
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
|
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ngb_node_map) {
|
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auto op_attrs = paddle::framework::AttrReader(op->Attrs());
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int k = op_attrs.Get<int>("k");
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auto input = paddle::platform::GetInputNode(op, "X", ngb_node_map);
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auto top_k = std::make_shared<ngraph::op::TopK>(
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input, input->get_shape().size() - 1, ngraph::element::i64, k);
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std::shared_ptr<ngraph::Node> indices =
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std::make_shared<ngraph::op::GetOutputElement>(top_k, 0);
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std::shared_ptr<ngraph::Node> out =
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std::make_shared<ngraph::op::GetOutputElement>(top_k, 1);
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auto dummy_out = paddle::platform::GetOutputNode(op, "Out", ngb_node_map);
|
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if (dummy_out && dummy_out->get_element_type() != out->get_element_type()) {
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out = std::make_shared<ngraph::op::Convert>(out,
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dummy_out->get_element_type());
|
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}
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paddle::platform::SetOutputNode(op, "Indices", indices, ngb_node_map);
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paddle::platform::SetOutputNode(op, "Out", out, ngb_node_map);
|
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}
|
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} // namespace ngraphs
|
||||
} // namespace operators
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} // namespace paddle
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#endif
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@ -0,0 +1,89 @@
|
||||
/* 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/tensor.h"
|
||||
#include "paddle/fluid/operators/quantize_op.h"
|
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#include "paddle/fluid/platform/mkldnn_helper.h"
|
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#include "paddle/fluid/platform/mkldnn_reuse.h"
|
||||
|
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namespace paddle {
|
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namespace operators {
|
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|
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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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|
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template <typename T>
|
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class QuantOpKernel : public framework::OpKernel<T> {
|
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public:
|
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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();
|
||||
|
||||
std::vector<primitive> pipeline;
|
||||
std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
|
||||
std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
|
||||
|
||||
const T* input_data = input->data<T>();
|
||||
|
||||
mkldnn::primitive_attr attri;
|
||||
int mask = 0;
|
||||
attri.set_output_scales(mask, {scale_data});
|
||||
|
||||
auto src_md = platform::MKLDNNMemDesc({src_tz}, memory::data_type::f32,
|
||||
input->format());
|
||||
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));
|
||||
|
||||
bool is_negative = ctx.Attr<bool>("is_negative_input");
|
||||
std::shared_ptr<mkldnn::memory::primitive_desc> dst_pd;
|
||||
std::shared_ptr<mkldnn::memory> dst_memory;
|
||||
if (is_negative) {
|
||||
platform::ConvMKLDNNHandler::SetDstMemory<int8_t>(
|
||||
ctx, output, dst_tz, engine, dst_pd, dst_memory);
|
||||
} else {
|
||||
platform::ConvMKLDNNHandler::SetDstMemory<uint8_t>(
|
||||
ctx, output, dst_tz, engine, dst_pd, dst_memory);
|
||||
}
|
||||
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_layout(DataLayout::kMKLDNN);
|
||||
output->set_format(GetMKLDNNFormat(*dst_memory));
|
||||
}
|
||||
};
|
||||
} // namespace operators
|
||||
} // namespace paddle
|
||||
namespace ops = paddle::operators;
|
||||
|
||||
// TODO(Xiaoli) Support FP32->S8 quantization.
|
||||
|
||||
REGISTER_OP_KERNEL(quantize, MKLDNN, ::paddle::platform::CPUPlace,
|
||||
ops::QuantOpKernel<float>);
|
||||
@ -0,0 +1,47 @@
|
||||
/* 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/quantize_op.h"
|
||||
#ifdef PADDLE_WITH_MKLDNN
|
||||
#include "paddle/fluid/platform/mkldnn_helper.h"
|
||||
#endif
|
||||
|
||||
namespace paddle {
|
||||
namespace operators {
|
||||
|
||||
framework::OpKernelType QuantOp::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 QuantOpMaker::Make() {
|
||||
AddInput("Input", "input data");
|
||||
AddOutput("Output", "output data");
|
||||
AddAttr<bool>("is_negative_input",
|
||||
"(bool, default false) Only used in mkldnn INT8 kernel")
|
||||
.SetDefault(false);
|
||||
AddAttr<float>("Scale", "scale data").SetDefault({1.0f});
|
||||
AddComment(R"DOC(This op will quantize data from FP32 to INT8)DOC");
|
||||
}
|
||||
|
||||
} // namespace operators
|
||||
} // namespace paddle
|
||||
namespace ops = paddle::operators;
|
||||
|
||||
REGISTER_OPERATOR(quantize, ops::QuantOp, ops::QuantOpMaker,
|
||||
paddle::framework::DefaultGradOpDescMaker<true>);
|
||||
@ -0,0 +1,46 @@
|
||||
/* 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 QuantOp : 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 QuantOpMaker : public framework::OpProtoAndCheckerMaker {
|
||||
public:
|
||||
void Make() override;
|
||||
};
|
||||
} // namespace operators
|
||||
} // namespace paddle
|
||||
@ -0,0 +1,37 @@
|
||||
# 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
|
||||
from paddle.fluid.tests.unittests.test_fill_constant_op import TestFillConstantOp1, TestFillConstantOp2, TestFillConstantOpWithSelectedRows
|
||||
|
||||
|
||||
class TestNGRAPHFillConstantOp1(TestFillConstantOp1):
|
||||
def setUp(self):
|
||||
super(TestNGRAPHFillConstantOp1, self).setUp()
|
||||
|
||||
|
||||
class TestNGRAPHFillConstantOp2(TestFillConstantOp2):
|
||||
def setUp(self):
|
||||
super(TestNGRAPHFillConstantOp2, self).setUp()
|
||||
|
||||
|
||||
class TestNGRAPHFillConstantOpWithSelectedRows(
|
||||
TestFillConstantOpWithSelectedRows):
|
||||
def setUp(self):
|
||||
super(TestFillConstantOpWithSelectedRows, self).setUp()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@ -0,0 +1,41 @@
|
||||
# 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
|
||||
from paddle.fluid.tests.unittests.test_top_k_op import TestTopkOp, TestTopkOp3d, TestTopkOp2, TestTopkOp3, TestTopkOp4
|
||||
|
||||
|
||||
class TestNGRAPHTopkOp(TestTopkOp):
|
||||
def setUp(self):
|
||||
super(TestNGRAPHTopkOp, self).setUp()
|
||||
|
||||
|
||||
class TestNGRAPHTopkOp2(TestTopkOp2):
|
||||
def setUp(self):
|
||||
super(TestNGRAPHTopkOp2, self).setUp()
|
||||
|
||||
|
||||
class TestNGRAPHTopkOp3(TestTopkOp3):
|
||||
def setUp(self):
|
||||
super(TestNGRAPHTopkOp3, self).setUp()
|
||||
|
||||
|
||||
class TestNGRAPHTopkOp4(TestTopkOp4):
|
||||
def setUp(self):
|
||||
super(TestNGRAPHTopkOp4, self).setUp()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
@ -0,0 +1,73 @@
|
||||
# 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()
|
||||
@ -0,0 +1,76 @@
|
||||
# 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 TestQuantizeOp(OpTest):
|
||||
def setUp(self):
|
||||
self.op_type = 'quantize'
|
||||
self.scale = 2.0
|
||||
self.input_size = [1, 1, 5, 5] #Naive nChw16c
|
||||
self.is_negative = False
|
||||
self.set_scale()
|
||||
self.set_is_negative()
|
||||
|
||||
if self.is_negative:
|
||||
input = (100 * np.random.random_sample(self.input_size) - 50
|
||||
).astype('float32')
|
||||
output = np.round(input * self.scale).astype('int8')
|
||||
else:
|
||||
input = (100 *
|
||||
np.random.random_sample(self.input_size)).astype('float32')
|
||||
output = np.round(input * self.scale).astype('uint8')
|
||||
|
||||
self.inputs = {'Input': OpTest.np_dtype_to_fluid_dtype(input)}
|
||||
|
||||
self.outputs = {'Output': output}
|
||||
|
||||
self.attrs = {
|
||||
'Scale': self.scale,
|
||||
'is_negative_input': self.is_negative
|
||||
}
|
||||
|
||||
def test_check_output(self):
|
||||
self.check_output()
|
||||
|
||||
def set_scale(self):
|
||||
pass
|
||||
|
||||
def set_is_negative(self):
|
||||
pass
|
||||
|
||||
|
||||
class TestQuantizeOp1(TestQuantizeOp):
|
||||
def set_scale(self):
|
||||
self.scale = 1.5
|
||||
|
||||
def set_is_negative(self):
|
||||
self.is_nagative = True
|
||||
|
||||
|
||||
class TestQuantizeOp2(TestQuantizeOp):
|
||||
def set_scale(self):
|
||||
self.scale = 0.1
|
||||
|
||||
def set_is_negative(self):
|
||||
self.is_nagative = False
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
Loading…
Reference in new issue