Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix_googlenet_bug_with_rule
test=developrevert-14324-fix_vlog
nhzlx
7 years ago
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9d98ca0424
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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");
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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/inference/tensorrt/convert/op_converter.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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/*
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* PadOp.
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*/
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class PadOpConverter : public OpConverter {
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public:
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void operator()(const framework::proto::OpDesc& op,
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const framework::Scope& scope, bool test_mode) override {
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VLOG(4) << "convert a fluid transpose op to tensorrt tranpose layer";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
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const std::vector<int> paddings =
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boost::get<std::vector<int>>(op_desc.GetAttr("paddings"));
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const float pad_value = boost::get<float>(op_desc.GetAttr("pad_value"));
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nvinfer1::Dims input_shape = input->getDimensions();
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int nbDims = input_shape.nbDims;
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int pad_size = static_cast<int>(paddings.size());
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PADDLE_ENFORCE_GE(nbDims, 2);
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PADDLE_ENFORCE_EQ((nbDims + 1) * 2, pad_size);
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PADDLE_ENFORCE(pad_value == 0.0, "The pad layer of TRT only support zero.");
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nvinfer1::DimsHW pre_pad(paddings[pad_size - 4], paddings[pad_size - 2]);
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nvinfer1::DimsHW post_pad(paddings[pad_size - 3], paddings[pad_size - 1]);
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auto* layer = TRT_ENGINE_ADD_LAYER(engine_, Padding,
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*const_cast<nvinfer1::ITensor*>(input),
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pre_pad, post_pad);
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PADDLE_ENFORCE(layer != nullptr);
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auto output_name = op_desc.Output("Out")[0];
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engine_->SetITensor(output_name, layer->getOutput(0));
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layer->setName(("scale (Output: " + output_name + ")").c_str());
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layer->getOutput(0)->setName(output_name.c_str());
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if (test_mode) { // the test framework can not determine which is the
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// output, so place the declaration inside.
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engine_->DeclareOutput(output_name);
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}
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}
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};
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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REGISTER_TRT_OP_CONVERTER(pad, PadOpConverter);
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@ -0,0 +1,52 @@
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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");
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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 <gtest/gtest.h>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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TEST(PadConverter, main) {
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framework::Scope scope;
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std::unordered_set<std::string> parameters;
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TRTConvertValidation validator(10, parameters, scope, 1000);
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validator.DeclInputVar("pad-X", nvinfer1::Dims3(3, 2, 2));
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validator.DeclOutputVar("pad-Out", nvinfer1::Dims3(3, 3, 5));
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// Prepare Op description
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framework::OpDesc desc;
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desc.SetType("pad");
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desc.SetInput("X", {"pad-X"});
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desc.SetOutput("Out", {"pad-Out"});
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std::vector<int> paddings = {0, 0, 0, 0, 0, 1, 1, 2};
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float pad_value = 0.0;
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desc.SetAttr("paddings", paddings);
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desc.SetAttr("pad_value", pad_value);
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LOG(INFO) << "set OP";
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validator.SetOp(*desc.Proto());
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LOG(INFO) << "execute";
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validator.Execute(2);
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}
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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USE_OP(pad);
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