提交 ebd9f7fc 编写于 作者: Q qiaolongfei

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into add-fake-reader

test=develop
......@@ -40,7 +40,7 @@ set(OPENBLAS_LIB_SEARCH_PATHS
/usr/local/opt/openblas/lib)
find_path(OPENBLAS_INC_DIR NAMES cblas.h
PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS} NO_DEFAULT_PATH)
find_path(OPENBLAS_LAPACKE_INC_DIR NAMES lapacke.h
PATHS ${OPENBLAS_INCLUDE_SEARCH_PATHS})
find_library(OPENBLAS_LIB NAMES openblas
......
......@@ -27,7 +27,7 @@ IF(NOT ${CBLAS_FOUND})
SET(CBLAS_SOURCES_DIR ${THIRD_PARTY_PATH}/openblas)
SET(CBLAS_INSTALL_DIR ${THIRD_PARTY_PATH}/install/openblas)
SET(CBLAS_INCLUDE_DIR "${CBLAS_INSTALL_DIR}/include" CACHE PATH "openblas include directory." FORCE)
SET(CBLAS_INC_DIR "${CBLAS_INSTALL_DIR}/include" CACHE PATH "openblas include directory." FORCE)
SET(CBLAS_LIBRARIES
"${CBLAS_INSTALL_DIR}/lib/${CMAKE_STATIC_LIBRARY_PREFIX}openblas${CMAKE_STATIC_LIBRARY_SUFFIX}"
......@@ -96,7 +96,7 @@ IF(NOT ${CBLAS_FOUND})
ENDIF(NOT WIN32)
SET(CBLAS_PROVIDER openblas)
IF(WITH_C_API)
INSTALL(DIRECTORY ${CBLAS_INCLUDE_DIR} DESTINATION third_party/openblas)
INSTALL(DIRECTORY ${CBLAS_INC_DIR} DESTINATION third_party/openblas)
# Because libopenblas.a is a symbolic link of another library, thus need to
# install the whole directory.
IF(ANDROID)
......@@ -117,8 +117,8 @@ IF(NOT ${CBLAS_FOUND})
ENDIF(NOT ${CBLAS_FOUND})
MESSAGE(STATUS "BLAS library: ${CBLAS_LIBRARIES}")
MESSAGE(STATUS "BLAS Include: ${CBLAS_INCLUDE_DIR}")
INCLUDE_DIRECTORIES(${CBLAS_INCLUDE_DIR})
MESSAGE(STATUS "BLAS Include: ${CBLAS_INC_DIR}")
INCLUDE_DIRECTORIES(${CBLAS_INC_DIR})
# FIXME(gangliao): generate cblas target to track all high performance
# linear algebra libraries for cc_library(xxx SRCS xxx.c DEPS cblas)
......
# windows treat symbolic file as a real file, which is different with unix
# We create a hidden file and compile it instead of origin source file.
function(windows_symbolic TARGET)
......@@ -9,11 +10,23 @@ function(windows_symbolic TARGET)
if (NOT EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/${src}.cc OR NOT EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/${src}.cu)
message(FATAL " ${src}.cc and ${src}.cu must exsits, and ${src}.cu must be symbolic file.")
endif()
add_custom_command(OUTPUT .${src}.cu
# only copy the xx.cu to .xx.cu when the content are modified
set(copy_flag 1)
if (EXISTS ${CMAKE_CURRENT_SOURCE_DIR}/.${src}.cu)
file(READ ${CMAKE_CURRENT_SOURCE_DIR}/${src}.cc SOURCE_STR)
file(READ ${CMAKE_CURRENT_SOURCE_DIR}/.${src}.cu TARGET_STR)
if (SOURCE_STR STREQUAL TARGET_STR)
set(copy_flag 0)
endif()
endif()
if (copy_flag)
add_custom_command(OUTPUT .${src}.cu
COMMAND ${CMAKE_COMMAND} -E remove ${CMAKE_CURRENT_SOURCE_DIR}/.${src}.cu
COMMAND ${CMAKE_COMMAND} -E copy "${CMAKE_CURRENT_SOURCE_DIR}/${src}.cc" "${CMAKE_CURRENT_SOURCE_DIR}/.${src}.cu"
COMMENT "create hidden file of ${src}.cu")
add_custom_target(${TARGET} ALL DEPENDS .${src}.cu)
endif(copy_flag)
add_custom_target(${TARGET} ALL DEPENDS .${src}.cu)
endforeach()
endfunction()
......@@ -81,6 +94,8 @@ nv_test(data_device_transform_test SRCS data_device_transform_test.cu
if(WITH_GPU)
if (WIN32)
# windows treat symbolic file as a real file, which is different with unix
# We create a hidden file and compile it instead of origin source file.
windows_symbolic(hidden_file SRCS data_type_transform.cu)
nv_library(data_type_transform SRCS .data_type_transform.cu DEPS tensor)
add_dependencies(data_type_transform hidden_file)
......@@ -149,7 +164,7 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
else()
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass)
cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass elementwise_add_op)
cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op)
endif()
if (NOT WIN32)
......
......@@ -146,5 +146,22 @@ void NaiveExecutor::CleanFeedFetchOps() {
ops_.swap(ops);
}
void NaiveExecutor::EnableMKLDNN(const ProgramDesc &program) {
#ifdef PADDLE_WITH_MKLDNN
VLOG(3) << "use_mkldnn=True";
for (size_t block_id = 0; block_id < program.Size(); ++block_id) {
auto *block = const_cast<ProgramDesc &>(program).MutableBlock(block_id);
for (auto *op : block->AllOps()) {
if (op->HasAttr("use_mkldnn")) {
op->SetAttr("use_mkldnn", true);
}
}
}
#else
LOG(WARNING)
<< "'MKLDNN' is not supported, Please re-compile with WITH_MKLDNN option";
#endif
}
} // namespace framework
} // namespace paddle
......@@ -14,6 +14,8 @@
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
......@@ -46,6 +48,8 @@ class NaiveExecutor {
void CleanFeedFetchOps();
void EnableMKLDNN(const ProgramDesc& program);
protected:
void CreateVariables(const ProgramDesc& desc, Scope* scope, int block_id);
......
......@@ -46,6 +46,7 @@ struct RWLock {
private:
pthread_rwlock_t lock_;
};
// TODO(paddle-dev): Support RWLock for WIN32 for correctness.
#else
// https://stackoverflow.com/questions/7125250/making-pthread-rwlock-wrlock-recursive
// In windows, rw_lock seems like a hack. Use empty object and do nothing.
......
......@@ -20,8 +20,6 @@ cc_test(test_node SRCS node_tester.cc DEPS analysis)
cc_test(test_dot SRCS dot_tester.cc DEPS analysis)
cc_binary(inference_analyzer SRCS analyzer_main.cc DEPS analysis paddle_fluid)
set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests)
function (inference_analysis_test TARGET)
if(WITH_TESTING)
set(options "")
......
......@@ -31,7 +31,6 @@ function(inference_api_test TARGET_NAME)
set(multiValueArgs ARGS)
cmake_parse_arguments(inference_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests)
cc_test(${TARGET_NAME}
SRCS ${inference_test_SRC}
DEPS "${inference_deps}"
......
......@@ -71,6 +71,11 @@ bool AnalysisPredictor::Init(
} else {
inference_program_ = program;
}
if (config_._use_mkldnn) {
executor_->EnableMKLDNN(*inference_program_);
}
executor_->Prepare(scope_.get(), *inference_program_, 0,
config_.use_feed_fetch_ops);
......@@ -92,6 +97,7 @@ bool AnalysisPredictor::Run(const std::vector<PaddleTensor> &inputs,
LOG(ERROR) << "fail to set feed";
return false;
}
// Run the inference program
// if share variables, we need not create variables
executor_->Run();
......
......@@ -70,6 +70,14 @@ if (NOT EXISTS ${OCR_INSTALL_DIR})
endif()
inference_analysis_api_test(test_analyzer_ocr ${OCR_INSTALL_DIR} analyzer_vis_tester.cc)
# resnet50
set(RESNET50_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/resnet50")
if (NOT EXISTS ${RESNET50_INSTALL_DIR})
inference_download_and_uncompress(${RESNET50_INSTALL_DIR} ${INFERENCE_URL} "resnet50_model.tar.gz")
endif()
inference_analysis_test(test_analyzer_resnet50 SRCS analyzer_resnet50_tester.cc
EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} ARGS --infer_model=${RESNET50_INSTALL_DIR}/model)
# anakin
if (WITH_ANAKIN AND WITH_MKL) # only needed in CI
# anakin rnn1
......
/* 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 <fstream>
#include <iostream>
#include "paddle/fluid/inference/tests/api/tester_helper.h"
namespace paddle {
namespace inference {
namespace analysis {
void SetConfig(AnalysisConfig *cfg) {
cfg->param_file = FLAGS_infer_model + "/params";
cfg->prog_file = FLAGS_infer_model + "/model";
cfg->use_gpu = false;
cfg->device = 0;
cfg->enable_ir_optim = true;
cfg->specify_input_name = true;
}
void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
PADDLE_ENFORCE_EQ(FLAGS_test_all_data, 0, "Only have single batch of data.");
PaddleTensor input;
// channel=3, height/width=318
std::vector<int> shape({FLAGS_batch_size, 3, 318, 318});
input.shape = shape;
input.dtype = PaddleDType::FLOAT32;
// fill input data, for profile easily, do not use random data here.
size_t size = FLAGS_batch_size * 3 * 318 * 318;
input.data.Resize(size * sizeof(float));
float *input_data = static_cast<float *>(input.data.data());
for (size_t i = 0; i < size; i++) {
*(input_data + i) = static_cast<float>(i) / size;
}
std::vector<PaddleTensor> input_slots;
input_slots.assign({input});
(*inputs).emplace_back(input_slots);
}
// Easy for profiling independently.
TEST(Analyzer_resnet50, profile) {
AnalysisConfig cfg;
SetConfig(&cfg);
std::vector<PaddleTensor> outputs;
std::vector<std::vector<PaddleTensor>> input_slots_all;
SetInput(&input_slots_all);
TestPrediction(cfg, input_slots_all, &outputs, FLAGS_num_threads);
if (FLAGS_num_threads == 1 && !FLAGS_test_all_data) {
PADDLE_ENFORCE_EQ(outputs.size(), 1UL);
size_t size = GetSize(outputs[0]);
// output is a 512-dimension feature
EXPECT_EQ(size, 512 * FLAGS_batch_size);
}
}
// Check the fuse status
TEST(Analyzer_resnet50, fuse_statis) {
AnalysisConfig cfg;
SetConfig(&cfg);
int num_ops;
auto predictor = CreatePaddlePredictor<AnalysisConfig>(cfg);
auto fuse_statis = GetFuseStatis(
static_cast<AnalysisPredictor *>(predictor.get()), &num_ops);
ASSERT_TRUE(fuse_statis.count("fc_fuse"));
EXPECT_EQ(fuse_statis.at("fc_fuse"), 1);
}
// Compare result of NativeConfig and AnalysisConfig
TEST(Analyzer_resnet50, compare) {
AnalysisConfig cfg;
SetConfig(&cfg);
std::vector<std::vector<PaddleTensor>> input_slots_all;
SetInput(&input_slots_all);
CompareNativeAndAnalysis(cfg, input_slots_all);
}
} // namespace analysis
} // namespace inference
} // namespace paddle
......@@ -270,10 +270,11 @@ TEST(Analyzer_rnn1, multi_thread) {
std::vector<std::vector<PaddleTensor>> input_slots_all;
SetInput(&input_slots_all);
TestPrediction(cfg, input_slots_all, &outputs, FLAGS_num_threads);
TestPrediction(cfg, input_slots_all, &outputs, 4 /* multi_thread */);
}
bool CompareTensors(framework::Scope &a_scope, framework::Scope &b_scope,
bool CompareTensors(const framework::Scope &a_scope,
const framework::Scope &b_scope,
const std::vector<std::string> &tensors) {
for (auto &x : tensors) {
auto *a_var = a_scope.FindVar(x);
......
......@@ -61,8 +61,6 @@ void SetConfig(AnalysisConfig *cfg) {
cfg->ir_passes.push_back("fc_gru_fuse_pass");
#ifdef PADDLE_WITH_MKLDNN
cfg->_use_mkldnn = true;
// disable mkldnn fuse since it should have some bugs
cfg->ir_passes.push_back("conv_relu_mkldnn_fuse_pass");
#endif
}
......
......@@ -4,7 +4,6 @@ function(inference_test TARGET_NAME)
set(multiValueArgs ARGS)
cmake_parse_arguments(inference_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests)
set(arg_list "")
if(inference_test_ARGS)
foreach(arg ${inference_test_ARGS})
......
......@@ -224,10 +224,12 @@ class WhileGradOp : public framework::OperatorBase {
if (cur_scope_iter == step_scopes->rbegin()) {
auto *var = (*cur_scope_iter)->FindVar(inside_grad_name);
PADDLE_ENFORCE_NOT_NULL(var, "Can not find var %s", inside_grad_name);
PADDLE_ENFORCE(var->IsType<framework::LoDTensorArray>() ||
var->IsType<LoDTensor>(),
"Currently the type of var only can be LoDTensorArray "
"or LoDTensor.");
PADDLE_ENFORCE(
var->IsType<framework::LoDTensorArray>() ||
var->IsType<LoDTensor>(),
"Currently the type of var only can be LoDTensorArray, "
"or LoDTensor, but the received var[%s] is %s.",
inside_grad_name, var->Type().name());
if (var->IsType<LoDTensor>()) {
auto &inside_tensor = var->Get<framework::LoDTensor>();
......
......@@ -20,8 +20,11 @@ limitations under the License. */
#include "paddle/fluid/platform/enforce.h"
DEFINE_double(fraction_of_gpu_memory_to_use, 0.92,
"Default use 92% of GPU memory for PaddlePaddle,"
"reserve the rest for page tables, etc");
"Allocate a trunk of gpu memory that is this fraction of the "
"total gpu memory size. Future memory usage will be allocated "
"from the trunk. If the trunk doesn't have enough gpu memory, "
"additional trunks of the same size will be requested from gpu "
"until the gpu has no memory left for another trunk.");
namespace paddle {
namespace platform {
......
......@@ -4,7 +4,6 @@ function(train_test TARGET_NAME)
set(multiValueArgs ARGS)
cmake_parse_arguments(train_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(PYTHON_TESTS_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/tests)
set(arg_list "")
if(train_test_ARGS)
foreach(arg ${train_test_ARGS})
......
......@@ -1570,6 +1570,10 @@ class DynamicRNN(object):
The dynamic RNN can mark multiple variables as its output. Use `drnn()` to
get the output sequence.
NOTES:
Currently it is not supported that setting is_sparse to True of any
layers within DynamicRNN.
"""
BEFORE_RNN = 0
IN_RNN = 1
......
set(PYTHON_TESTS_DIR ${CMAKE_CURRENT_BINARY_DIR} CACHE PATH "python tests directory")
file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
......
......@@ -124,7 +124,7 @@ class InferenceTranspiler(object):
next_op = self.block.ops[i + 1]
if next_op.type == 'relu':
# modify bnorm OP to include relu
current_op.set_attr("fuse_relu", True)
current_op._set_attr("fuse_relu", True)
# remove relu OP
self.block._remove_op(i + 1)
i = i + 1
......@@ -454,7 +454,7 @@ class InferenceTranspiler(object):
:type eltwise_op: Operator
'''
conv_op.set_attr("fuse_eltwise", True)
conv_op._set_attr("fuse_eltwise", True)
self.input_map[conv_op.output("Output")[0]] = eltwise_op.input("Y")[0]
self.input_map[eltwise_op.output("Out")[0]] = eltwise_op.input("Y")[0]
......
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