test/add text-classification test (#13081)
Yan Chunwei
7 years ago
committed by
GitHub
parent
4907d093aa
commit
9df2d8b5ba
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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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// TODO(Superjomn) add a definition flag like PADDLE_WITH_TENSORRT and hide this
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// flag if not available.
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DECLARE_bool(IA_enable_tensorrt_subgraph_engine);
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DECLARE_string(IA_graphviz_log_root);
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DECLARE_string(IA_output_storage_path);
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DECLARE_bool(IA_enable_ir);
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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> // use glog instead of PADDLE_ENFORCE to avoid importing other paddle header files.
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#include <gtest/gtest.h>
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#include "paddle/fluid/framework/ir/pass.h"
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#include "paddle/fluid/inference/analysis/analyzer.h"
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#include "paddle/fluid/inference/analysis/ut_helper.h"
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#include "paddle/fluid/inference/api/paddle_inference_api.h"
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#include "paddle/fluid/inference/api/timer.h"
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DEFINE_string(infer_model, "", "Directory of the inference model.");
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DEFINE_string(infer_data, "", "Path of the dataset.");
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DEFINE_int32(batch_size, 1, "batch size.");
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DEFINE_int32(repeat, 1, "How many times to repeat run.");
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namespace paddle {
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template <typename T>
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std::string to_string(const std::vector<T> &vec) {
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std::stringstream ss;
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for (const auto &c : vec) {
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ss << c << " ";
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}
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return ss.str();
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}
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void PrintTime(const double latency, const int bs, const int repeat) {
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LOG(INFO) << "===========profile result===========";
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LOG(INFO) << "batch_size: " << bs << ", repeat: " << repeat
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<< ", avg latency: " << latency / repeat << "ms";
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LOG(INFO) << "=====================================";
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}
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void Main(int batch_size) {
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// Three sequence inputs.
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std::vector<PaddleTensor> input_slots(1);
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// one batch starts
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// data --
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int64_t data0[] = {0, 1, 2};
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for (auto &input : input_slots) {
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input.data.Reset(data0, sizeof(data0));
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input.shape = std::vector<int>({3, 1});
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// dtype --
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input.dtype = PaddleDType::INT64;
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// LoD --
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input.lod = std::vector<std::vector<size_t>>({{0, 3}});
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}
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// shape --
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// Create Predictor --
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AnalysisConfig config;
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config.model_dir = FLAGS_infer_model;
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config.use_gpu = false;
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config.enable_ir_optim = true;
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config.ir_passes.push_back("fc_lstm_fuse_pass");
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auto predictor =
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CreatePaddlePredictor<AnalysisConfig, PaddleEngineKind::kAnalysis>(
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config);
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inference::Timer timer;
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double sum = 0;
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std::vector<PaddleTensor> output_slots;
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for (int i = 0; i < FLAGS_repeat; i++) {
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timer.tic();
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CHECK(predictor->Run(input_slots, &output_slots));
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sum += timer.toc();
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}
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PrintTime(sum, batch_size, FLAGS_repeat);
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// Get output
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LOG(INFO) << "get outputs " << output_slots.size();
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for (auto &output : output_slots) {
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LOG(INFO) << "output.shape: " << to_string(output.shape);
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// no lod ?
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CHECK_EQ(output.lod.size(), 0UL);
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LOG(INFO) << "output.dtype: " << output.dtype;
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std::stringstream ss;
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for (int i = 0; i < 5; i++) {
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ss << static_cast<float *>(output.data.data())[i] << " ";
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}
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LOG(INFO) << "output.data summary: " << ss.str();
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// one batch ends
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}
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}
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TEST(text_classification, basic) { Main(FLAGS_batch_size); }
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} // namespace paddle
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USE_PASS(fc_fuse_pass);
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USE_PASS(seq_concat_fc_fuse_pass);
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USE_PASS(fc_lstm_fuse_pass);
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USE_PASS(graph_viz_pass);
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USE_PASS(infer_clean_graph_pass);
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USE_PASS(attention_lstm_fuse_pass);
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