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未验证 提交 047bba85 编写于 作者: 石 石晓伟 提交者： GitHub
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Remove the obsolete cmake options (#18481) 

* remove the obsolete cmake options, test=develop

* remove unittests, test=develop
上级 e9c7e218
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Showing with 12 addition and 443 deletion
CMakeLists.txt
浏览文件 @ 047bba85
......@@ -59,7 +59,6 @@ option(WITH_DISTRIBUTE "Compile with distributed support" OFF)
option(WITH_BRPC_RDMA "Use brpc rdma as the rpc protocal" OFF)
option(ON_INFER "Turn on inference optimization." OFF)
################################ Internal Configurations #######################################
option(WITH_ANAKIN "Compile with Anakin library" OFF)
option(WITH_AMD_GPU "Compile PaddlePaddle with AMD GPU" OFF)
option(WITH_NGRAPH "Compile PaddlePaddle with nGraph support." OFF)
option(WITH_PROFILER "Compile PaddlePaddle with GPU profiler and gperftools" OFF)
......@@ -68,9 +67,6 @@ option(COVERALLS_UPLOAD "Package code coverage data to coveralls" OFF)
option(WITH_PSLIB "Compile with pslib support" OFF)
option(WITH_CONTRIB "Compile the third-party contributation" OFF)
option(REPLACE_ENFORCE_GLOG "Replace PADDLE_ENFORCE with glog/CHECK for better debug." OFF)
# TODO(Superjomn) Remove WITH_ANAKIN option if not needed latter.
option(ANAKIN_BUILD_FAT_BIN "Build anakin cuda fat-bin lib for all device plantform, ignored when WITH_ANAKIN=OFF" OFF)
option(ANAKIN_BUILD_CROSS_PLANTFORM "Build anakin lib for any nvidia device plantform. ignored when WITH_ANAKIN=OFF" ON)
option(WITH_GRPC "Use grpc as the default rpc framework" ${WITH_DISTRIBUTE})
option(WITH_INFERENCE_API_TEST "Test fluid inference C++ high-level api interface" OFF)
option(WITH_HIGH_LEVEL_API_TEST "Test fluid python high-level api interface" OFF)
......@@ -184,6 +180,7 @@ if(WITH_BRPC_RDMA)
endif()
endif()
include(anakin_subgraph)
include(external/threadpool)
include(flags) # set paddle compile flags
......@@ -193,7 +190,6 @@ include(configure) # add paddle env configuration
if(WITH_GPU)
include(cuda)
include(tensorrt)
include(anakin_subgraph)
endif()
if(WIN32 OR APPLE OR NOT WITH_GPU OR ON_INFER)
......@@ -206,12 +202,6 @@ if(WITH_DGC)
add_definitions(-DPADDLE_WITH_DGC)
endif()
if(WITH_MKL OR WITH_MKLML)
include(external/anakin)
elseif()
set(WITH_ANAKIN OFF CACHE STRING "Anakin is used in MKL only now." FORCE)
endif()
if (WITH_PROFILER)
find_package(Gperftools REQUIRED)
include_directories(${GPERFTOOLS_INCLUDE_DIR})
......
cmake/configure.cmake
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......@@ -99,23 +99,15 @@ if(WITH_GPU)
endif()
include_directories(${TENSORRT_INCLUDE_DIR})
endif()
if(WITH_ANAKIN)
if(ANAKIN_FOUND)
if(${CUDA_VERSION_MAJOR} VERSION_LESS 8)
message(WARNING "Anakin needs CUDA >= 8.0 to compile. Force WITH_ANAKIN=OFF")
set(WITH_ANAKIN OFF CACHE STRING "Anakin is valid only when CUDA >= 8.0." FORCE)
message(WARNING "Anakin needs CUDA >= 8.0 to compile. Force ANAKIN_FOUND = OFF")
set(ANAKIN_FOUND OFF CACHE STRING "Anakin is valid only when CUDA >= 8.0." FORCE)
endif()
if(${CUDNN_MAJOR_VERSION} VERSION_LESS 7)
message(WARNING "Anakin needs CUDNN >= 7.0 to compile. Force WITH_ANAKIN=OFF")
set(WITH_ANAKIN OFF CACHE STRING "Anakin is valid only when CUDNN >= 7.0." FORCE)
message(WARNING "Anakin needs CUDNN >= 7.0 to compile. Force ANAKIN_FOUND = OFF")
set(ANAKIN_FOUND OFF CACHE STRING "Anakin is valid only when CUDNN >= 7.0." FORCE)
endif()
add_definitions(-DWITH_ANAKIN)
endif()
if(WITH_ANAKIN)
# NOTICE(minqiyang): the end slash is important because $CUDNN_INCLUDE_DIR
# is a softlink to real cudnn.h directory
set(ENV{CUDNN_INCLUDE_DIR} "${CUDNN_INCLUDE_DIR}/")
get_filename_component(CUDNN_LIBRARY_DIR ${CUDNN_LIBRARY} DIRECTORY)
set(ENV{CUDNN_LIBRARY} ${CUDNN_LIBRARY_DIR})
endif()
elseif(WITH_AMD_GPU)
add_definitions(-DPADDLE_WITH_HIP)
......
cmake/external/anakin.cmake 已删除 100644 → 0
浏览文件 @ e9c7e218
if (NOT WITH_ANAKIN)
return()
endif()
option(ANAKIN_ENABLE_OP_TIMER "Get more detailed information with Anakin op time" OFF)
if(ANAKIN_ENABLE_OP_TIMER)
add_definitions(-DPADDLE_ANAKIN_ENABLE_OP_TIMER)
endif()
INCLUDE(ExternalProject)
set(ANAKIN_SOURCE_DIR ${THIRD_PARTY_PATH}/anakin)
# the anakin install dir is only default one now
set(ANAKIN_INSTALL_DIR ${THIRD_PARTY_PATH}/anakin/src/extern_anakin/output)
set(ANAKIN_INCLUDE ${ANAKIN_INSTALL_DIR})
set(ANAKIN_LIBRARY ${ANAKIN_INSTALL_DIR})
set(ANAKIN_SHARED_LIB ${ANAKIN_LIBRARY}/libanakin.so)
set(ANAKIN_SABER_LIB ${ANAKIN_LIBRARY}/libanakin_saber_common.so)
include_directories(${ANAKIN_INCLUDE})
include_directories(${ANAKIN_INCLUDE}/saber/)
include_directories(${ANAKIN_INCLUDE}/saber/core/)
include_directories(${ANAKIN_INCLUDE}/saber/funcs/impl/x86/)
include_directories(${ANAKIN_INCLUDE}/saber/funcs/impl/cuda/base/cuda_c/)
set(ANAKIN_COMPILE_EXTRA_FLAGS
-Wno-error=unused-but-set-variable -Wno-unused-but-set-variable
-Wno-error=unused-variable -Wno-unused-variable
-Wno-error=format-extra-args -Wno-format-extra-args
-Wno-error=comment -Wno-comment
-Wno-error=format -Wno-format
-Wno-error=maybe-uninitialized -Wno-maybe-uninitialized
-Wno-error=switch -Wno-switch
-Wno-error=return-type -Wno-return-type
-Wno-error=non-virtual-dtor -Wno-non-virtual-dtor
-Wno-error=ignored-qualifiers
-Wno-ignored-qualifiers
-Wno-sign-compare
-Wno-reorder
-Wno-error=cpp)
if(WITH_GPU)
set(CMAKE_ARGS_PREFIX -DUSE_GPU_PLACE=YES -DCUDNN_ROOT=${CUDNN_ROOT} -DCUDNN_INCLUDE_DIR=${CUDNN_INCLUDE_DIR})
else()
set(CMAKE_ARGS_PREFIX -DUSE_GPU_PLACE=NO)
endif()
ExternalProject_Add(
extern_anakin
${EXTERNAL_PROJECT_LOG_ARGS}
DEPENDS ${MKLML_PROJECT}
GIT_REPOSITORY "https://github.com/PaddlePaddle/Anakin"
GIT_TAG "3c8554f4978628183566ab7dd6c1e7e66493c7cd"
PREFIX ${ANAKIN_SOURCE_DIR}
UPDATE_COMMAND ""
CMAKE_ARGS ${CMAKE_ARGS_PREFIX}
-DUSE_LOGGER=YES
-DUSE_X86_PLACE=YES
-DBUILD_WITH_UNIT_TEST=NO
-DPROTOBUF_ROOT=${THIRD_PARTY_PATH}/install/protobuf
-DMKLML_ROOT=${THIRD_PARTY_PATH}/install/mklml
-DENABLE_OP_TIMER=${ANAKIN_ENABLE_OP_TIMER}
-DBUILD_FAT_BIN=${ANAKIN_BUILD_FAT_BIN}
-DBUILD_CROSS_PLANTFORM=${ANAKIN_BUILD_CROSS_PLANTFORM}
${EXTERNAL_OPTIONAL_ARGS}
CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${ANAKIN_INSTALL_DIR}
)
message(STATUS "Anakin for inference is enabled")
message(STATUS "Anakin is set INCLUDE:${ANAKIN_INCLUDE} LIBRARY:${ANAKIN_LIBRARY}")
add_dependencies(extern_anakin protobuf mklml)
add_library(anakin_shared SHARED IMPORTED GLOBAL)
set_property(TARGET anakin_shared PROPERTY IMPORTED_LOCATION ${ANAKIN_SHARED_LIB})
add_dependencies(anakin_shared extern_anakin)
add_library(anakin_saber SHARED IMPORTED GLOBAL)
set_property(TARGET anakin_saber PROPERTY IMPORTED_LOCATION ${ANAKIN_SABER_LIB})
add_dependencies(anakin_saber extern_anakin)
cmake/inference_lib.cmake
浏览文件 @ 047bba85
......@@ -207,14 +207,6 @@ copy(memory_lib
set(inference_deps paddle_fluid_shared paddle_fluid)
set(module "inference/api")
if (WITH_ANAKIN AND WITH_MKL)
copy(anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
SRCS
${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libinference_anakin_api* # compiled anakin api
${ANAKIN_INSTALL_DIR} # anakin release
DSTS ${FLUID_INSTALL_DIR}/third_party/install/anakin ${FLUID_INSTALL_DIR}/third_party/install/anakin)
list(APPEND inference_deps anakin_inference_lib)
endif ()
if (TENSORRT_FOUND)
copy(tensorrt_lib DEPS ${inference_deps}
......@@ -222,6 +214,11 @@ if (TENSORRT_FOUND)
DSTS ${FLUID_INSTALL_DIR}/third_party/install/tensorrt/include ${FLUID_INSTALL_DIR}/third_party/install/tensorrt/lib)
endif ()
if (ANAKIN_FOUND)
copy(anakin_lib DEPS ${inference_deps}
SRCS ${ANAKIN_ROOT}/*
DSTS ${FLUID_INSTALL_DIR}/third_party/install/anakin)
endif ()
set(module "inference")
if(WIN32)
......
paddle/fluid/inference/api/paddle_inference_api.h
浏览文件 @ 047bba85
......@@ -28,6 +28,6 @@ limitations under the License. */
#include "paddle_analysis_config.h" // NOLINT
#include "paddle_api.h" // NOLINT
#if (defined WITH_ANAKIN) || (defined PADDLE_WITH_ANAKIN)
#if (defined PADDLE_WITH_ANAKIN)
#include "paddle_anakin_config.h" // NOLINT
#endif
paddle/fluid/inference/tests/api/CMakeLists.txt
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......@@ -254,27 +254,6 @@ set(BERT_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/bert_emb128")
download_model_and_data(${BERT_INSTALL_DIR} "bert_emb128_model.tar.gz" "bert_data_len20.txt.tar.gz")
inference_analysis_api_test(test_analyzer_bert ${BERT_INSTALL_DIR} analyzer_bert_tester.cc)
# anakin
if (ANAKIN_FOUND AND WITH_MKL) # only needed in CI
# anakin rnn1
set(ANAKIN_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/anakin")
set(ANAKIN_RNN1_INSTALL_DIR "${ANAKIN_INSTALL_DIR}/rnn1")
inference_download(${ANAKIN_RNN1_INSTALL_DIR} ${INFERENCE_URL} "anakin_test%2Fditu_rnn.anakin2.model.bin")
inference_download(${ANAKIN_RNN1_INSTALL_DIR} ${INFERENCE_URL} "anakin_test%2Fditu_rnn_data.txt")
cc_test(test_anakin_rnn1 SRCS anakin_rnn1_tester.cc
ARGS --model=${ANAKIN_RNN1_INSTALL_DIR}/anakin_test%2Fditu_rnn.anakin2.model.bin
--datapath=${ANAKIN_RNN1_INSTALL_DIR}/anakin_test%2Fditu_rnn_data.txt
DEPS inference_anakin_api_shared)
# anakin mobilenet
if(WITH_GPU)
set(ANAKIN_MOBILENET_INSTALL_DIR "${ANAKIN_INSTALL_DIR}/mobilenet")
inference_download(${ANAKIN_MOBILENET_INSTALL_DIR} ${INFERENCE_URL} "mobilenet_v2.anakin.bin")
cc_test(test_anakin_mobilenet SRCS anakin_mobilenet_tester.cc
ARGS --model=${ANAKIN_MOBILENET_INSTALL_DIR}/mobilenet_v2.anakin.bin
DEPS inference_anakin_api_shared dynload_cuda)
endif()
endif()
if(WITH_GPU AND TENSORRT_FOUND)
set(TRT_MODEL_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/trt")
if (NOT EXISTS ${TRT_MODEL_INSTALL_DIR})
......
paddle/fluid/inference/tests/api/anakin_mobilenet_tester.cc 已删除 100644 → 0
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/* 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 <glog/logging.h>
#include <gtest/gtest.h>
#include "gflags/gflags.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
DEFINE_string(model, "", "Directory of the inference model(mobile_v2).");
namespace paddle {
contrib::AnakinConfig GetConfig() {
contrib::AnakinConfig config;
// using AnakinConfig::X86 if you need to use cpu to do inference
config.target_type = contrib::AnakinConfig::NVGPU;
config.model_file = FLAGS_model;
config.device_id = 0;
config.init_batch_size = 1;
return config;
}
TEST(inference, anakin) {
auto config = GetConfig();
auto predictor =
CreatePaddlePredictor<contrib::AnakinConfig, PaddleEngineKind::kAnakin>(
config);
float data[1 * 3 * 224 * 224] = {1.0f};
PaddleTensor tensor;
tensor.name = "input_0";
tensor.shape = std::vector<int>({1, 3, 224, 224});
tensor.data = PaddleBuf(data, sizeof(data));
tensor.dtype = PaddleDType::FLOAT32;
// For simplicity, we set all the slots with the same data.
std::vector<PaddleTensor> paddle_tensor_feeds(1, tensor);
PaddleTensor tensor_out;
tensor_out.name = "prob_out";
tensor_out.shape = std::vector<int>({});
tensor_out.data = PaddleBuf();
tensor_out.dtype = PaddleDType::FLOAT32;
std::vector<PaddleTensor> outputs(1, tensor_out);
ASSERT_TRUE(predictor->Run(paddle_tensor_feeds, &outputs));
float* data_o = static_cast<float*>(outputs[0].data.data());
for (size_t j = 0; j < outputs[0].data.length(); ++j) {
LOG(INFO) << "output[" << j << "]: " << data_o[j];
}
}
} // namespace paddle
paddle/fluid/inference/tests/api/anakin_rnn1_tester.cc 已删除 100644 → 0
浏览文件 @ e9c7e218
/* 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 <gflags/gflags.h>
#include <time.h>
#include <algorithm>
#include <fstream>
#include <iostream>
#include <thread> // NOLINT
#include <vector>
#include "paddle/fluid/inference/api/helper.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "utils/logger/logger.h"
DEFINE_string(model, "", "Directory of the inference model.");
DEFINE_string(datapath, "", "Path of the dataset.");
DEFINE_int32(batch_size, 1, "batch size.");
DEFINE_int32(repeat, 1, "Running the inference program repeat times.");
class Data {
public:
Data(std::string file_name, int batch_size)
: _batch_size(batch_size), _total_length(0) {
_file.open(file_name);
_file.seekg(_file.end);
_total_length = _file.tellg();
_file.seekg(_file.beg);
}
void get_batch_data(std::vector<std::vector<float>>& fea, // NOLINT
std::vector<std::vector<float>>& week_fea, // NOLINT
std::vector<std::vector<float>>& time_fea, // NOLINT
std::vector<long unsigned int>& seq_offset); // NOLINT
private:
std::fstream _file;
int _total_length;
int _batch_size;
};
void Data::get_batch_data(
std::vector<std::vector<float>>& fea, // NOLINT
std::vector<std::vector<float>>& week_fea, // NOLINT
std::vector<std::vector<float>>& time_fea, // NOLINT
std::vector<long unsigned int>& seq_offset) { // NOLINT
int seq_num = 0;
long unsigned int cum = 0; // NOLINT
char buf[10000];
seq_offset.clear();
seq_offset.push_back(0);
fea.clear();
week_fea.clear();
time_fea.clear();
while (_file.getline(buf, 10000)) {
std::vector<std::string> data_vec;
paddle::inference::split(buf, ':', &data_vec);
std::vector<std::string> seq;
paddle::inference::split(data_vec[0], '|', &seq);
for (auto link : seq) {
std::vector<float> vec;
paddle::inference::split_to_float(link, ',', &vec);
fea.push_back(vec);
}
std::vector<float> vec_w;
paddle::inference::split_to_float(data_vec[2], ',', &vec_w);
week_fea.push_back(vec_w);
std::vector<float> vec_t;
paddle::inference::split_to_float(data_vec[1], ',', &vec_t);
time_fea.push_back(vec_t);
cum += seq.size();
seq_offset.push_back(cum);
seq_num++;
if (seq_num >= _batch_size) {
break;
}
}
}
namespace paddle {
contrib::AnakinConfig GetConfig() {
contrib::AnakinConfig config;
// using AnakinConfig::X86 if you need to use cpu to do inference
config.target_type = contrib::AnakinConfig::X86;
config.model_file = FLAGS_model;
config.device_id = 0;
config.init_batch_size = 1000; // the max number of token
return config;
}
void set_tensor(std::string name, std::vector<int> shape,
std::vector<PaddleTensor>& vec) { // NOLINT
int sum = 1;
std::for_each(shape.begin(), shape.end(), [&](int n) { sum *= n; });
float* data = new float[sum];
PaddleTensor tensor;
tensor.name = name;
tensor.shape = shape;
tensor.data = PaddleBuf(data, sum);
tensor.dtype = PaddleDType::FLOAT32;
vec.push_back(tensor);
}
void single_test() {
auto config = GetConfig();
auto predictor =
CreatePaddlePredictor<contrib::AnakinConfig, PaddleEngineKind::kAnakin>(
config);
int max_batch_size = 1000;
std::string feature_file = FLAGS_datapath;
Data map_data(feature_file, FLAGS_batch_size);
std::vector<std::vector<float>> fea;
std::vector<std::vector<float>> week_fea;
std::vector<std::vector<float>> time_fea;
std::vector<long unsigned int> seq_offset; // NOLINT
paddle::PaddleTensor tensor_0, tensor_1, tensor_2;
tensor_0.name = "input_0";
tensor_1.name = "input_4";
tensor_2.name = "input_5";
PaddleTensor tensor_out;
tensor_out.name = "final_output.tmp_1_gout";
tensor_out.shape = std::vector<int>({});
tensor_out.data = PaddleBuf();
tensor_out.dtype = PaddleDType::FLOAT32;
std::vector<PaddleTensor> inputs;
std::vector<PaddleTensor> outputs(1, tensor_out);
int data_0_dim = 38;
int data_1_dim = 10;
int data_2_dim = 10;
float data_0[max_batch_size * data_0_dim]; // NOLINT
float data_1[max_batch_size * data_1_dim]; // NOLINT
float data_2[max_batch_size * data_2_dim]; // NOLINT
int count = 0;
while (true) {
if (count++ > 0) break; // only run the first batch in ci.
seq_offset.clear();
map_data.get_batch_data(fea, week_fea, time_fea, seq_offset);
if (seq_offset.size() <= 1) {
LOG(FATAL) << "seq_offset.size() <= 1, exit.";
break;
}
std::vector<std::vector<long unsigned int>> seq_offset_vec; // NOLINT
seq_offset_vec.push_back(seq_offset);
tensor_0.lod = seq_offset_vec;
int p_shape_0[] = {(int)fea.size(), 1, 1, data_0_dim}; // NOLINT
int p_shape_1[] = {(int)week_fea.size(), data_1_dim, 1, 1}; // NOLINT
int p_shape_2[] = {(int)time_fea.size(), data_2_dim, 1, 1}; // NOLINT
std::vector<int> shape_0(p_shape_0, p_shape_0 + 4);
std::vector<int> shape_1(p_shape_1, p_shape_1 + 4);
std::vector<int> shape_2(p_shape_2, p_shape_2 + 4);
tensor_0.shape = shape_0;
tensor_1.shape = shape_1;
tensor_2.shape = shape_2;
for (int i = 0; i < fea.size(); i++) {
memcpy(data_0 + i * data_0_dim, &fea[i][0], sizeof(float) * data_0_dim);
}
for (int i = 0; i < week_fea.size(); i++) {
memcpy(data_1 + i * data_1_dim, &week_fea[i][0],
sizeof(float) * data_1_dim);
}
for (int i = 0; i < time_fea.size(); i++) {
memcpy(data_2 + i * data_2_dim, &time_fea[i][0],
sizeof(float) * data_2_dim);
}
tensor_0.data =
paddle::PaddleBuf(data_0, fea.size() * sizeof(float) * data_0_dim);
tensor_1.data =
paddle::PaddleBuf(data_1, week_fea.size() * sizeof(float) * data_1_dim);
tensor_2.data =
paddle::PaddleBuf(data_2, time_fea.size() * sizeof(float) * data_2_dim);
tensor_0.dtype = paddle::PaddleDType::FLOAT32;
tensor_1.dtype = paddle::PaddleDType::FLOAT32;
tensor_2.dtype = paddle::PaddleDType::FLOAT32;
inputs.clear();
inputs.push_back(tensor_1);
inputs.push_back(tensor_2);
inputs.push_back(tensor_0);
paddle::inference::Timer timer;
timer.tic();
for (int i = 0; i < FLAGS_repeat; i++) predictor->Run(inputs, &outputs);
paddle::inference::PrintTime(FLAGS_batch_size, FLAGS_repeat, 1, 0,
timer.toc() / FLAGS_repeat);
LOG(INFO) << "sequence_length = " << seq_offset[seq_offset.size() - 1];
float* data_o = static_cast<float*>(outputs[0].data.data());
VLOG(3) << "outputs[0].data.length() = " << outputs[0].data.length();
for (size_t j = 0; j < outputs[0].data.length(); ++j) {
VLOG(3) << "output[" << j << "]: " << data_o[j];
}
}
}
} // namespace paddle
int main(int argc, char** argv) {
google::ParseCommandLineFlags(&argc, &argv, true);
logger::init(argv[0]);
paddle::single_test();
/* multi-threads
std::vector<std::thread> threads;
int num = 1;
for (int i = 0; i < num; i++) {
LOG(INFO) << " thread id : " << i;
threads.emplace_back(paddle::single_test);
}
for (int i = 0; i < num; i++) {
threads[i].join();
}
threads.clear();
*/
return 0;
}
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