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Merge branch 'develop' into nlp_multi_thread

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fix-develop-build.sh
luotao1 7 years ago
parent 20b40cb06a 7622234205
commit 6b9ccd97a2
6 changed files with 227 additions and 32 deletions
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56
paddle/fluid/inference/tests/api/CMakeLists.txt
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@ -1,55 +1,57 @@
function (inference_download_and_uncompress install_dir url)
get_filename_component(filename ${url} NAME)
message(STATUS "Download inference test stuff ${filename} from ${url}")
set(INFERENCE_URL "http://paddle-inference-dist.bj.bcebos.com")
set(INFERENCE_DEMO_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo")
set(INFERENCE_EXTRA_DEPS paddle_inference_api paddle_fluid_api ir_pass_manager analysis_predictor)
function (inference_download_and_uncompress install_dir filename)
message(STATUS "Download inference test stuff from ${INFERENCE_URL}/${filename}")
execute_process(COMMAND bash -c "mkdir -p ${install_dir}")
execute_process(COMMAND bash -c "cd ${install_dir} && wget -q ${url}")
execute_process(COMMAND bash -c "cd ${install_dir} && wget -q ${INFERENCE_URL}/${filename}")
execute_process(COMMAND bash -c "cd ${install_dir} && tar xzf ${filename}")
message(STATUS "finish downloading ${filename}")
endfunction(inference_download_and_uncompress)
function(download_model_and_data install_dir model_url data_url)
function(download_model_and_data install_dir model_name data_name)
if (NOT EXISTS ${install_dir} AND WITH_INFERENCE)
inference_download_and_uncompress(${install_dir} ${model_url})
inference_download_and_uncompress(${install_dir} ${data_url})
inference_download_and_uncompress(${install_dir} ${model_name})
inference_download_and_uncompress(${install_dir} ${data_name})
endif()
endfunction()
# RNN1
set(RNN1_MODEL_URL "http://paddle-inference-dist.bj.bcebos.com/rnn1%2Fmodel.tar.gz")
set(RNN1_DATA_URL "http://paddle-inference-dist.bj.bcebos.com/rnn1%2Fdata.txt.tar.gz")
set(RNN1_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo/rnn1")
download_model_and_data(${RNN1_INSTALL_DIR} ${RNN1_MODEL_URL} ${RNN1_DATA_URL})
set(RNN1_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/rnn1")
download_model_and_data(${RNN1_INSTALL_DIR} "rnn1%2Fmodel.tar.gz" "rnn1%2Fdata.txt.tar.gz")
inference_analysis_test(test_analyzer_rnn1 SRCS analyzer_rnn1_tester.cc
EXTRA_DEPS paddle_inference_api paddle_fluid_api ir_pass_manager analysis_predictor
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${RNN1_INSTALL_DIR}/model
--infer_data=${RNN1_INSTALL_DIR}/data.txt)
# RNN2
set(RNN2_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/rnn2")
download_model_and_data(${RNN2_INSTALL_DIR} "rnn2_model.tar.gz" "rnn2_data.txt.tar.gz")
inference_analysis_test(test_analyzer_rnn2 SRCS analyzer_rnn2_tester.cc
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${RNN2_INSTALL_DIR}/model
--infer_data=${RNN2_INSTALL_DIR}/data.txt)
# chinese_ner
set(CHINESE_NER_MODEL_URL "http://paddle-inference-dist.bj.bcebos.com/chinese_ner_model.tar.gz")
set(CHINESE_NER_DATA_URL "http://paddle-inference-dist.bj.bcebos.com/chinese_ner-data.txt.tar.gz")
set(CHINESE_NER_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo/chinese_ner")
download_model_and_data(${CHINESE_NER_INSTALL_DIR} ${CHINESE_NER_MODEL_URL} ${CHINESE_NER_DATA_URL})
set(CHINESE_NER_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/chinese_ner")
download_model_and_data(${CHINESE_NER_INSTALL_DIR} "chinese_ner_model.tar.gz" "chinese_ner-data.txt.tar.gz")
inference_analysis_test(test_analyzer_ner SRCS analyzer_ner_tester.cc
EXTRA_DEPS paddle_inference_api paddle_fluid_api analysis_predictor
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${CHINESE_NER_INSTALL_DIR}/model
--infer_data=${CHINESE_NER_INSTALL_DIR}/data.txt)
# lac
set(LAC_MODEL_URL "http://paddle-inference-dist.bj.bcebos.com/lac_model.tar.gz")
set(LAC_DATA_URL "http://paddle-inference-dist.bj.bcebos.com/lac_data.txt.tar.gz")
set(LAC_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo/lac")
download_model_and_data(${LAC_INSTALL_DIR} ${LAC_MODEL_URL} ${LAC_DATA_URL})
set(LAC_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/lac")
download_model_and_data(${LAC_INSTALL_DIR} "lac_model.tar.gz" "lac_data.txt.tar.gz")
inference_analysis_test(test_analyzer_lac SRCS analyzer_lac_tester.cc
EXTRA_DEPS paddle_inference_api paddle_fluid_api ir_pass_manager analysis_predictor
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${LAC_INSTALL_DIR}/model
--infer_data=${LAC_INSTALL_DIR}/data.txt)
# text_classification
set(TEXT_CLASSIFICATION_MODEL_URL "http://paddle-inference-dist.bj.bcebos.com/text-classification-Senta.tar.gz")
set(TEXT_CLASSIFICATION_DATA_URL "http://paddle-inference-dist.bj.bcebos.com/text_classification_data.txt.tar.gz")
set(TEXT_CLASSIFICATION_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo/text_classification")
download_model_and_data(${TEXT_CLASSIFICATION_INSTALL_DIR} ${TEXT_CLASSIFICATION_MODEL_URL} ${TEXT_CLASSIFICATION_DATA_URL})
set(TEXT_CLASSIFICATION_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/text_classification")
download_model_and_data(${TEXT_CLASSIFICATION_INSTALL_DIR} "text-classification-Senta.tar.gz" "text_classification_data.txt.tar.gz")
inference_analysis_test(test_analyzer_text_classification SRCS analyzer_text_classification_tester.cc
EXTRA_DEPS paddle_inference_api paddle_fluid_api analysis_predictor
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS}
ARGS --infer_model=${TEXT_CLASSIFICATION_INSTALL_DIR}/text-classification-Senta
--infer_data=${TEXT_CLASSIFICATION_INSTALL_DIR}/data.txt)

181
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
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@ -0,0 +1,181 @@
// 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.
#include "paddle/fluid/inference/analysis/analyzer.h"
#include <google/protobuf/text_format.h>
#include <gtest/gtest.h>
#include <thread> // NOLINT
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/pass.h"
#include "paddle/fluid/inference/analysis/ut_helper.h"
#include "paddle/fluid/inference/api/analysis_predictor.h"
#include "paddle/fluid/inference/api/helper.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_pass.h"
DEFINE_string(infer_model, "", "model path");
DEFINE_string(infer_data, "", "data path");
DEFINE_int32(batch_size, 1, "batch size.");
DEFINE_int32(repeat, 1, "Running the inference program repeat times.");
DEFINE_int32(num_threads, 1, "Running the inference program in multi-threads.");
namespace paddle {
namespace inference {
using namespace framework; // NOLINT
struct DataRecord {
std::vector<std::vector<std::vector<float>>> link_step_data_all;
std::vector<size_t> lod;
std::vector<std::vector<float>> rnn_link_data;
std::vector<float> result_data;
size_t batch_iter{0};
size_t batch_size{1};
DataRecord() = default;
explicit DataRecord(const std::string &path, int batch_size = 1)
: batch_size(batch_size) {
Load(path);
}
DataRecord NextBatch() {
DataRecord data;
size_t batch_end = batch_iter + batch_size;
// NOTE skip the final batch, if no enough data is provided.
if (batch_end <= link_step_data_all.size()) {
data.link_step_data_all.assign(link_step_data_all.begin() + batch_iter,
link_step_data_all.begin() + batch_end);
// Prepare LoDs
data.lod.push_back(0);
CHECK(!data.link_step_data_all.empty()) << "empty";
for (size_t j = 0; j < data.link_step_data_all.size(); j++) {
for (const auto &d : data.link_step_data_all[j]) {
data.rnn_link_data.push_back(d);
// calculate lod
data.lod.push_back(data.lod.back() + 11);
}
}
}
batch_iter += batch_size;
return data;
}
void Load(const std::string &path) {
std::ifstream file(path);
std::string line;
int num_lines = 0;
while (std::getline(file, line)) {
num_lines++;
std::vector<std::string> data;
split(line, ':', &data);
if (num_lines % 2) { // feature
std::vector<std::string> feature_data;
split(data[1], ' ', &feature_data);
std::vector<std::vector<float>> link_step_data;
int feature_count = 1;
std::vector<float> feature;
for (auto &step_data : feature_data) {
std::vector<float> tmp;
split_to_float(step_data, ',', &tmp);
feature.insert(feature.end(), tmp.begin(), tmp.end());
if (feature_count % 11 == 0) { // each sample has 11 features
link_step_data.push_back(feature);
feature.clear();
}
feature_count++;
}
link_step_data_all.push_back(std::move(link_step_data));
} else { // result
std::vector<float> tmp;
split_to_float(data[1], ',', &tmp);
result_data.insert(result_data.end(), tmp.begin(), tmp.end());
}
}
}
};
void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data,
int batch_size) {
PaddleTensor feed_tensor;
feed_tensor.name = "feed";
auto one_batch = data->NextBatch();
int token_size = one_batch.rnn_link_data.size();
// each token has 11 features, each feature's dim is 54.
std::vector<int> rnn_link_data_shape({token_size * 11, 54});
feed_tensor.shape = rnn_link_data_shape;
feed_tensor.lod.assign({one_batch.lod});
feed_tensor.dtype = PaddleDType::FLOAT32;
TensorAssignData<float>(&feed_tensor, one_batch.rnn_link_data);
// Set inputs.
input_slots->assign({feed_tensor});
}
void CompareResult(const std::vector<PaddleTensor> &outputs,
const std::vector<float> &base_result) {
PADDLE_ENFORCE_GT(outputs.size(), 0);
for (size_t i = 0; i < outputs.size(); i++) {
auto &out = outputs[i];
size_t size = std::accumulate(out.shape.begin(), out.shape.end(), 1,
[](int a, int b) { return a * b; });
PADDLE_ENFORCE_GT(size, 0);
float *data = static_cast<float *>(out.data.data());
for (size_t i = 0; i < size; i++) {
EXPECT_NEAR(data[i], base_result[i], 1e-3);
}
}
}
// Test with a really complicate model.
void TestRNN2Prediction() {
AnalysisConfig config;
config.prog_file = FLAGS_infer_model + "/__model__";
config.param_file = FLAGS_infer_model + "/param";
config.use_gpu = false;
config.device = 0;
config.specify_input_name = true;
config.enable_ir_optim = true;
PADDLE_ENFORCE(config.ir_mode ==
AnalysisConfig::IrPassMode::kExclude); // default
int batch_size = FLAGS_batch_size;
int num_times = FLAGS_repeat;
auto base_predictor =
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(config);
auto predictor =
CreatePaddlePredictor<AnalysisConfig, PaddleEngineKind::kAnalysis>(
config);
std::vector<PaddleTensor> input_slots;
DataRecord data(FLAGS_infer_data, batch_size);
PrepareInputs(&input_slots, &data, batch_size);
std::vector<PaddleTensor> outputs, base_outputs;
Timer timer1;
timer1.tic();
for (int i = 0; i < num_times; i++) {
base_predictor->Run(input_slots, &base_outputs);
}
PrintTime(batch_size, num_times, 1, 0, timer1.toc() / num_times);
Timer timer2;
timer2.tic();
for (int i = 0; i < num_times; i++) {
predictor->Run(input_slots, &outputs);
}
PrintTime(batch_size, num_times, 1, 0, timer2.toc() / num_times);
CompareResult(base_outputs, data.result_data);
CompareResult(outputs, data.result_data);
}
TEST(Analyzer, rnn2) { TestRNN2Prediction(); }
} // namespace inference
} // namespace paddle

10
paddle/fluid/operators/distributed/grpc_client.cc
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@ -290,12 +290,18 @@ void GRPCClient::Proceed() {
c->Finish(false);
}
delete c;
bool notify = false;
{
std::lock_guard<std::mutex> lk(sync_mutex_);
req_count_--;
notify = (req_count_ <= 0 || !c->status_.ok());
}
delete c;
if (notify) {
sync_cond_.notify_all();
}
sync_cond_.notify_all();
}
VLOG(3) << "GRPCClient Proceed end";
}

4
python/paddle/fluid/tests/unittests/CMakeLists.txt
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@ -28,6 +28,10 @@ list(REMOVE_ITEM TEST_OPS test_cond_op) # FIXME(qijun): https://github.com/Paddl
list(REMOVE_ITEM TEST_OPS op_test) # op_test is a helper python file, not a test
list(REMOVE_ITEM TEST_OPS decorators) # decorators is a helper python file, not a test
if(APPLE)
# this op is not support on mac
list(REMOVE_ITEM TEST_OPS test_fusion_seqexpand_concat_fc_op)
endif()
function(py_test_modules TARGET_NAME)
if(WITH_TESTING)

2
python/paddle/fluid/tests/unittests/test_data_balance.py
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@ -84,7 +84,7 @@ class TestDataBalance(unittest.TestCase):
self.data_file_name = './data_balance_test.recordio'
self.lod_data_file_name = './data_balance_with_lod_test.recordio'
self.total_ins_num = 50
self.batch_size = 10
self.batch_size = 12
self.prepare_data()
self.prepare_lod_data()

4
python/paddle/fluid/tests/unittests/test_reader_reset.py
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@ -13,7 +13,7 @@
# limitations under the License.
from __future__ import print_function
import os
import paddle.fluid as fluid
import paddle
import numpy as np
@ -41,6 +41,8 @@ class TestReaderReset(unittest.TestCase):
self.data_file_name, reader, feeder)
def setUp(self):
# set parallel threads to fit 20 batches in line 49
os.environ['CPU_NUM'] = str(20)
self.use_cuda = fluid.core.is_compiled_with_cuda()
self.data_file_name = './reader_reset_test.recordio'
self.ins_shape = [3]

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