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@ -90,56 +90,44 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchema) {
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std::string schema_file = datasets_root_path_ + "/testAlbum/datasetSchema.json";
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std::vector<std::string> column_names = {"image", "label", "id"};
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auto tree = Build({AlbumSchema(16, 2, 32, folder_path, schema_file, column_names, false), Repeat(2)});
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tree->Prepare();
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << ".";
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EXPECT_TRUE(false);
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} else {
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(tree->Prepare());
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ASSERT_OK(tree->Launch());
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(di.GetNextAsMap(&tensor_map));
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uint64_t i = 0;
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std::string_view label = 0;
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while (tensor_map.size() != 0) {
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EXPECT_TRUE(tensor_map["label"]->GetItemAt(&label, {}));
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(rc.IsOk());
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uint64_t i = 0;
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int32_t label = 0;
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while (tensor_map.size() != 0) {
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tensor_map["label"]->GetItemAt<int32_t>(&label, {});
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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}
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MS_LOG(INFO) << "got rows" << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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MS_LOG(INFO) << "got rows: " << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchemaNoOrder) {
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std::string folder_path = datasets_root_path_ + "/testAlbum/images";
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std::string schema_file = datasets_root_path_ + "/testAlbum/datasetSchema.json";
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auto tree = Build({AlbumSchema(16, 2, 32, folder_path, schema_file), Repeat(2)});
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tree->Prepare();
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << ".";
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EXPECT_TRUE(false);
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} else {
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(tree->Prepare());
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ASSERT_OK(tree->Launch());
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_TRUE(di.GetNextAsMap(&tensor_map));
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uint64_t i = 0;
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std::string_view label;
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while (tensor_map.size() != 0) {
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EXPECT_OK(tensor_map["label"]->GetItemAt(&label, {}));
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(rc.IsOk());
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uint64_t i = 0;
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int32_t label = 0;
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while (tensor_map.size() != 0) {
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tensor_map["label"]->GetItemAt<int32_t>(&label, {});
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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}
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MS_LOG(INFO) << "got rows" << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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MS_LOG(INFO) << "got rows: " << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchemaFloat) {
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@ -148,29 +136,23 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchemaFloat) {
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std::string schema_file = datasets_root_path_ + "/testAlbum/floatSchema.json";
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auto tree = Build({AlbumSchema(16, 2, 32, folder_path, schema_file), Repeat(2)});
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tree->Prepare();
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << ".";
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EXPECT_TRUE(false);
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} else {
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(tree->Launch());
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(di.GetNextAsMap(&tensor_map));
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uint64_t i = 0;
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std::string_view label;
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double priority = 0;
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while (tensor_map.size() != 0) {
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EXPECT_OK(tensor_map["label"]->GetItemAt(&label, {}));
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EXPECT_OK(tensor_map["_priority"]->GetItemAt<double>(&priority, {}));
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "priority: " << priority << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(rc.IsOk());
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uint64_t i = 0;
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int32_t label = 0;
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double priority = 0;
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while (tensor_map.size() != 0) {
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tensor_map["label"]->GetItemAt<int32_t>(&label, {});
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tensor_map["_priority"]->GetItemAt<double>(&priority, {});
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "priority: " << priority << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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}
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MS_LOG(INFO) << "got rows" << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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MS_LOG(INFO) << "got rows: " << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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TEST_F(MindDataTestAlbum, TestSequentialAlbumWithFullSchema) {
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@ -178,32 +160,26 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithFullSchema) {
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// add the priority column
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std::string schema_file = datasets_root_path_ + "/testAlbum/fullSchema.json";
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auto tree = Build({AlbumSchema(16, 2, 32, folder_path, schema_file), Repeat(2)});
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tree->Prepare();
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Status rc = tree->Launch();
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if (rc.IsError()) {
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MS_LOG(ERROR) << "Return code error detected during tree launch: " << ".";
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EXPECT_TRUE(false);
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} else {
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(tree->Prepare());
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ASSERT_OK(tree->Launch());
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DatasetIterator di(tree);
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TensorMap tensor_map;
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ASSERT_OK(di.GetNextAsMap(&tensor_map));
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uint64_t i = 0;
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std::string_view label = 0;
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double priority = 0;
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int64_t id = 0;
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while (tensor_map.size() != 0) {
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EXPECT_OK(tensor_map["label"]->GetItemAt(&label, {}));
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EXPECT_OK(tensor_map["_priority"]->GetItemAt<double>(&priority, {}));
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EXPECT_OK(tensor_map["id"]->GetItemAt<int64_t>(&id, {}));
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MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "priority: " << priority << " embedding : "
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<< tensor_map["_embedding"]->shape() << " id: " << id << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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EXPECT_TRUE(rc.IsOk());
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uint64_t i = 0;
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int32_t label = 0;
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double priority = 0;
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int64_t id = 0;
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while (tensor_map.size() != 0) {
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tensor_map["label"]->GetItemAt<int32_t>(&label, {});
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tensor_map["_priority"]->GetItemAt<double>(&priority, {});
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tensor_map["id"]->GetItemAt<int64_t>(&id, {});
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MS_LOG(ERROR) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape"
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<< tensor_map["label"] << "priority: " << priority << " embedding : " <<
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tensor_map["_embedding"]->shape() << " id: " << id << "\n";
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i++;
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di.GetNextAsMap(&tensor_map);
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}
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MS_LOG(INFO) << "got rows" << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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MS_LOG(INFO) << "got rows: " << i << "\n";
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EXPECT_TRUE(i == 14);
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}
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