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Merge pull request #13909 from luotao1/mkldnn_test

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refine mkldnn test in analyzer_tests
ce
Tao Luo 7 years ago committed by GitHub
parent 081fd41f05 e5b4643ad8
commit 305034f5b3
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GPG Key ID: 4AEE18F83AFDEB23
10 changed files with 40 additions and 16 deletions
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2
paddle/fluid/framework/ir/attention_lstm_fuse_pass.cc
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@ -262,7 +262,7 @@ std::unique_ptr<ir::Graph> AttentionLSTMFusePass::ApplyImpl(
std::unordered_set<std::string> specified_vars({"data_lod_attention",
"cell_init", "hidden_init",
"data", "week", "minute"});
int count = 0;
size_t count = 0;
for (auto* node : graph->Nodes()) {
if (node->IsVar() && specified_vars.count(node->Name())) {
++count;

4
paddle/fluid/framework/program_desc.cc
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@ -126,7 +126,7 @@ const std::vector<std::string> ProgramDesc::GetFeedTargetNames() {
std::vector<std::string> feed_target_names;
for (auto *op : global_block.AllOps()) {
if (op->Type() == kFeedOpType) {
int col = boost::get<int>(op->GetAttr("col"));
size_t col = boost::get<int>(op->GetAttr("col"));
if (col >= feed_target_names.size()) {
feed_target_names.resize(col + 1);
}
@ -143,7 +143,7 @@ const std::vector<std::string> ProgramDesc::GetFetchTargetNames() {
std::vector<std::string> fetch_target_names;
for (auto *op : global_block.AllOps()) {
if (op->Type() == kFetchOpType) {
int col = boost::get<int>(op->GetAttr("col"));
size_t col = boost::get<int>(op->GetAttr("col"));
if (col >= fetch_target_names.size()) {
fetch_target_names.resize(col + 1);
}

2
paddle/fluid/framework/reader_test.cc
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@ -39,7 +39,7 @@ TEST(READER, decorate_chain) {
{
auto endpoints = root->GetEndPoints();
ASSERT_EQ(endpoints.size(), 2U);
ASSERT_NE(endpoints.count(end_point1.get()), 0);
ASSERT_NE(endpoints.count(end_point1.get()), 0UL);
ASSERT_NE(endpoints.count(end_point2.get()), 0);
}

2
paddle/fluid/framework/selected_rows_test.cc
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@ -91,7 +91,7 @@ TEST(SelectedRows, SparseTable) {
ASSERT_TRUE(table.HasKey(10));
ASSERT_TRUE(table.HasKey(8));
ASSERT_TRUE(table.HasKey(6));
ASSERT_EQ(table.rows().size(), 3);
ASSERT_EQ(table.rows().size(), 3UL);
framework::Tensor ids;
ids.Resize(framework::make_ddim({4}));

16
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
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@ -52,9 +52,10 @@ void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
}
// Easy for profiling independently.
TEST(Analyzer_resnet50, profile) {
void profile(bool use_mkldnn = false) {
AnalysisConfig cfg;
SetConfig(&cfg);
cfg._use_mkldnn = use_mkldnn;
std::vector<PaddleTensor> outputs;
std::vector<std::vector<PaddleTensor>> input_slots_all;
@ -69,6 +70,11 @@ TEST(Analyzer_resnet50, profile) {
}
}
TEST(Analyzer_resnet50, profile) { profile(); }
#ifndef PADDLE_WITH_MKLDNN
TEST(Analyzer_resnet50, profile_mkldnn) { profile(true /* use_mkldnn */); }
#endif
// Check the fuse status
TEST(Analyzer_resnet50, fuse_statis) {
AnalysisConfig cfg;
@ -82,15 +88,21 @@ TEST(Analyzer_resnet50, fuse_statis) {
}
// Compare result of NativeConfig and AnalysisConfig
TEST(Analyzer_resnet50, compare) {
void compare(bool use_mkldnn = false) {
AnalysisConfig cfg;
SetConfig(&cfg);
cfg._use_mkldnn = use_mkldnn;
std::vector<std::vector<PaddleTensor>> input_slots_all;
SetInput(&input_slots_all);
CompareNativeAndAnalysis(cfg, input_slots_all);
}
TEST(Analyzer_resnet50, compare) { compare(); }
#ifdef PADDLE_WITH_MKLDNN
TEST(Analyzer_resnet50, compare_mkldnn) { compare(true /* use_mkldnn */); }
#endif
} // namespace analysis
} // namespace inference
} // namespace paddle

20
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
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@ -59,9 +59,6 @@ void SetConfig(AnalysisConfig *cfg) {
cfg->specify_input_name = true;
// TODO(TJ): fix fusion gru
cfg->ir_passes.push_back("fc_gru_fuse_pass");
#ifdef PADDLE_WITH_MKLDNN
cfg->_use_mkldnn = true;
#endif
}
void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
@ -84,9 +81,10 @@ void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
// Easy for profiling independently.
// ocr, mobilenet and se_resnext50
TEST(Analyzer_vis, profile) {
void profile(bool use_mkldnn = false) {
AnalysisConfig cfg;
SetConfig(&cfg);
cfg._use_mkldnn = use_mkldnn;
std::vector<PaddleTensor> outputs;
std::vector<std::vector<PaddleTensor>> input_slots_all;
@ -108,6 +106,12 @@ TEST(Analyzer_vis, profile) {
}
}
TEST(Analyzer_vis, profile) { profile(); }
#ifdef PADDLE_WITH_MKLDNN
TEST(Analyzer_vis, profile_mkldnn) { profile(true /* use_mkldnn */); }
#endif
// Check the fuse status
TEST(Analyzer_vis, fuse_statis) {
AnalysisConfig cfg;
@ -118,15 +122,21 @@ TEST(Analyzer_vis, fuse_statis) {
}
// Compare result of NativeConfig and AnalysisConfig
TEST(Analyzer_vis, compare) {
void compare(bool use_mkldnn = false) {
AnalysisConfig cfg;
SetConfig(&cfg);
cfg._use_mkldnn = use_mkldnn;
std::vector<std::vector<PaddleTensor>> input_slots_all;
SetInput(&input_slots_all);
CompareNativeAndAnalysis(cfg, input_slots_all);
}
TEST(Analyzer_vis, compare) { compare(); }
#ifdef PADDLE_WITH_MKLDNN
TEST(Analyzer_vis, compare_mkldnn) { compare(true /* use_mkldnn */); }
#endif
} // namespace analysis
} // namespace inference
} // namespace paddle

4
paddle/fluid/inference/tests/api/tester_helper.h
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@ -163,7 +163,8 @@ void TestPrediction(const AnalysisConfig &config,
const std::vector<std::vector<PaddleTensor>> &inputs,
std::vector<PaddleTensor> *outputs, int num_threads,
bool use_analysis = FLAGS_use_analysis) {
LOG(INFO) << "use_analysis: " << use_analysis;
LOG(INFO) << "use_analysis: " << use_analysis
<< ", use_mkldnn: " << config._use_mkldnn;
if (num_threads == 1) {
TestOneThreadPrediction(config, inputs, outputs, use_analysis);
} else {
@ -175,6 +176,7 @@ void TestPrediction(const AnalysisConfig &config,
void CompareNativeAndAnalysis(
const AnalysisConfig &config,
const std::vector<std::vector<PaddleTensor>> &inputs) {
LOG(INFO) << "use_mkldnn: " << config._use_mkldnn;
std::vector<PaddleTensor> native_outputs, analysis_outputs;
TestOneThreadPrediction(config, inputs, &native_outputs, false);
TestOneThreadPrediction(config, inputs, &analysis_outputs, true);

2
paddle/fluid/operators/reader/reader_blocking_queue_test.cc
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@ -229,7 +229,7 @@ TEST(BlockingQueue, speed_test_mode) {
q1.Receive(&b);
EXPECT_EQ(b, i);
}
EXPECT_EQ(q1.Size(), 0);
EXPECT_EQ(q1.Size(), 0UL);
BlockingQueue<size_t> q2(queue_size, true);
for (size_t i = 0; i < queue_size; ++i) {

2
paddle/fluid/operators/sequence_unpad_op.cc
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@ -50,7 +50,7 @@ class SequenceUnpadOp : public framework::OperatorWithKernel {
if (x_dims.size() == 2) {
out_dims_vec.push_back(1);
} else {
for (size_t i = 2; i < x_dims.size(); ++i) {
for (int i = 2; i < x_dims.size(); ++i) {
out_dims_vec.push_back(x_dims[i]);
}
}

2
paddle/fluid/operators/sequence_unpad_op.h
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@ -61,7 +61,7 @@ class SequenceUnpadOpKernel : public framework::OpKernel<T> {
if (x_t->dims().size() == 2) {
out_dims_vec.push_back(1);
} else {
for (size_t i = 2; i < x_t->dims().size(); ++i) {
for (int i = 2; i < x_t->dims().size(); ++i) {
out_dims_vec.push_back(x_t->dims()[i]);
}
}

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