Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into quantize_transpiler_update
Dang Qingqing
7 years ago
commit
f7bd1761a0
@ -1,11 +1,9 @@
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add_custom_target(paddle_apis ALL
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DEPENDS paddle_v2_apis paddle_fluid_apis)
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DEPENDS paddle_v2_apis)
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add_custom_target(paddle_docs ALL
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DEPENDS paddle_v2_docs paddle_v2_docs_cn
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paddle_fluid_docs paddle_fluid_docs_cn
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paddle_mobile_docs paddle_mobile_docs_cn)
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add_subdirectory(v2)
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add_subdirectory(fluid)
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add_subdirectory(mobile)
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@ -0,0 +1,106 @@
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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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#include <gflags/gflags.h>
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#include <glog/logging.h>
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#include <gtest/gtest.h>
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#include "paddle/fluid/inference/analysis/analyzer.h"
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#include "paddle/fluid/inference/api/paddle_inference_api.h"
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namespace paddle {
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using paddle::contrib::MixedRTConfig;
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DEFINE_string(dirname, "", "Directory of the inference model.");
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NativeConfig GetConfigNative() {
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NativeConfig config;
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config.model_dir = FLAGS_dirname;
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// LOG(INFO) << "dirname " << config.model_dir;
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config.fraction_of_gpu_memory = 0.45;
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config.use_gpu = true;
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config.device = 0;
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return config;
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}
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MixedRTConfig GetConfigTRT() {
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MixedRTConfig config;
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config.model_dir = FLAGS_dirname;
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config.use_gpu = true;
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config.fraction_of_gpu_memory = 0.2;
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config.device = 0;
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config.max_batch_size = 3;
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return config;
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}
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void CompareTensorRTWithFluid(int batch_size, std::string model_dirname) {
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NativeConfig config0 = GetConfigNative();
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config0.model_dir = model_dirname;
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MixedRTConfig config1 = GetConfigTRT();
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config1.model_dir = model_dirname;
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config1.max_batch_size = batch_size;
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auto predictor0 =
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CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config0);
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auto predictor1 =
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CreatePaddlePredictor<MixedRTConfig,
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PaddleEngineKind::kAutoMixedTensorRT>(config1);
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// Prepare inputs
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int height = 224;
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int width = 224;
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float *data = new float[batch_size * 3 * height * width];
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memset(data, 0, sizeof(float) * (batch_size * 3 * height * width));
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data[0] = 1.0f;
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// Prepare inputs
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PaddleTensor tensor;
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tensor.name = "input_0";
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tensor.shape = std::vector<int>({batch_size, 3, height, width});
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tensor.data = PaddleBuf(static_cast<void *>(data),
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sizeof(float) * (batch_size * 3 * height * width));
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tensor.dtype = PaddleDType::FLOAT32;
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std::vector<PaddleTensor> paddle_tensor_feeds(1, tensor);
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// Prepare outputs
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std::vector<PaddleTensor> outputs0;
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std::vector<PaddleTensor> outputs1;
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CHECK(predictor0->Run(paddle_tensor_feeds, &outputs0));
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CHECK(predictor1->Run(paddle_tensor_feeds, &outputs1, batch_size));
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// Get output.
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ASSERT_EQ(outputs0.size(), 1UL);
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ASSERT_EQ(outputs1.size(), 1UL);
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const size_t num_elements = outputs0.front().data.length() / sizeof(float);
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const size_t num_elements1 = outputs1.front().data.length() / sizeof(float);
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EXPECT_EQ(num_elements, num_elements1);
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auto *data0 = static_cast<float *>(outputs0.front().data.data());
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auto *data1 = static_cast<float *>(outputs1.front().data.data());
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ASSERT_GT(num_elements, 0UL);
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for (size_t i = 0; i < std::min(num_elements, num_elements1); i++) {
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EXPECT_NEAR(data0[i], data1[i], 1e-3);
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}
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}
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TEST(trt_models_test, main) {
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std::vector<std::string> infer_models = {"mobilenet", "resnet50",
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"resnext50"};
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for (auto &model_dir : infer_models) {
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CompareTensorRTWithFluid(1, FLAGS_dirname + "/" + model_dir);
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}
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}
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} // namespace paddle
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