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116 lines
4.5 KiB
116 lines
4.5 KiB
/* Copyright (c) 2019 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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#include <gtest/gtest.h>
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#include "paddle/fluid/framework/block_desc.h"
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#include "paddle/fluid/framework/op_desc.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/inference/utils/singleton.h"
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#include "paddle/fluid/operators/lite/lite_engine_op.h"
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#include "paddle/fluid/operators/lite/ut_helper.h"
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USE_NO_KERNEL_OP(lite_engine)
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using paddle::inference::lite::AddTensorToBlockDesc;
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using paddle::inference::lite::CreateTensor;
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using paddle::inference::lite::serialize_params;
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namespace paddle {
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namespace operators {
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TEST(LiteEngineOp, engine_op) {
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framework::ProgramDesc program;
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auto* block_ = program.Proto()->mutable_blocks(0);
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framework::BlockDesc block_desc(&program, block_);
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auto* feed0 = block_desc.AppendOp();
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feed0->SetType("feed");
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feed0->SetInput("X", {"feed"});
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feed0->SetOutput("Out", {"x"});
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feed0->SetAttr("col", 0);
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auto* feed1 = block_desc.AppendOp();
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feed1->SetType("feed");
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feed1->SetInput("X", {"feed"});
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feed1->SetOutput("Out", {"y"});
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feed1->SetAttr("col", 1);
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LOG(INFO) << "create elementwise_add op";
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auto* elt_add = block_desc.AppendOp();
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elt_add->SetType("elementwise_add");
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elt_add->SetInput("X", std::vector<std::string>({"x"}));
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elt_add->SetInput("Y", std::vector<std::string>({"y"}));
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elt_add->SetOutput("Out", std::vector<std::string>({"z"}));
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elt_add->SetAttr("axis", -1);
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LOG(INFO) << "create fetch op";
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auto* fetch = block_desc.AppendOp();
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fetch->SetType("fetch");
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fetch->SetInput("X", std::vector<std::string>({"z"}));
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fetch->SetOutput("Out", std::vector<std::string>({"out"}));
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fetch->SetAttr("col", 0);
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// Set inputs' variable shape in BlockDesc
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AddTensorToBlockDesc(block_, "x", std::vector<int64_t>({2, 4}), true);
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AddTensorToBlockDesc(block_, "y", std::vector<int64_t>({2, 4}), true);
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AddTensorToBlockDesc(block_, "z", std::vector<int64_t>({2, 4}), false);
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AddTensorToBlockDesc(block_, "out", std::vector<int64_t>({2, 4}), false);
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*block_->add_ops() = *feed1->Proto();
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*block_->add_ops() = *feed0->Proto();
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*block_->add_ops() = *elt_add->Proto();
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*block_->add_ops() = *fetch->Proto();
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framework::Scope scope;
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#ifdef PADDLE_WITH_CUDA
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platform::CUDAPlace place;
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platform::CUDADeviceContext ctx(place);
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#else
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platform::CPUPlace place;
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platform::CPUDeviceContext ctx(place);
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#endif
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// Prepare variables.
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CreateTensor(&scope, "x", std::vector<int64_t>({2, 4}), false);
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CreateTensor(&scope, "y", std::vector<int64_t>({2, 4}), false);
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CreateTensor(&scope, "out", std::vector<int64_t>({2, 4}), false);
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ASSERT_EQ(block_->ops_size(), 4);
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std::vector<std::string> repetitive_params{"x", "y"};
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inference::lite::EngineConfig config;
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config.valid_places = {
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#ifdef PADDLE_WITH_CUDA
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paddle::lite::Place({TARGET(kCUDA), PRECISION(kFloat)}),
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#endif
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paddle::lite::Place({TARGET(kHost), PRECISION(kAny)}),
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paddle::lite::Place({TARGET(kX86), PRECISION(kFloat)}),
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};
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serialize_params(&(config.param), &scope, repetitive_params);
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config.model = program.Proto()->SerializeAsString();
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LOG(INFO) << "create lite_engine desc";
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framework::OpDesc engine_op_desc(nullptr);
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engine_op_desc.SetType("lite_engine");
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engine_op_desc.SetInput("Xs", std::vector<std::string>({"x", "y"}));
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engine_op_desc.SetOutput("Ys", std::vector<std::string>({"out"}));
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std::string engine_key = "engine_0";
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engine_op_desc.SetAttr("engine_key", engine_key);
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engine_op_desc.SetAttr("enable_int8", false);
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engine_op_desc.SetAttr("use_gpu", true);
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engine_op_desc.SetBlockAttr("sub_block", &block_desc);
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inference::Singleton<inference::lite::EngineManager>::Global().Create(
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engine_key, config);
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LOG(INFO) << "create engine op";
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auto engine_op = framework::OpRegistry::CreateOp(engine_op_desc);
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LOG(INFO) << "engine_op " << engine_op.get();
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// Execute them.
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LOG(INFO) << "engine_op run";
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engine_op->Run(scope, place);
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LOG(INFO) << "done";
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}
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} // namespace operators
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} // namespace paddle
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