From ecae157edf352ad73c8e60a90ced540fe0e48ff3 Mon Sep 17 00:00:00 2001 From: Tao Luo Date: Wed, 26 Dec 2018 21:31:45 +0800 Subject: [PATCH] simplify some data record in analyzer_tester test=develop --- .../tests/api/analyzer_mm_dnn_tester.cc | 35 +++------- .../tests/api/analyzer_ner_tester.cc | 33 +++------- .../tests/api/analyzer_seq_conv1_tester.cc | 64 ++++--------------- .../fluid/inference/tests/api/tester_helper.h | 12 ++++ 4 files changed, 45 insertions(+), 99 deletions(-) diff --git a/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc b/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc index 98335fe4f88..9d3c7519430 100644 --- a/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc +++ b/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc @@ -19,11 +19,9 @@ namespace inference { using contrib::AnalysisConfig; struct DataRecord { - std::vector> query_data_all, title_data_all; + std::vector> query, title; std::vector lod1, lod2; - size_t batch_iter{0}; - size_t batch_size{1}; - size_t num_samples; // total number of samples + size_t batch_iter{0}, batch_size{1}, num_samples; // total number of samples DataRecord() = default; explicit DataRecord(const std::string &path, int batch_size = 1) : batch_size(batch_size) { @@ -33,22 +31,9 @@ struct DataRecord { DataRecord data; size_t batch_end = batch_iter + batch_size; // NOTE skip the final batch, if no enough data is provided. - if (batch_end <= query_data_all.size()) { - data.query_data_all.assign(query_data_all.begin() + batch_iter, - query_data_all.begin() + batch_end); - data.title_data_all.assign(title_data_all.begin() + batch_iter, - title_data_all.begin() + batch_end); - // Prepare LoDs - data.lod1.push_back(0); - data.lod2.push_back(0); - CHECK(!data.query_data_all.empty()); - CHECK(!data.title_data_all.empty()); - CHECK_EQ(data.query_data_all.size(), data.title_data_all.size()); - for (size_t j = 0; j < data.query_data_all.size(); j++) { - // calculate lod - data.lod1.push_back(data.lod1.back() + data.query_data_all[j].size()); - data.lod2.push_back(data.lod2.back() + data.title_data_all[j].size()); - } + if (batch_end <= query.size()) { + GetInputPerBatch(query, &data.query, &data.lod1, batch_iter, batch_end); + GetInputPerBatch(title, &data.title, &data.lod2, batch_iter, batch_end); } batch_iter += batch_size; return data; @@ -67,8 +52,8 @@ struct DataRecord { // load title data std::vector title_data; split_to_int64(data[1], ' ', &title_data); - query_data_all.push_back(std::move(query_data)); - title_data_all.push_back(std::move(title_data)); + query.push_back(std::move(query_data)); + title.push_back(std::move(title_data)); } num_samples = num_lines; } @@ -81,10 +66,8 @@ void PrepareInputs(std::vector *input_slots, DataRecord *data, lod_title_tensor.name = "right"; auto one_batch = data->NextBatch(); // assign data - TensorAssignData(&lod_query_tensor, one_batch.query_data_all, - one_batch.lod1); - TensorAssignData(&lod_title_tensor, one_batch.title_data_all, - one_batch.lod2); + TensorAssignData(&lod_query_tensor, one_batch.query, one_batch.lod1); + TensorAssignData(&lod_title_tensor, one_batch.title, one_batch.lod2); // Set inputs. input_slots->assign({lod_query_tensor, lod_title_tensor}); for (auto &tensor : *input_slots) { diff --git a/paddle/fluid/inference/tests/api/analyzer_ner_tester.cc b/paddle/fluid/inference/tests/api/analyzer_ner_tester.cc index 54298fdab28..f8635968ceb 100644 --- a/paddle/fluid/inference/tests/api/analyzer_ner_tester.cc +++ b/paddle/fluid/inference/tests/api/analyzer_ner_tester.cc @@ -19,11 +19,9 @@ namespace inference { using contrib::AnalysisConfig; struct DataRecord { - std::vector> word_data_all, mention_data_all; + std::vector> word, mention; std::vector lod; // two inputs have the same lod info. - size_t batch_iter{0}; - size_t batch_size{1}; - size_t num_samples; // total number of samples + size_t batch_iter{0}, batch_size{1}, num_samples; // total number of samples DataRecord() = default; explicit DataRecord(const std::string &path, int batch_size = 1) : batch_size(batch_size) { @@ -33,20 +31,10 @@ struct DataRecord { DataRecord data; size_t batch_end = batch_iter + batch_size; // NOTE skip the final batch, if no enough data is provided. - if (batch_end <= word_data_all.size()) { - data.word_data_all.assign(word_data_all.begin() + batch_iter, - word_data_all.begin() + batch_end); - data.mention_data_all.assign(mention_data_all.begin() + batch_iter, - mention_data_all.begin() + batch_end); - // Prepare LoDs - data.lod.push_back(0); - CHECK(!data.word_data_all.empty()); - CHECK(!data.mention_data_all.empty()); - CHECK_EQ(data.word_data_all.size(), data.mention_data_all.size()); - for (size_t j = 0; j < data.word_data_all.size(); j++) { - // calculate lod - data.lod.push_back(data.lod.back() + data.word_data_all[j].size()); - } + if (batch_end <= word.size()) { + GetInputPerBatch(word, &data.word, &data.lod, batch_iter, batch_end); + GetInputPerBatch(mention, &data.mention, &data.lod, batch_iter, + batch_end); } batch_iter += batch_size; return data; @@ -65,8 +53,8 @@ struct DataRecord { // load mention data std::vector mention_data; split_to_int64(data[3], ' ', &mention_data); - word_data_all.push_back(std::move(word_data)); - mention_data_all.push_back(std::move(mention_data)); + word.push_back(std::move(word_data)); + mention.push_back(std::move(mention_data)); } num_samples = num_lines; } @@ -79,9 +67,8 @@ void PrepareInputs(std::vector *input_slots, DataRecord *data, lod_mention_tensor.name = "mention"; auto one_batch = data->NextBatch(); // assign data - TensorAssignData(&lod_word_tensor, one_batch.word_data_all, - one_batch.lod); - TensorAssignData(&lod_mention_tensor, one_batch.mention_data_all, + TensorAssignData(&lod_word_tensor, one_batch.word, one_batch.lod); + TensorAssignData(&lod_mention_tensor, one_batch.mention, one_batch.lod); // Set inputs. input_slots->assign({lod_word_tensor, lod_mention_tensor}); diff --git a/paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc b/paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc index 49f6059715d..e6d6cd2960b 100644 --- a/paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc +++ b/paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc @@ -18,12 +18,9 @@ namespace paddle { namespace inference { struct DataRecord { - std::vector> title1_all, title2_all, title3_all, l1_all; std::vector> title1, title2, title3, l1; - std::vector title1_lod, title2_lod, title3_lod, l1_lod; - size_t batch_iter{0}; - size_t batch_size{1}; - size_t num_samples; // total number of samples + std::vector lod1, lod2, lod3, l1_lod; + size_t batch_iter{0}, batch_size{1}, num_samples; // total number of samples DataRecord() = default; explicit DataRecord(const std::string &path, int batch_size = 1) : batch_size(batch_size) { @@ -33,41 +30,11 @@ struct DataRecord { DataRecord data; size_t batch_end = batch_iter + batch_size; // NOTE skip the final batch, if no enough data is provided. - if (batch_end <= title1_all.size()) { - data.title1_all.assign(title1_all.begin() + batch_iter, - title1_all.begin() + batch_end); - data.title2_all.assign(title2_all.begin() + batch_iter, - title2_all.begin() + batch_end); - data.title3_all.assign(title3_all.begin() + batch_iter, - title3_all.begin() + batch_end); - data.l1_all.assign(l1_all.begin() + batch_iter, - l1_all.begin() + batch_end); - // Prepare LoDs - data.title1_lod.push_back(0); - data.title2_lod.push_back(0); - data.title3_lod.push_back(0); - data.l1_lod.push_back(0); - CHECK(!data.title1_all.empty()); - CHECK(!data.title2_all.empty()); - CHECK(!data.title3_all.empty()); - CHECK(!data.l1_all.empty()); - CHECK_EQ(data.title1_all.size(), data.title2_all.size()); - CHECK_EQ(data.title1_all.size(), data.title3_all.size()); - CHECK_EQ(data.title1_all.size(), data.l1_all.size()); - for (size_t j = 0; j < data.title1_all.size(); j++) { - data.title1.push_back(data.title1_all[j]); - data.title2.push_back(data.title2_all[j]); - data.title3.push_back(data.title3_all[j]); - data.l1.push_back(data.l1_all[j]); - // calculate lod - data.title1_lod.push_back(data.title1_lod.back() + - data.title1_all[j].size()); - data.title2_lod.push_back(data.title2_lod.back() + - data.title2_all[j].size()); - data.title3_lod.push_back(data.title3_lod.back() + - data.title3_all[j].size()); - data.l1_lod.push_back(data.l1_lod.back() + data.l1_all[j].size()); - } + if (batch_end <= title1.size()) { + GetInputPerBatch(title1, &data.title1, &data.lod1, batch_iter, batch_end); + GetInputPerBatch(title2, &data.title2, &data.lod2, batch_iter, batch_end); + GetInputPerBatch(title3, &data.title3, &data.lod3, batch_iter, batch_end); + GetInputPerBatch(l1, &data.l1, &data.l1_lod, batch_iter, batch_end); } batch_iter += batch_size; return data; @@ -92,10 +59,10 @@ struct DataRecord { // load l1 data std::vector l1_data; split_to_int64(data[3], ' ', &l1_data); - title1_all.push_back(std::move(title1_data)); - title2_all.push_back(std::move(title2_data)); - title3_all.push_back(std::move(title3_data)); - l1_all.push_back(std::move(l1_data)); + title1.push_back(std::move(title1_data)); + title2.push_back(std::move(title2_data)); + title3.push_back(std::move(title3_data)); + l1.push_back(std::move(l1_data)); } num_samples = num_lines; } @@ -110,12 +77,9 @@ void PrepareInputs(std::vector *input_slots, DataRecord *data, l1_tensor.name = "l1"; auto one_batch = data->NextBatch(); // assign data - TensorAssignData(&title1_tensor, one_batch.title1, - one_batch.title1_lod); - TensorAssignData(&title2_tensor, one_batch.title2, - one_batch.title2_lod); - TensorAssignData(&title3_tensor, one_batch.title3, - one_batch.title3_lod); + TensorAssignData(&title1_tensor, one_batch.title1, one_batch.lod1); + TensorAssignData(&title2_tensor, one_batch.title2, one_batch.lod2); + TensorAssignData(&title3_tensor, one_batch.title3, one_batch.lod3); TensorAssignData(&l1_tensor, one_batch.l1, one_batch.l1_lod); // Set inputs. input_slots->assign({title1_tensor, title2_tensor, title3_tensor, l1_tensor}); diff --git a/paddle/fluid/inference/tests/api/tester_helper.h b/paddle/fluid/inference/tests/api/tester_helper.h index b0c8f395ce0..144027589cc 100644 --- a/paddle/fluid/inference/tests/api/tester_helper.h +++ b/paddle/fluid/inference/tests/api/tester_helper.h @@ -169,6 +169,18 @@ void SetFakeImageInput(std::vector> *inputs, (*inputs).emplace_back(input_slots); } +void GetInputPerBatch(const std::vector> &in, + std::vector> *out, + std::vector *lod, size_t batch_iter, + size_t batch_end) { + lod->clear(); + lod->push_back(0); + for (auto it = in.begin() + batch_iter; it < in.begin() + batch_end; it++) { + out->push_back(*it); + lod->push_back(lod->back() + (*it).size()); // calculate lod + } +} + void TestOneThreadPrediction( const PaddlePredictor::Config *config, const std::vector> &inputs, -- GitLab