| @@ -96,7 +96,7 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchema) { | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape" | |||
| << tensor_map["label"] << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| MS_LOG(INFO) << "got rows: " << i << "\n"; | |||
| EXPECT_TRUE(i == 14); | |||
| @@ -114,7 +114,7 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchemaNoOrder) { | |||
| ASSERT_OK(tree->Launch()); | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| ASSERT_TRUE(di.GetNextAsMap(&tensor_map)); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| uint64_t i = 0; | |||
| std::string_view label; | |||
| while (tensor_map.size() != 0) { | |||
| @@ -122,7 +122,7 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchemaNoOrder) { | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape" | |||
| << tensor_map["label"] << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| MS_LOG(INFO) << "got rows: " << i << "\n"; | |||
| EXPECT_TRUE(i == 14); | |||
| @@ -151,7 +151,7 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithSchemaFloat) { | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "label shape" | |||
| << tensor_map["label"] << "priority: " << priority << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| MS_LOG(INFO) << "got rows: " << i << "\n"; | |||
| EXPECT_TRUE(i == 14); | |||
| @@ -183,7 +183,7 @@ TEST_F(MindDataTestAlbum, TestSequentialAlbumWithFullSchema) { | |||
| << tensor_map["label"] << "priority: " << priority | |||
| << " embedding : " << tensor_map["_embedding"]->shape() << " id: " << id << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| MS_LOG(INFO) << "got rows: " << i << "\n"; | |||
| EXPECT_TRUE(i == 14); | |||
| @@ -100,14 +100,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheImageFolderCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -143,14 +143,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheCocoCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 12); | |||
| @@ -184,14 +184,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheMnistCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -226,14 +226,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheCelebaCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 8); | |||
| @@ -267,14 +267,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheManifestCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -308,14 +308,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheCifar10CApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -349,14 +349,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheCifar100CApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -391,14 +391,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheVocCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 18); | |||
| @@ -435,12 +435,12 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheAlbumCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 14); | |||
| @@ -460,8 +460,8 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheRandomDataCApi) { | |||
| // Create a RandomDataset | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2}); | |||
| schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1}); | |||
| ASSERT_OK(schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2})); | |||
| ASSERT_OK(schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(8, schema, {}, some_cache); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -477,12 +477,12 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheRandomDataCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 16); | |||
| @@ -518,14 +518,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheTFRecordCApi1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 6); | |||
| @@ -569,14 +569,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheTFRecordCApi2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -616,14 +616,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheTFRecordCApi3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -661,12 +661,12 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheTextfileCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -705,12 +705,12 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheCsvCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -750,12 +750,12 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCacheClueCApi) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -784,14 +784,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCApiCacheShare1) { | |||
| EXPECT_NE(iter1, nullptr); | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter1->GetNextRow(&row); | |||
| ASSERT_OK(iter1->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter1->GetNextRow(&row); | |||
| ASSERT_OK(iter1->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| // Manually terminate the pipeline | |||
| @@ -801,14 +801,14 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCApiCacheShare1) { | |||
| std::shared_ptr<Iterator> iter2 = ds2->CreateIterator(); | |||
| EXPECT_NE(iter2, nullptr); | |||
| // Iterate the dataset and get each row | |||
| iter2->GetNextRow(&row); | |||
| ASSERT_OK(iter2->GetNextRow(&row)); | |||
| i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter2->GetNextRow(&row); | |||
| ASSERT_OK(iter2->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -839,13 +839,13 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCApiCacheShare2) { | |||
| EXPECT_NE(iter1, nullptr); | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter1->GetNextRow(&row); | |||
| ASSERT_OK(iter1->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| iter1->GetNextRow(&row); | |||
| ASSERT_OK(iter1->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| // Manually terminate the pipeline | |||
| @@ -855,13 +855,13 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCApiCacheShare2) { | |||
| std::shared_ptr<Iterator> iter2 = ds2->CreateIterator(); | |||
| EXPECT_NE(iter2, nullptr); | |||
| // Iterate the dataset and get each row | |||
| iter2->GetNextRow(&row); | |||
| ASSERT_OK(iter2->GetNextRow(&row)); | |||
| i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| iter2->GetNextRow(&row); | |||
| ASSERT_OK(iter2->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -889,13 +889,13 @@ TEST_F(MindDataTestCacheOp, DISABLED_TestCApiCacheShareFailure1) { | |||
| EXPECT_NE(iter1, nullptr); | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter1->GetNextRow(&row); | |||
| ASSERT_OK(iter1->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| iter1->GetNextRow(&row); | |||
| ASSERT_OK(iter1->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| // Manually terminate the pipeline | |||
| @@ -40,14 +40,14 @@ TEST_F(MindDataTestPipeline, TestAlbumBasic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 7); | |||
| @@ -95,14 +95,14 @@ TEST_F(MindDataTestPipeline, TestAlbumBasicWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 35); | |||
| @@ -155,7 +155,7 @@ TEST_F(MindDataTestPipeline, TestAlbumDecode) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -165,7 +165,7 @@ TEST_F(MindDataTestPipeline, TestAlbumDecode) { | |||
| MS_LOG(INFO) << "Tensor image shape size: " << shape.size(); | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_GT(shape.size(), 1); // Verify decode=true took effect | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 7); | |||
| @@ -191,14 +191,14 @@ TEST_F(MindDataTestPipeline, TestAlbumNumSamplers) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 1); | |||
| @@ -41,7 +41,7 @@ TEST_F(MindDataTestPipeline, TestCifar10Dataset) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("image"), row.end()); | |||
| EXPECT_NE(row.find("label"), row.end()); | |||
| @@ -51,7 +51,7 @@ TEST_F(MindDataTestPipeline, TestCifar10Dataset) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -96,7 +96,7 @@ TEST_F(MindDataTestPipeline, TestCifar10DatasetWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("image"), row.end()); | |||
| EXPECT_NE(row.find("label"), row.end()); | |||
| @@ -106,7 +106,7 @@ TEST_F(MindDataTestPipeline, TestCifar10DatasetWithPipeline) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -179,7 +179,7 @@ TEST_F(MindDataTestPipeline, TestCifar100Dataset) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("image"), row.end()); | |||
| EXPECT_NE(row.find("coarse_label"), row.end()); | |||
| @@ -190,7 +190,7 @@ TEST_F(MindDataTestPipeline, TestCifar100Dataset) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -45,7 +45,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetAFQMC) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| std::vector<std::string> expected_result = {"蚂蚁借呗等额还款能否换成先息后本", "蚂蚁花呗说我违约了", | |||
| @@ -57,11 +57,11 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetAFQMC) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -78,7 +78,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetAFQMC) { | |||
| EXPECT_NE(ds, nullptr); | |||
| iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -86,10 +86,10 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetAFQMC) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| iter->Stop(); | |||
| @@ -101,7 +101,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetAFQMC) { | |||
| EXPECT_NE(ds, nullptr); | |||
| iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -109,10 +109,10 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetAFQMC) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| iter->Stop(); | |||
| @@ -135,7 +135,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetBasic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| uint64_t i = 0; | |||
| @@ -143,7 +143,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetBasic) { | |||
| auto text = row["sentence1"]; | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 samples | |||
| @@ -191,7 +191,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetBasicWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| uint64_t i = 0; | |||
| @@ -199,7 +199,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetBasicWithPipeline) { | |||
| auto text = row["sentence1"]; | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 10 samples | |||
| @@ -241,7 +241,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetCMNLI) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| std::vector<std::string> expected_result = {"你应该给这件衣服定一个价格。", "我怎么知道他要说什么", "向左。"}; | |||
| @@ -252,11 +252,11 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetCMNLI) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -284,7 +284,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetCSL) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("abst"), row.end()); | |||
| std::vector<std::string> expected_result = {"这是一段长文本", "这是一段长文本", "这是一段长文本"}; | |||
| @@ -295,11 +295,11 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetCSL) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -327,7 +327,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetDistribution) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| uint64_t i = 0; | |||
| @@ -335,7 +335,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetDistribution) { | |||
| auto text = row["sentence1"]; | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 1 samples | |||
| @@ -427,7 +427,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetIFLYTEK) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence"), row.end()); | |||
| std::vector<std::string> expected_result = {"第一个文本", "第二个文本", "第三个文本"}; | |||
| @@ -438,11 +438,11 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetIFLYTEK) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -484,7 +484,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetShuffleFilesA) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| std::vector<std::string> expected_result = {"你有花呗吗", | |||
| @@ -500,13 +500,13 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetShuffleFilesA) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 3 + 3 = 6 samples | |||
| @@ -551,7 +551,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetShuffleFilesB) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| std::vector<std::string> expected_result = {"你有花呗吗", | |||
| @@ -567,12 +567,12 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetShuffleFilesB) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 3 + 3 = 6 samples | |||
| @@ -611,7 +611,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetShuffleGlobal) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence1"), row.end()); | |||
| std::vector<std::string> expected_result = {"蚂蚁花呗说我违约了", "帮我看看本月花呗账单结清了没", | |||
| @@ -622,12 +622,12 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetShuffleGlobal) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 3 samples | |||
| @@ -658,7 +658,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetTNEWS) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("sentence"), row.end()); | |||
| std::vector<std::string> expected_result = {"新闻1", "新闻2", "新闻3"}; | |||
| @@ -669,11 +669,11 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetTNEWS) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -701,7 +701,7 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetWSC) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"小明呢,他在哪?", "小红刚刚看到小明,他在操场", | |||
| @@ -713,11 +713,11 @@ TEST_F(MindDataTestPipeline, TestCLUEDatasetWSC) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -41,7 +41,7 @@ TEST_F(MindDataTestPipeline, TestCocoDefault) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -51,7 +51,7 @@ TEST_F(MindDataTestPipeline, TestCocoDefault) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Tensor bbox shape: " << bbox.Shape(); | |||
| MS_LOG(INFO) << "Tensor category_id shape: " << category_id.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -98,7 +98,7 @@ TEST_F(MindDataTestPipeline, TestCocoDefaultWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -108,7 +108,7 @@ TEST_F(MindDataTestPipeline, TestCocoDefaultWithPipeline) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Tensor bbox shape: " << bbox.Shape(); | |||
| MS_LOG(INFO) << "Tensor category_id shape: " << category_id.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -149,7 +149,7 @@ TEST_F(MindDataTestPipeline, TestCocoDetection) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::string expect_file[] = {"000000391895", "000000318219", "000000554625", | |||
| "000000574769", "000000060623", "000000309022"}; | |||
| @@ -182,7 +182,7 @@ TEST_F(MindDataTestPipeline, TestCocoDetection) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_categoryid)); | |||
| EXPECT_MSTENSOR_EQ(category_id, expect_categoryid); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -239,7 +239,7 @@ TEST_F(MindDataTestPipeline, TestCocoKeypoint) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::string expect_file[] = {"000000391895", "000000318219"}; | |||
| std::vector<std::vector<float>> expect_keypoint_vector = { | |||
| @@ -274,7 +274,7 @@ TEST_F(MindDataTestPipeline, TestCocoKeypoint) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_num_keypoints)); | |||
| EXPECT_MSTENSOR_EQ(num_keypoints, expect_num_keypoints); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -301,7 +301,7 @@ TEST_F(MindDataTestPipeline, TestCocoPanoptic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::string expect_file[] = {"000000391895", "000000574769"}; | |||
| std::vector<std::vector<float>> expect_bbox_vector = {{472, 173, 36, 48, 340, 22, 154, 301, 486, 183, 30, 35}, | |||
| @@ -346,7 +346,7 @@ TEST_F(MindDataTestPipeline, TestCocoPanoptic) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_area)); | |||
| EXPECT_MSTENSOR_EQ(area, expect_area); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -396,7 +396,7 @@ TEST_F(MindDataTestPipeline, TestCocoStuff) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::string expect_file[] = {"000000391895", "000000318219", "000000554625", | |||
| "000000574769", "000000060623", "000000309022"}; | |||
| @@ -424,7 +424,7 @@ TEST_F(MindDataTestPipeline, TestCocoStuff) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_segmentation)); | |||
| EXPECT_MSTENSOR_EQ(segmentation, expect_segmentation); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -129,7 +129,7 @@ TEST_F(MindDataTestPipeline, TestShuffleWithSeed) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"Good luck to everyone.", "Be happy every day.", "This is a text file."}; | |||
| @@ -141,14 +141,14 @@ TEST_F(MindDataTestPipeline, TestShuffleWithSeed) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 3 samples | |||
| @@ -194,7 +194,7 @@ TEST_F(MindDataTestPipeline, TestCallShuffleTwice) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> first_copy; | |||
| @@ -206,7 +206,7 @@ TEST_F(MindDataTestPipeline, TestCallShuffleTwice) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| @@ -218,7 +218,7 @@ TEST_F(MindDataTestPipeline, TestCallShuffleTwice) { | |||
| } | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 6 samples | |||
| @@ -42,7 +42,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetBasic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = { | |||
| {"1", "2", "3", "4"}, | |||
| @@ -57,11 +57,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetBasic) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -109,7 +109,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetMultiFiles) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = { | |||
| {"17", "18", "19", "20"}, {"1", "2", "3", "4"}, {"5", "6", "7", "8"}, | |||
| @@ -123,11 +123,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetMultiFiles) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -158,7 +158,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetNumSamples) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = {{"1", "2", "3", "4"}, {"5", "6", "7", "8"}}; | |||
| @@ -169,11 +169,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetNumSamples) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -200,7 +200,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetDistribution) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = {{"1", "2", "3", "4"}, {"5", "6", "7", "8"}}; | |||
| @@ -211,11 +211,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetDistribution) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -248,7 +248,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetType) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::shared_ptr<CsvBase>>> expected = { | |||
| { | |||
| std::make_shared<CsvRecord<std::string>>(CsvType::STRING, ""), | |||
| @@ -273,20 +273,20 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetType) { | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| if (colum_type[j]->type == CsvType::INT) { | |||
| int val; | |||
| de_text->GetItemAt(&val, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&val, {})); | |||
| EXPECT_EQ(val, std::dynamic_pointer_cast<CsvRecord<int>>(expected[i][j])->value); | |||
| } else if (colum_type[j]->type == CsvType::FLOAT) { | |||
| float val; | |||
| de_text->GetItemAt(&val, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&val, {})); | |||
| EXPECT_EQ(val, std::dynamic_pointer_cast<CsvRecord<float>>(expected[i][j])->value); | |||
| } else if (colum_type[j]->type == CsvType::STRING) { | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), std::dynamic_pointer_cast<CsvRecord<std::string>>(expected[i][j])->value.c_str()); | |||
| } | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -312,7 +312,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetHeader) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = { | |||
| {"a", "b", "c", "d"}, | |||
| @@ -326,11 +326,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetHeader) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -421,7 +421,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleFilesA) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = { | |||
| {"13", "14", "15", "16"}, {"1", "2", "3", "4"}, {"17", "18", "19", "20"}, | |||
| @@ -435,11 +435,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleFilesA) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -478,7 +478,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleFilesB) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = { | |||
| {"13", "14", "15", "16"}, {"1", "2", "3", "4"}, {"17", "18", "19", "20"}, | |||
| @@ -492,12 +492,12 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleFilesB) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -536,7 +536,7 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleGlobal) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| std::vector<std::vector<std::string>> expected_result = { | |||
| {"5", "6", "7", "8"}, {"9", "10", "11", "12"}, {"1", "2", "3", "4"}}; | |||
| @@ -548,11 +548,11 @@ TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleGlobal) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -39,7 +39,7 @@ TEST_F(MindDataTestPipeline, TestIteratorEmptyColumn) { | |||
| // Iterate the dataset and get each row | |||
| std::vector<mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expect_image = {32, 32, 3}; | |||
| std::vector<int64_t> expect_label = {}; | |||
| @@ -49,7 +49,7 @@ TEST_F(MindDataTestPipeline, TestIteratorEmptyColumn) { | |||
| EXPECT_EQ(expect_image, row[0].Shape()); | |||
| EXPECT_EQ(expect_label, row[1].Shape()); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -79,7 +79,7 @@ TEST_F(MindDataTestPipeline, TestIteratorOneColumn) { | |||
| // Iterate the dataset and get each row | |||
| std::vector<mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expect_image = {2, 28, 28, 1}; | |||
| uint64_t i = 0; | |||
| @@ -88,7 +88,7 @@ TEST_F(MindDataTestPipeline, TestIteratorOneColumn) { | |||
| MS_LOG(INFO) << "image shape:" << v.Shape(); | |||
| EXPECT_EQ(expect_image, v.Shape()); | |||
| } | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -117,7 +117,7 @@ TEST_F(MindDataTestPipeline, TestIteratorReOrder) { | |||
| // Iterate the dataset and get each row | |||
| std::vector<mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expect_image = {32, 32, 3}; | |||
| std::vector<int64_t> expect_label = {}; | |||
| @@ -127,7 +127,7 @@ TEST_F(MindDataTestPipeline, TestIteratorReOrder) { | |||
| MS_LOG(INFO) << "row[0]:" << row[0].Shape() << ", row[1]:" << row[1].Shape(); | |||
| EXPECT_EQ(expect_label, row[0].Shape()); | |||
| EXPECT_EQ(expect_image, row[1].Shape()); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -158,7 +158,7 @@ TEST_F(MindDataTestPipeline, TestIteratorTwoColumns) { | |||
| // Iterate the dataset and get each row | |||
| std::vector<mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<int64_t>> expect = {{173673}, {1, 4}, {173673}, {1, 4}, | |||
| {147025}, {1, 4}, {211653}, {1, 4}}; | |||
| @@ -169,7 +169,7 @@ TEST_F(MindDataTestPipeline, TestIteratorTwoColumns) { | |||
| EXPECT_EQ(2, row.size()); | |||
| EXPECT_EQ(expect[j++], row[0].Shape()); | |||
| EXPECT_EQ(expect[j++], row[1].Shape()); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| j = (j == expect.size()) ? 0 : j; | |||
| } | |||
| @@ -209,10 +209,10 @@ TEST_F(MindDataTestPipeline, TestIteratorNumEpoch) { | |||
| int32_t inner_row_cnt = 0; | |||
| int32_t total_row_cnt = 0; | |||
| for (int32_t i = 0; i < num_epochs; i++) { | |||
| ASSERT_TRUE(iter->GetNextRow(&row)); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| inner_row_cnt = 0; | |||
| while (row.size() != 0) { | |||
| ASSERT_TRUE(iter->GetNextRow(&row)); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| ++inner_row_cnt; | |||
| ++total_row_cnt; | |||
| } | |||
| @@ -38,14 +38,14 @@ TEST_F(MindDataTestPipeline, TestManifestBasic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -90,14 +90,14 @@ TEST_F(MindDataTestPipeline, TestManifestBasicWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -157,7 +157,7 @@ TEST_F(MindDataTestPipeline, TestManifestDecode) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -167,7 +167,7 @@ TEST_F(MindDataTestPipeline, TestManifestDecode) { | |||
| MS_LOG(INFO) << "Tensor image shape size: " << shape.size(); | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_GT(shape.size(), 1); // Verify decode=true took effect | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -191,14 +191,14 @@ TEST_F(MindDataTestPipeline, TestManifestEval) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 1); | |||
| @@ -235,7 +235,7 @@ TEST_F(MindDataTestPipeline, TestManifestClassIndex) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| int32_t label_idx = 0; | |||
| @@ -247,12 +247,12 @@ TEST_F(MindDataTestPipeline, TestManifestClassIndex) { | |||
| std::shared_ptr<Tensor> de_label; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(label, &de_label)); | |||
| de_label->GetItemAt<int32_t>(&label_idx, {}); | |||
| ASSERT_OK(de_label->GetItemAt<int32_t>(&label_idx, {})); | |||
| MS_LOG(INFO) << "Tensor label value: " << label_idx; | |||
| auto label_it = std::find(expected_label.begin(), expected_label.end(), label_idx); | |||
| EXPECT_NE(label_it, expected_label.end()); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -276,14 +276,14 @@ TEST_F(MindDataTestPipeline, TestManifestNumSamplers) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 1); | |||
| @@ -41,7 +41,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -49,7 +49,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess1) { | |||
| auto image = row["file_name"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor image file name: ", image); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Each *.mindrecord file has 5 rows, so there are 20 rows in total(imagenet.mindrecord0 ~ imagenet.mindrecord3) | |||
| @@ -91,7 +91,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -99,7 +99,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess2) { | |||
| auto image = row["file_name"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor image file name: ", image); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Only records in imagenet.mindrecord0 are read | |||
| @@ -127,7 +127,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -135,7 +135,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess3) { | |||
| auto image = row["file_name"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor image file name: ", image); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Only records in imagenet.mindrecord0 and imagenet.mindrecord1 are read | |||
| @@ -162,14 +162,14 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess4) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto label = row["label"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor label: ", label); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Shard file "mindrecord0/mindrecord1/mindrecord2/mindrecord3" have same dataset info, | |||
| @@ -197,7 +197,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess5) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::shared_ptr<Tensor> de_expect_item; | |||
| ASSERT_OK(Tensor::CreateScalar((int64_t)0, &de_expect_item)); | |||
| @@ -210,7 +210,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess5) { | |||
| EXPECT_MSTENSOR_EQ(label, expect_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // SequentialSampler will return 3 samples | |||
| @@ -263,14 +263,14 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess6) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t j = 0; | |||
| while (row.size() != 0) { | |||
| j++; | |||
| auto label = row["label"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor label: ", label); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(j, expected_samples[i]); | |||
| @@ -306,7 +306,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess7) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::shared_ptr<Tensor> de_expect_item; | |||
| ASSERT_OK(Tensor::CreateScalar((int64_t)999, &de_expect_item)); | |||
| @@ -322,7 +322,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess7) { | |||
| EXPECT_MSTENSOR_EQ(label, expect_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -377,7 +377,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess8) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::shared_ptr<Tensor> de_expect_item; | |||
| ASSERT_OK(Tensor::CreateScalar((int64_t)999, &de_expect_item)); | |||
| @@ -393,7 +393,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess8) { | |||
| EXPECT_MSTENSOR_EQ(label, expect_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 8); | |||
| @@ -452,7 +452,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess9) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::shared_ptr<Tensor> de_expect_item; | |||
| ASSERT_OK(Tensor::CreateScalar((int64_t)999, &de_expect_item)); | |||
| @@ -466,7 +466,7 @@ TEST_F(MindDataTestPipeline, TestMindDataSuccess9) { | |||
| EXPECT_MSTENSOR_EQ(label, expect_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -31,9 +31,8 @@ TensorRow VecToRow(const MSTensorVec &v) { | |||
| TensorRow row; | |||
| for (const mindspore::MSTensor &t : v) { | |||
| std::shared_ptr<Tensor> rt; | |||
| Status rc = | |||
| Tensor::CreateFromMemory(TensorShape(t.Shape()), MSTypeToDEType(static_cast<mindspore::TypeId>(t.DataType())), | |||
| (const uchar *)(t.Data().get()), t.DataSize(), &rt); | |||
| (void)Tensor::CreateFromMemory(TensorShape(t.Shape()), MSTypeToDEType(static_cast<mindspore::TypeId>(t.DataType())), | |||
| (const uchar *)(t.Data().get()), t.DataSize(), &rt); | |||
| row.emplace_back(rt); | |||
| } | |||
| return row; | |||
| @@ -49,9 +48,9 @@ MSTensorVec RowToVec(const TensorRow &v) { | |||
| MSTensorVec BucketBatchTestFunction(MSTensorVec input) { | |||
| mindspore::dataset::TensorRow output; | |||
| std::shared_ptr<Tensor> out; | |||
| Tensor::CreateEmpty(mindspore::dataset::TensorShape({1}), | |||
| mindspore::dataset::DataType(mindspore::dataset::DataType::Type::DE_INT32), &out); | |||
| out->SetItemAt({0}, 2); | |||
| (void)Tensor::CreateEmpty(mindspore::dataset::TensorShape({1}), | |||
| mindspore::dataset::DataType(mindspore::dataset::DataType::Type::DE_INT32), &out); | |||
| (void)out->SetItemAt({0}, 2); | |||
| output.push_back(out); | |||
| return RowToVec(output); | |||
| } | |||
| @@ -60,15 +59,15 @@ MSTensorVec Predicate1(MSTensorVec in) { | |||
| // Return true if input is equal to 3 | |||
| uint64_t input_value; | |||
| TensorRow input = VecToRow(in); | |||
| input.at(0)->GetItemAt(&input_value, {0}); | |||
| (void)input.at(0)->GetItemAt(&input_value, {0}); | |||
| bool result = (input_value == 3); | |||
| // Convert from boolean to TensorRow | |||
| TensorRow output; | |||
| std::shared_ptr<Tensor> out; | |||
| Tensor::CreateEmpty(mindspore::dataset::TensorShape({}), | |||
| mindspore::dataset::DataType(mindspore::dataset::DataType::Type::DE_BOOL), &out); | |||
| out->SetItemAt({}, result); | |||
| (void)Tensor::CreateEmpty(mindspore::dataset::TensorShape({}), | |||
| mindspore::dataset::DataType(mindspore::dataset::DataType::Type::DE_BOOL), &out); | |||
| (void)out->SetItemAt({}, result); | |||
| output.push_back(out); | |||
| return RowToVec(output); | |||
| @@ -79,15 +78,15 @@ MSTensorVec Predicate2(MSTensorVec in) { | |||
| // The index of label in input is 1 | |||
| uint64_t input_value; | |||
| TensorRow input = VecToRow(in); | |||
| input.at(1)->GetItemAt(&input_value, {0}); | |||
| (void)input.at(1)->GetItemAt(&input_value, {0}); | |||
| bool result = (input_value > 1); | |||
| // Convert from boolean to TensorRow | |||
| TensorRow output; | |||
| std::shared_ptr<Tensor> out; | |||
| Tensor::CreateEmpty(mindspore::dataset::TensorShape({}), | |||
| mindspore::dataset::DataType(mindspore::dataset::DataType::Type::DE_BOOL), &out); | |||
| out->SetItemAt({}, result); | |||
| (void)Tensor::CreateEmpty(mindspore::dataset::TensorShape({}), | |||
| mindspore::dataset::DataType(mindspore::dataset::DataType::Type::DE_BOOL), &out); | |||
| (void)out->SetItemAt({}, result); | |||
| output.push_back(out); | |||
| return RowToVec(output); | |||
| @@ -118,14 +117,14 @@ TEST_F(MindDataTestPipeline, TestBatchAndRepeat) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -154,14 +153,14 @@ TEST_F(MindDataTestPipeline, TestBucketBatchByLengthSuccess1) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // 2 batches of size 5 | |||
| EXPECT_EQ(i, 2); | |||
| @@ -504,13 +503,13 @@ TEST_F(MindDataTestPipeline, TestConcatSuccess) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 19); | |||
| @@ -584,13 +583,13 @@ TEST_F(MindDataTestPipeline, TestConcatSuccess2) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 19); | |||
| @@ -745,12 +744,12 @@ TEST_F(MindDataTestPipeline, TestFilterFail2) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect failure: column check fail and return nothing | |||
| @@ -805,14 +804,14 @@ TEST_F(MindDataTestPipeline, TestImageFolderBatchAndRepeat) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -861,12 +860,12 @@ TEST_F(MindDataTestPipeline, TestDistributedGetDatasetSize1) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // The value of i should be equal to the result of get dataset size | |||
| @@ -892,12 +891,12 @@ TEST_F(MindDataTestPipeline, TestDistributedGetDatasetSize2) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // The value of i should be equal to the result of get dataset size | |||
| @@ -942,14 +941,14 @@ TEST_F(MindDataTestPipeline, TestProjectMap) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -1075,7 +1074,7 @@ TEST_F(MindDataTestPipeline, TestProjectMapAutoInjection) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // 'label' is dropped during the project op | |||
| EXPECT_EQ(row.find("label"), row.end()); | |||
| @@ -1088,7 +1087,7 @@ TEST_F(MindDataTestPipeline, TestProjectMapAutoInjection) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0], 30); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -1197,7 +1196,7 @@ TEST_F(MindDataTestPipeline, TestRenameSuccess) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| EXPECT_NE(row.find("col1"), row.end()); | |||
| @@ -1209,7 +1208,7 @@ TEST_F(MindDataTestPipeline, TestRenameSuccess) { | |||
| i++; | |||
| auto image = row["col1"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -1243,7 +1242,7 @@ TEST_F(MindDataTestPipeline, TestRepeatDefault) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| // manually stop | |||
| @@ -1253,7 +1252,7 @@ TEST_F(MindDataTestPipeline, TestRepeatDefault) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 100); | |||
| @@ -1286,13 +1285,13 @@ TEST_F(MindDataTestPipeline, TestRepeatOne) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -1369,14 +1368,14 @@ TEST_F(MindDataTestPipeline, TestShuffleDataset) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -1405,14 +1404,14 @@ TEST_F(MindDataTestPipeline, TestSkipDataset) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| MS_LOG(INFO) << "Number of rows: " << i; | |||
| @@ -1450,14 +1449,14 @@ TEST_F(MindDataTestPipeline, TestSkipTakeRepeat) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| MS_LOG(INFO) << "Number of rows: " << i; | |||
| @@ -1522,14 +1521,14 @@ TEST_F(MindDataTestPipeline, TestTakeDatasetDefault) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| MS_LOG(INFO) << "Number of rows: " << i; | |||
| @@ -1603,14 +1602,14 @@ TEST_F(MindDataTestPipeline, TestTakeDatasetNormal) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| MS_LOG(INFO) << "Number of rows: " << i; | |||
| @@ -1657,14 +1656,14 @@ TEST_F(MindDataTestPipeline, TestTensorOpsAndMap) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 40); | |||
| @@ -1769,7 +1768,7 @@ TEST_F(MindDataTestPipeline, TestZipSuccess) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check zipped column names | |||
| EXPECT_EQ(row.size(), 4); | |||
| @@ -1783,7 +1782,7 @@ TEST_F(MindDataTestPipeline, TestZipSuccess) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -1861,7 +1860,7 @@ TEST_F(MindDataTestPipeline, TestZipSuccess2) { | |||
| // iterate over the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check zipped column names | |||
| EXPECT_EQ(row.size(), 4); | |||
| @@ -1875,7 +1874,7 @@ TEST_F(MindDataTestPipeline, TestZipSuccess2) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 9); | |||
| @@ -30,8 +30,8 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic1) { | |||
| // Create a RandomDataset | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2}); | |||
| schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1}); | |||
| ASSERT_OK(schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2})); | |||
| ASSERT_OK(schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(50, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -49,7 +49,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if RandomData() read correct columns | |||
| uint64_t i = 0; | |||
| @@ -59,7 +59,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic1) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Tensor label shape: " << label.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -74,8 +74,8 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasicWithPipeline) { | |||
| // Create two RandomDataset | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2}); | |||
| schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1}); | |||
| ASSERT_OK(schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2})); | |||
| ASSERT_OK(schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1})); | |||
| std::shared_ptr<Dataset> ds1 = RandomData(50, schema); | |||
| std::shared_ptr<Dataset> ds2 = RandomData(50, schema); | |||
| EXPECT_NE(ds1, nullptr); | |||
| @@ -107,7 +107,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasicWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if RandomData() read correct columns | |||
| uint64_t i = 0; | |||
| @@ -117,7 +117,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasicWithPipeline) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Tensor label shape: " << label.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -132,8 +132,8 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetGetters) { | |||
| // Create a RandomDataset | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2}); | |||
| schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1}); | |||
| ASSERT_OK(schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2})); | |||
| ASSERT_OK(schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(50, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -163,14 +163,14 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if RandomData() read correct columns | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| // If no schema specified, RandomData will generate random columns | |||
| // So we don't check columns here | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -203,7 +203,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expect_num = {1}; | |||
| std::vector<int64_t> expect_1d = {2}; | |||
| @@ -252,7 +252,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic3) { | |||
| ASSERT_EQ(col_3d.DataType(), mindspore::DataType::kNumberTypeInt64); | |||
| ASSERT_EQ(col_binary.DataType(), mindspore::DataType::kNumberTypeUInt8); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -285,7 +285,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic4) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expect_num = {1}; | |||
| std::vector<int64_t> expect_1d = {2}; | |||
| @@ -334,7 +334,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic4) { | |||
| ASSERT_EQ(col_3d.DataType(), mindspore::DataType::kNumberTypeInt64); | |||
| ASSERT_EQ(col_binary.DataType(), mindspore::DataType::kNumberTypeUInt8); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -367,7 +367,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic5) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expect_num = {1}; | |||
| std::vector<int64_t> expect_1d = {2}; | |||
| @@ -396,7 +396,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic5) { | |||
| ASSERT_EQ(col_sint64.DataType(), mindspore::DataType::kNumberTypeInt64); | |||
| ASSERT_EQ(col_1d.DataType(), mindspore::DataType::kNumberTypeInt64); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -425,12 +425,12 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic6) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if RandomData() read correct columns | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -459,12 +459,12 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetBasic7) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if RandomData() read correct columns | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -482,7 +482,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetUInt8) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(963); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeUInt8, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeUInt8, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(3); | |||
| @@ -495,14 +495,14 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetUInt8) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| auto ind = row["col1"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "ind: ", ind); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -520,7 +520,7 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetFloat) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(369); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeFloat16, {2, 3}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeFloat16, {2, 3})); | |||
| std::shared_ptr<Dataset> ds = RandomData(4, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -533,14 +533,14 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetFloat) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| auto ind = row["col1"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "ind: ", ind); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -556,8 +556,8 @@ TEST_F(MindDataTestPipeline, TestRandomDatasetDuplicateColumnName) { | |||
| // Create a RandomDataset | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2}); | |||
| schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1}); | |||
| ASSERT_OK(schema->add_column("image", mindspore::DataType::kNumberTypeUInt8, {2})); | |||
| ASSERT_OK(schema->add_column("label", mindspore::DataType::kNumberTypeUInt8, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(50, schema, {"image", "image"}); | |||
| // Expect failure: duplicate column names | |||
| EXPECT_EQ(ds->CreateIterator(), nullptr); | |||
| @@ -41,7 +41,7 @@ TEST_F(MindDataTestPipeline, TestSaveCifar10AndLoad) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| std::vector<mindspore::MSTensor> original_data; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Save original data for comparison | |||
| uint64_t i = 0; | |||
| @@ -50,7 +50,7 @@ TEST_F(MindDataTestPipeline, TestSaveCifar10AndLoad) { | |||
| original_data.push_back(label); | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor label: ", label); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -90,7 +90,7 @@ TEST_F(MindDataTestPipeline, TestSaveCifar10AndLoad) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row_minddata; | |||
| iter_minddata->GetNextRow(&row_minddata); | |||
| ASSERT_OK(iter_minddata->GetNextRow(&row_minddata)); | |||
| // Check column name for each row | |||
| EXPECT_NE(row_minddata.find("image"), row_minddata.end()); | |||
| @@ -103,7 +103,7 @@ TEST_F(MindDataTestPipeline, TestSaveCifar10AndLoad) { | |||
| EXPECT_MSTENSOR_EQ(original_data[j], label); | |||
| TEST_MS_LOG_MSTENSOR(INFO, "Tensor label: ", label); | |||
| iter_minddata->GetNextRow(&row_minddata); | |||
| ASSERT_OK(iter_minddata->GetNextRow(&row_minddata)); | |||
| j++; | |||
| } | |||
| @@ -51,7 +51,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetBasic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"Be happy every day.", "This is a text file."}; | |||
| @@ -63,14 +63,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetBasic) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 samples | |||
| @@ -124,7 +124,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetBasicWithPipeline) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"Be happy every day.", "This is a text file."}; | |||
| @@ -134,7 +134,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetBasicWithPipeline) { | |||
| auto text = row["text"]; | |||
| MS_LOG(INFO) << "Tensor text shape: " << text.Shape(); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 10 samples | |||
| @@ -310,7 +310,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFalse1A) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"This is a text file.", "Be happy every day.", "Good luck to everyone.", | |||
| @@ -323,14 +323,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFalse1A) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -371,7 +371,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFalse1B) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"This is a text file.", "Be happy every day.", "Good luck to everyone.", | |||
| @@ -384,14 +384,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFalse1B) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -432,7 +432,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFalse4Shard) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"This is a text file.", "Be happy every day.", "Good luck to everyone."}; | |||
| @@ -444,14 +444,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFalse4Shard) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 3 samples for this shard | |||
| @@ -493,7 +493,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFiles1A) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = { | |||
| @@ -507,14 +507,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFiles1A) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -556,7 +556,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFiles1B) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = { | |||
| @@ -570,14 +570,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFiles1B) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -619,7 +619,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFiles4) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"This is a text file.", "Another file.", "Be happy every day.", | |||
| @@ -632,14 +632,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleFiles4) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -678,7 +678,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleGlobal1A) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"Good luck to everyone.", "This is a text file.", "Be happy every day."}; | |||
| @@ -690,14 +690,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleGlobal1A) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 3 samples | |||
| @@ -738,7 +738,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleGlobal1B) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"Another file.", "Good luck to everyone.", "This is a text file.", | |||
| @@ -751,14 +751,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleGlobal1B) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -799,7 +799,7 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleGlobal4) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_NE(row.find("text"), row.end()); | |||
| std::vector<std::string> expected_result = {"Another file.", "Good luck to everyone.", "End of file.", | |||
| @@ -812,14 +812,14 @@ TEST_F(MindDataTestPipeline, TestTextFileDatasetShuffleGlobal4) { | |||
| std::shared_ptr<Tensor> de_text; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(text, &de_text)); | |||
| std::string_view sv; | |||
| de_text->GetItemAt(&sv, {}); | |||
| ASSERT_OK(de_text->GetItemAt(&sv, {})); | |||
| std::string ss(sv); | |||
| MS_LOG(INFO) << "Text length: " << ss.length() << ", Text: " << ss.substr(0, 50); | |||
| // Compare against expected result | |||
| EXPECT_STREQ(ss.c_str(), expected_result[i].c_str()); | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Expect 2 + 3 = 5 samples | |||
| @@ -63,7 +63,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetBasic) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check column | |||
| EXPECT_EQ(row.size(), 1); | |||
| @@ -74,7 +74,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetBasic) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -143,9 +143,9 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetShuffle) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row1; | |||
| iter1->GetNextRow(&row1); | |||
| ASSERT_OK(iter1->GetNextRow(&row1)); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row2; | |||
| iter2->GetNextRow(&row2); | |||
| ASSERT_OK(iter2->GetNextRow(&row2)); | |||
| uint64_t i = 0; | |||
| int64_t value1 = 0; | |||
| @@ -154,17 +154,17 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetShuffle) { | |||
| auto scalars1 = row1["scalars"]; | |||
| std::shared_ptr<Tensor> de_scalars1; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(scalars1, &de_scalars1)); | |||
| de_scalars1->GetItemAt(&value1, {0}); | |||
| ASSERT_OK(de_scalars1->GetItemAt(&value1, {0})); | |||
| auto scalars2 = row2["scalars"]; | |||
| std::shared_ptr<Tensor> de_scalars2; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(scalars2, &de_scalars2)); | |||
| de_scalars2->GetItemAt(&value2, {0}); | |||
| ASSERT_OK(de_scalars2->GetItemAt(&value2, {0})); | |||
| EXPECT_EQ(value1, value2); | |||
| iter1->GetNextRow(&row1); | |||
| iter2->GetNextRow(&row2); | |||
| ASSERT_OK(iter1->GetNextRow(&row1)); | |||
| ASSERT_OK(iter2->GetNextRow(&row2)); | |||
| i++; | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -198,7 +198,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetShuffle2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int> expect = {9, 3, 4, 7, 2, 1, 6, 8, 10, 5}; | |||
| std::vector<int> actual = {}; | |||
| @@ -208,10 +208,10 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetShuffle2) { | |||
| auto scalars = row["scalars"]; | |||
| std::shared_ptr<Tensor> de_scalars; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(scalars, &de_scalars)); | |||
| de_scalars->GetItemAt(&value, {0}); | |||
| ASSERT_OK(de_scalars->GetItemAt(&value, {0})); | |||
| actual.push_back(value); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| ASSERT_EQ(actual, expect); | |||
| @@ -241,7 +241,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetSchemaPath) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check column | |||
| EXPECT_EQ(row.size(), 8); | |||
| @@ -257,7 +257,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetSchemaPath) { | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 9); | |||
| @@ -272,9 +272,9 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetSchemaObj) { | |||
| // Create a TFRecord Dataset | |||
| std::string file_path = datasets_root_path_ + "/testTFTestAllTypes/test.data"; | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col_sint16", "int16", {1}); | |||
| schema->add_column("col_float", "float32", {1}); | |||
| schema->add_column("col_2d", "int64", {2, 2}); | |||
| ASSERT_OK(schema->add_column("col_sint16", "int16", {1})); | |||
| ASSERT_OK(schema->add_column("col_float", "float32", {1})); | |||
| ASSERT_OK(schema->add_column("col_2d", "int64", {2, 2})); | |||
| std::shared_ptr<Dataset> ds = TFRecord({file_path}, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -285,7 +285,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetSchemaObj) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check column | |||
| EXPECT_EQ(row.size(), 3); | |||
| @@ -317,7 +317,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetSchemaObj) { | |||
| ASSERT_EQ(col_float.DataType(), mindspore::DataType::kNumberTypeFloat32); | |||
| ASSERT_EQ(col_2d.DataType(), mindspore::DataType::kNumberTypeInt64); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -343,7 +343,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetNoSchema) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check column | |||
| EXPECT_EQ(row.size(), 2); | |||
| @@ -357,7 +357,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetNoSchema) { | |||
| MS_LOG(INFO) << "Shape of column [image]:" << image.Shape(); | |||
| MS_LOG(INFO) << "Shape of column [label]:" << label.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -383,7 +383,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetColName) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check column | |||
| EXPECT_EQ(row.size(), 1); | |||
| @@ -392,7 +392,7 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetColName) { | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -423,20 +423,20 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetShard) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row1; | |||
| iter1->GetNextRow(&row1); | |||
| ASSERT_OK(iter1->GetNextRow(&row1)); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row2; | |||
| iter2->GetNextRow(&row2); | |||
| ASSERT_OK(iter2->GetNextRow(&row2)); | |||
| uint64_t i = 0; | |||
| uint64_t j = 0; | |||
| while (row1.size() != 0) { | |||
| i++; | |||
| iter1->GetNextRow(&row1); | |||
| ASSERT_OK(iter1->GetNextRow(&row1)); | |||
| } | |||
| while (row2.size() != 0) { | |||
| j++; | |||
| iter2->GetNextRow(&row2); | |||
| ASSERT_OK(iter2->GetNextRow(&row2)); | |||
| } | |||
| EXPECT_EQ(i, 5); | |||
| @@ -501,8 +501,8 @@ TEST_F(MindDataTestPipeline, TestTFRecordDatasetExeception2) { | |||
| TEST_F(MindDataTestPipeline, TestIncorrectTFSchemaObject) { | |||
| std::string path = datasets_root_path_ + "/test_tf_file_3_images2/train-0000-of-0001.data"; | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("image", "uint8", {1}); | |||
| schema->add_column("label", "int64", {1}); | |||
| ASSERT_OK(schema->add_column("image", "uint8", {1})); | |||
| ASSERT_OK(schema->add_column("label", "int64", {1})); | |||
| std::shared_ptr<Dataset> ds = TFRecord({path}, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| auto itr = ds->CreateIterator(); | |||
| @@ -46,7 +46,7 @@ TEST_F(MindDataTestPipeline, TestVOCClassIndex) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if VOC() read correct labels | |||
| // When we provide class_index, label of ["car","cat","train"] become [0,1,9] | |||
| @@ -65,7 +65,7 @@ TEST_F(MindDataTestPipeline, TestVOCClassIndex) { | |||
| mindspore::MSTensor expect_label = mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_label)); | |||
| EXPECT_MSTENSOR_EQ(label, expect_label); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -133,7 +133,7 @@ TEST_F(MindDataTestPipeline, TestVOCDetection) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if VOC() read correct images/labels | |||
| std::string expect_file[] = {"15", "32", "33", "39"}; | |||
| @@ -156,7 +156,7 @@ TEST_F(MindDataTestPipeline, TestVOCDetection) { | |||
| mindspore::MSTensor expect_label = mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_label)); | |||
| EXPECT_MSTENSOR_EQ(label, expect_label); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -208,7 +208,7 @@ TEST_F(MindDataTestPipeline, TestVOCSegmentation) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if VOC() read correct images/targets | |||
| std::string expect_file[] = {"32", "33", "39", "32", "33", "39"}; | |||
| @@ -225,7 +225,7 @@ TEST_F(MindDataTestPipeline, TestVOCSegmentation) { | |||
| mindspore::MSTensor expect_target = ReadFileToTensor(folder_path + "/SegmentationClass/" + expect_file[i] + ".png"); | |||
| EXPECT_MSTENSOR_EQ(target, expect_target); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -42,7 +42,7 @@ TEST_F(MindDataTestPipeline, TestCelebADataset) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if CelebA() read correct images/attr | |||
| std::string expect_file[] = {"1.JPEG", "2.jpg"}; | |||
| @@ -65,7 +65,7 @@ TEST_F(MindDataTestPipeline, TestCelebADataset) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expect_attr)); | |||
| EXPECT_MSTENSOR_EQ(attr, expect_attr); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -90,7 +90,7 @@ TEST_F(MindDataTestPipeline, TestCelebADefault) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check if CelebA() read correct images/attr | |||
| uint64_t i = 0; | |||
| @@ -100,7 +100,7 @@ TEST_F(MindDataTestPipeline, TestCelebADefault) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Tensor attr shape: " << attr.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -220,8 +220,8 @@ TEST_F(MindDataTestPipeline, TestImageFolderFailWithWrongExtensionFail) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| // Expect no data: cannot find files with specified extension | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 0); | |||
| // Manually terminate the pipeline | |||
| @@ -47,17 +47,17 @@ TEST_F(MindDataTestEpochCtrl, TestAutoInjectEpoch) { | |||
| for (int epoch = 0; epoch < num_epochs; epoch++) { | |||
| // Iterate the dataset and get each row | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| while (row.size() != 0) { | |||
| auto label = row["label"]; | |||
| std::shared_ptr<Tensor> de_label; | |||
| int64_t label_value; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(label, &de_label)); | |||
| de_label->GetItemAt(&label_value, {}); | |||
| ASSERT_OK(de_label->GetItemAt(&label_value, {})); | |||
| EXPECT_TRUE(img_class[(i % sampler_size) / class_size] == label_value); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -65,7 +65,7 @@ TEST_F(MindDataTestEpochCtrl, TestAutoInjectEpoch) { | |||
| EXPECT_EQ(i, sampler_size * num_epochs); | |||
| // Try to fetch data beyond the specified number of epochs. | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 2); | |||
| // Manually terminate the pipeline | |||
| @@ -94,16 +94,16 @@ TEST_F(MindDataTestEpochCtrl, TestEpoch) { | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| for (int epoch = 0; epoch < num_epochs; epoch++) { | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| while (row.size() != 0) { | |||
| auto label = row["label"]; | |||
| std::shared_ptr<Tensor> de_label; | |||
| int64_t label_value; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(label, &de_label)); | |||
| de_label->GetItemAt(&label_value, {}); | |||
| ASSERT_OK(de_label->GetItemAt(&label_value, {})); | |||
| EXPECT_TRUE(label_value >= 0 && label_value <= 3); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -112,7 +112,7 @@ TEST_F(MindDataTestEpochCtrl, TestEpoch) { | |||
| EXPECT_EQ(i, sampler_size * num_epochs); | |||
| // Try to fetch data beyond the specified number of epochs. | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 2); | |||
| // Manually terminate the pipeline | |||
| @@ -143,16 +143,16 @@ TEST_F(MindDataTestEpochCtrl, TestRepeatEpoch) { | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| for (int epoch = 0; epoch < num_epochs; epoch++) { | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| while (row.size() != 0) { | |||
| auto label = row["label"]; | |||
| std::shared_ptr<Tensor> de_label; | |||
| int64_t label_value; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(label, &de_label)); | |||
| de_label->GetItemAt(&label_value, {}); | |||
| ASSERT_OK(de_label->GetItemAt(&label_value, {})); | |||
| EXPECT_TRUE(label_value >= 0 && label_value <= 3); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -161,7 +161,7 @@ TEST_F(MindDataTestEpochCtrl, TestRepeatEpoch) { | |||
| EXPECT_EQ(i, sampler_size * num_repeats * num_epochs); | |||
| // Try to fetch data beyond the specified number of epochs. | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 2); | |||
| // Manually terminate the pipeline | |||
| @@ -192,16 +192,16 @@ TEST_F(MindDataTestEpochCtrl, TestRepeatRepeatEpoch) { | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| for (int epoch = 0; epoch < num_epochs; epoch++) { | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| while (row.size() != 0) { | |||
| auto label = row["label"]; | |||
| std::shared_ptr<Tensor> de_label; | |||
| int64_t label_value; | |||
| ASSERT_OK(Tensor::CreateFromMSTensor(label, &de_label)); | |||
| de_label->GetItemAt(&label_value, {}); | |||
| ASSERT_OK(de_label->GetItemAt(&label_value, {})); | |||
| EXPECT_TRUE(label_value >= 0 && label_value <= 3); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -210,7 +210,7 @@ TEST_F(MindDataTestEpochCtrl, TestRepeatRepeatEpoch) { | |||
| EXPECT_EQ(i, sampler_size * num_repeats[0] * num_repeats[1] * num_epochs); | |||
| // Try to fetch data beyond the specified number of epochs. | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 2); | |||
| // Manually terminate the pipeline | |||
| @@ -42,8 +42,7 @@ TEST_F(MindDataTestPipeline, TestPullBasedBatch) { | |||
| EXPECT_NE(iter, nullptr); | |||
| std::vector<mindspore::MSTensor> row; | |||
| Status rc = iter->GetNextRow(&row); | |||
| EXPECT_EQ(rc, Status::OK()); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 1); | |||
| auto temp = row[0].Shape(); | |||
| std::vector<int64_t> result = {batch_size, 2}; | |||
| @@ -63,8 +62,7 @@ TEST_F(MindDataTestPipeline, TestPullBasedProject) { | |||
| std::vector<mindspore::MSTensor> row; | |||
| auto iter = ds->CreatePullBasedIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| Status rc = iter->GetNextRow(&row); | |||
| EXPECT_EQ(rc, Status::OK()); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| EXPECT_EQ(row.size(), 2); | |||
| std::shared_ptr<Dataset> ds2 = Album(folder_path, schema_file, column_names); | |||
| @@ -77,7 +75,6 @@ TEST_F(MindDataTestPipeline, TestPullBasedProject) { | |||
| EXPECT_NE(iter2, nullptr); | |||
| std::vector<mindspore::MSTensor> new_row; | |||
| rc = iter2->GetNextRow(&new_row); | |||
| EXPECT_EQ(rc, Status::OK()); | |||
| ASSERT_OK(iter2->GetNextRow(&new_row)); | |||
| EXPECT_EQ(new_row.size(), 1); | |||
| } | |||
| @@ -38,12 +38,12 @@ TEST_F(MindDataTestPipeline, TestRepeatSetNumWorkers) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| // Verify correct number of rows fetched | |||
| @@ -72,14 +72,14 @@ TEST_F(MindDataTestPipeline, TestImageFolderWithSamplers) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 12); | |||
| @@ -101,13 +101,13 @@ TEST_F(MindDataTestPipeline, TestNoSamplerSuccess1) { | |||
| std::shared_ptr<Iterator> iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto label = row["label"]; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, ds->GetDatasetSize()); | |||
| @@ -131,13 +131,13 @@ TEST_F(MindDataTestPipeline, TestDistributedSamplerSuccess1) { | |||
| std::shared_ptr<Iterator> iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto label = row["label"]; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 11); | |||
| @@ -162,13 +162,13 @@ TEST_F(MindDataTestPipeline, TestDistributedSamplerSuccess2) { | |||
| std::shared_ptr<Iterator> iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto label = row["label"]; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 11); | |||
| @@ -194,13 +194,13 @@ TEST_F(MindDataTestPipeline, TestDistributedSamplerSuccess3) { | |||
| std::shared_ptr<Iterator> iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto label = row["label"]; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 11); | |||
| @@ -221,13 +221,13 @@ TEST_F(MindDataTestPipeline, TestDistributedSamplerSuccess4) { | |||
| std::shared_ptr<Iterator> iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto label = row["label"]; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -314,12 +314,12 @@ TEST_F(MindDataTestPipeline, TestSamplerAddChild) { | |||
| std::shared_ptr<Iterator> iter = ds->CreateIterator(); | |||
| EXPECT_NE(iter, nullptr); | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(ds->GetDatasetSize(), 5); | |||
| @@ -68,7 +68,7 @@ TEST_F(MindDataTestPipeline, TestSentencePieceVocabSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Expected result after tokenization | |||
| std::vector<std::string> expected = {"▁I", "▁sa", "w", "▁a", "▁girl", "▁with", "▁a", "▁te", "les", "co", "pe", "."}; | |||
| @@ -84,7 +84,7 @@ TEST_F(MindDataTestPipeline, TestSentencePieceVocabSuccess1) { | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -128,7 +128,7 @@ TEST_F(MindDataTestPipeline, TestSentencePieceVocabSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Expected result after tokenization | |||
| std::vector<std::string> expected = {"▁I", "▁sa", "w", "▁a", "▁girl", "▁with", "▁a", "▁te", "les", "co", "pe", "."}; | |||
| @@ -144,7 +144,7 @@ TEST_F(MindDataTestPipeline, TestSentencePieceVocabSuccess2) { | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -63,7 +63,7 @@ TEST_F(MindDataTestPipeline, TestBasicTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"Welcome", "to", "Beijing", "北", "京", "欢", "迎", "您"}, | |||
| @@ -86,7 +86,7 @@ TEST_F(MindDataTestPipeline, TestBasicTokenizerSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -124,7 +124,7 @@ TEST_F(MindDataTestPipeline, TestBasicTokenizerSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"this", "is", "a", "funky", "string"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -136,7 +136,7 @@ TEST_F(MindDataTestPipeline, TestBasicTokenizerSuccess2) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -175,7 +175,7 @@ TEST_F(MindDataTestPipeline, TestBasicTokenizerSuccess3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected_tokens = {"this", "is", "a", "funky", "string"}; | |||
| std::vector<uint32_t> expected_offsets_start = {0, 5, 8, 10, 16}; | |||
| @@ -207,7 +207,7 @@ TEST_F(MindDataTestPipeline, TestBasicTokenizerSuccess3) { | |||
| auto limit = row["offsets_limit"]; | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -257,7 +257,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"床", "前", "明", "月", "光"}, | |||
| {"疑", "是", "地", "上", "霜"}, | |||
| @@ -273,7 +273,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -321,7 +321,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"i", "am", "mak", "##ing", "small", "mistake", | |||
| "##s", "during", "work", "##ing", "hour", "##s"}; | |||
| @@ -334,7 +334,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess2) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -382,7 +382,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"😀", "嘿", "嘿", "😃", "哈", "哈", "😄", "大", "笑", "😁", "嘻", "嘻"}, {"繁", "體", "字"}}; | |||
| @@ -396,7 +396,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess3) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -444,7 +444,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess4) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"[UNK]", " ", "[CLS]"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -456,7 +456,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess4) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -504,7 +504,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess5) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"unused", " ", "[CLS]"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -516,7 +516,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess5) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -564,7 +564,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess6) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"unused", " ", "[", "CLS", "]"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -576,7 +576,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess6) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -624,7 +624,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess7) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected_tokens = {"i", "am", "mak", "##ing", "small", "mistake", | |||
| "##s", "during", "work", "##ing", "hour", "##s"}; | |||
| @@ -657,7 +657,7 @@ TEST_F(MindDataTestPipeline, TestBertTokenizerSuccess7) { | |||
| auto limit = row["offsets_limit"]; | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -739,7 +739,7 @@ TEST_F(MindDataTestPipeline, TestCaseFoldSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"welcome to beijing!", "北京欢迎您!", "我喜欢english!", " "}; | |||
| @@ -751,7 +751,7 @@ TEST_F(MindDataTestPipeline, TestCaseFoldSuccess) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -788,7 +788,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"今天天气", "太好了", "我们", "一起", "去", "外面", "玩吧"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -800,7 +800,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerSuccess) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -837,7 +837,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"今天", "天气", "太", "好", "了", "我们", "一起", "去", "外面", "玩", "吧"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -849,7 +849,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerSuccess1) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -887,7 +887,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected_tokens = {"今天天气", "太好了", "我们", "一起", "去", "外面", "玩吧"}; | |||
| std::vector<uint32_t> expected_offsets_start = {0, 12, 21, 27, 33, 36, 42}; | |||
| @@ -919,7 +919,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerSuccess2) { | |||
| auto limit = row["offsets_limit"]; | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1061,7 +1061,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"男默女泪", "市", "长江大桥"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -1073,7 +1073,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1113,7 +1113,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"男默女泪", "市", "长江大桥"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -1125,7 +1125,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord1) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1165,7 +1165,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"男默女泪", "市", "长江大桥"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -1177,7 +1177,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord2) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1217,7 +1217,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"江州", "市长", "江大桥", "参加", "了", "长江大桥", "的", "通车", "仪式"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -1229,7 +1229,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddWord3) { | |||
| while (row.size() != 0) { | |||
| auto ind = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1293,7 +1293,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddDict) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"江州", "市长", "江大桥", "参加", "了", "长江大桥", "的", "通车", "仪式"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -1305,7 +1305,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddDict) { | |||
| while (row.size() != 0) { | |||
| auto txt = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1349,7 +1349,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddDictFromFile) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"今天天气", "太好了", "我们", "一起", "去", "外面", "玩吧"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -1361,7 +1361,7 @@ TEST_F(MindDataTestPipeline, TestJiebaTokenizerAddDictFromFile) { | |||
| while (row.size() != 0) { | |||
| auto txt = row["text"]; | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1398,7 +1398,7 @@ TEST_F(MindDataTestPipeline, TestSlidingWindowSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"This", "is", "a", "is", "a", "text", "a", "text", "file."}, | |||
| {"Be", "happy", "every", "happy", "every", "day."}, | |||
| @@ -1415,7 +1415,7 @@ TEST_F(MindDataTestPipeline, TestSlidingWindowSuccess) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1452,7 +1452,7 @@ TEST_F(MindDataTestPipeline, TestSlidingWindowSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"This", "is", "is", "a", "a", "text", "text", "file."}, | |||
| {"Be", "happy", "happy", "every", "every", "day."}, | |||
| @@ -1468,7 +1468,7 @@ TEST_F(MindDataTestPipeline, TestSlidingWindowSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1555,7 +1555,7 @@ TEST_F(MindDataTestPipeline, TestToNumberSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<int64_t> expected = {-121, 14, -2219, 7623, -8162536, 162371864, -1726483716, 98921728421}; | |||
| @@ -1567,7 +1567,7 @@ TEST_F(MindDataTestPipeline, TestToNumberSuccess1) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1610,7 +1610,7 @@ TEST_F(MindDataTestPipeline, TestToNumberSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<double_t> expected = {-1.1, 1.4, -2219.321, 7623.453, -816256.234282, 162371864.243243}; | |||
| @@ -1622,7 +1622,7 @@ TEST_F(MindDataTestPipeline, TestToNumberSuccess2) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1667,11 +1667,11 @@ TEST_F(MindDataTestPipeline, TestToNumberFail1) { | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| // Expect error: input out of bounds of int8 | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1717,11 +1717,11 @@ TEST_F(MindDataTestPipeline, TestToNumberFail2) { | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| // Expect error: input out of bounds of float16 | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1763,11 +1763,11 @@ TEST_F(MindDataTestPipeline, TestToNumberFail3) { | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| // Expect error: invalid input which is non numerical | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| iter->GetNextRow(&row); | |||
| EXPECT_ERROR(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1840,8 +1840,8 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairSuccess1) { | |||
| // Create a RandomDataset which has column names "col1" and "col2" | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {5}); | |||
| schema->add_column("col2", mindspore::DataType::kNumberTypeInt32, {3}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {5})); | |||
| ASSERT_OK(schema->add_column("col2", mindspore::DataType::kNumberTypeInt32, {3})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -1860,7 +1860,7 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<int16_t>> expected1 = {{-29556, -29556}, {-18505, -18505}, {-25958, -25958}}; | |||
| std::vector<std::vector<int32_t>> expected2 = { | |||
| @@ -1883,7 +1883,7 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor2)); | |||
| EXPECT_MSTENSOR_EQ(ind2, expected_tensor2); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1915,8 +1915,8 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairSuccess2) { | |||
| // Create a RandomDataset which has column names "col1" and "col2" | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt32, {4}); | |||
| schema->add_column("col2", mindspore::DataType::kNumberTypeInt64, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt32, {4})); | |||
| ASSERT_OK(schema->add_column("col2", mindspore::DataType::kNumberTypeInt64, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(4, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -1935,7 +1935,7 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<int32_t>> expected1 = {{1785358954, 1785358954, 1785358954}, | |||
| {-1195853640, -1195853640, -1195853640}, | |||
| @@ -1961,7 +1961,7 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairSuccess2) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor2)); | |||
| EXPECT_MSTENSOR_EQ(ind2, expected_tensor2); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1983,8 +1983,8 @@ TEST_F(MindDataTestPipeline, TestTruncateSequencePairFail) { | |||
| // Create a RandomDataset which has column names "col1" and "col2" | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt8, {3}); | |||
| schema->add_column("col2", mindspore::DataType::kNumberTypeInt8, {3}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt8, {3})); | |||
| ASSERT_OK(schema->add_column("col2", mindspore::DataType::kNumberTypeInt8, {3})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| @@ -2028,7 +2028,7 @@ TEST_F(MindDataTestPipeline, TestNgramSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"_ This", "This is", "is a", "a text", "text file.", "file. _"}, | |||
| {"_ Be", "Be happy", "happy every", "every day.", "day. _"}, | |||
| @@ -2045,7 +2045,7 @@ TEST_F(MindDataTestPipeline, TestNgramSuccess) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2081,7 +2081,7 @@ TEST_F(MindDataTestPipeline, TestNgramSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"&-This", "This-is", "is-a", "a-text", "text-file.", "file.-&", "&-&-This", "&-This-is", "This-is-a", | |||
| @@ -2103,7 +2103,7 @@ TEST_F(MindDataTestPipeline, TestNgramSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2252,7 +2252,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"ṩ", "ḍ̇", "q̣̇", "fi", "25", "ṩ"}; | |||
| @@ -2264,7 +2264,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2298,7 +2298,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"ṩ", "ḍ̇", "q̣̇", "fi", "2⁵", "ẛ̣"}; | |||
| @@ -2310,7 +2310,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success1) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2344,7 +2344,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"ṩ", "ḍ̇", "q̣̇", "fi", "2⁵", "ẛ̣"}; | |||
| @@ -2356,7 +2356,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success2) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2390,7 +2390,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"ṩ", "ḍ̇", "q̣̇", "fi", "25", "ṩ"}; | |||
| @@ -2402,7 +2402,7 @@ TEST_F(MindDataTestPipeline, TestNormalizeUTF8Success3) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2436,7 +2436,7 @@ TEST_F(MindDataTestPipeline, TestRegexReplaceSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"Hello_World", "Let's_Go", "1:hello", "2:world", | |||
| "31:beijing", "Welcome_to_China!", "_我_不想_长大_", "Welcome_to_Shenzhen!"}; | |||
| @@ -2449,7 +2449,7 @@ TEST_F(MindDataTestPipeline, TestRegexReplaceSuccess) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2483,7 +2483,7 @@ TEST_F(MindDataTestPipeline, TestRegexReplaceSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"Hello_World", "Let's_Go", "1:hello", "2:world", | |||
| "31:beijing", "Welcome_to China!", "_我 不想 长大 ", "Welcome_to Shenzhen!"}; | |||
| @@ -2496,7 +2496,7 @@ TEST_F(MindDataTestPipeline, TestRegexReplaceSuccess1) { | |||
| mindspore::MSTensor ms_expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2530,7 +2530,7 @@ TEST_F(MindDataTestPipeline, TestRegexTokenizerSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"Hello", " ", "World"}, | |||
| {"Let's", " ", "Go"}, | |||
| @@ -2552,7 +2552,7 @@ TEST_F(MindDataTestPipeline, TestRegexTokenizerSuccess) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2587,7 +2587,7 @@ TEST_F(MindDataTestPipeline, TestRegexTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected_tokens = {{"Hello", " ", "World"}, | |||
| {"Let's", " ", "Go"}, | |||
| @@ -2628,7 +2628,7 @@ TEST_F(MindDataTestPipeline, TestRegexTokenizerSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_offsets_limit)); | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2662,7 +2662,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeCharTokenizerSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"W", "e", "l", "c", "o", "m", "e", " ", "t", "o", " ", "B", "e", "i", "j", "i", "n", "g", "!"}, | |||
| @@ -2681,7 +2681,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeCharTokenizerSuccess) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2716,7 +2716,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeCharTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected_tokens = { | |||
| {"W", "e", "l", "c", "o", "m", "e", " ", "t", "o", " ", "B", "e", "i", "j", "i", "n", "g", "!"}, | |||
| @@ -2761,7 +2761,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeCharTokenizerSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_offsets_limit)); | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2809,7 +2809,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"my"}, {"favor", "##ite"}, {"book"}, {"is"}, {"love"}, {"dur", "##ing"}, {"the"}, {"cholera"}, {"era"}, {"[UNK]"}}; | |||
| @@ -2822,7 +2822,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess1) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2866,7 +2866,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"my"}, {"favor", "##ite"}, {"book"}, {"is"}, {"love"}, {"dur", "##ing"}, {"the"}, {"cholera"}, {"era"}, {"what"}}; | |||
| @@ -2879,7 +2879,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess2) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2923,7 +2923,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"my"}, {"[UNK]"}, {"book"}, {"is"}, {"love"}, | |||
| {"[UNK]"}, {"the"}, {"[UNK]"}, {"era"}, {"[UNK]"}}; | |||
| @@ -2936,7 +2936,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess3) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -2984,7 +2984,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess4) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"我"}, {"最"}, {"喜"}, {"欢"}, {"的"}, {"书"}, {"是"}, {"霍"}, | |||
| {"乱"}, {"时"}, {"期"}, {"的"}, {"爱"}, {"情"}, {"[UNK]"}}; | |||
| @@ -2997,7 +2997,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess4) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3041,7 +3041,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess5) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"my"}, {"favor", "##ite"}, {"book"}, {"is"}, {"love"}, {"dur", "##ing"}, {"the"}, {"cholera"}, {"era"}, {"[UNK]"}}; | |||
| @@ -3070,7 +3070,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess5) { | |||
| mindspore::MSTensor expected_limit_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_limit_tensor)); | |||
| EXPECT_MSTENSOR_EQ(limit, expected_limit_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3114,7 +3114,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess6) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = {{"[UNK]"}, {"[UNK]"}, {"[UNK]"}, {"[UNK]"}, {"[UNK]"}, | |||
| {"[UNK]"}, {"[UNK]"}, {"[UNK]"}, {"[UNK]"}, {"[UNK]"}}; | |||
| @@ -3127,7 +3127,7 @@ TEST_F(MindDataTestPipeline, TestWordpieceTokenizerSuccess6) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(txt, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3210,7 +3210,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"Welcome", "to", "Beijing", "!"}, {"北京欢迎您", "!"}, {"我喜欢", "English", "!"}, {""}}; | |||
| @@ -3226,7 +3226,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3261,7 +3261,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"Welcome", " ", "to", " ", "Beijing", "!"}, {"北京欢迎您", "!"}, {"我喜欢", "English", "!"}, {" "}}; | |||
| @@ -3277,7 +3277,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3314,7 +3314,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected_tokens = { | |||
| {"Welcome", "to", "Beijing", "!"}, {"北京欢迎您", "!"}, {"我喜欢", "English", "!"}, {""}}; | |||
| @@ -3347,7 +3347,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess2) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_offsets_limit)); | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3383,7 +3383,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess3) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected_tokens = { | |||
| {"Welcome", " ", "to", " ", "Beijing", "!"}, {"北京欢迎您", "!"}, {"我喜欢", "English", "!"}, {" "}}; | |||
| @@ -3416,7 +3416,7 @@ TEST_F(MindDataTestPipeline, TestUnicodeScriptTokenizerSuccess3) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_offsets_limit)); | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3450,7 +3450,7 @@ TEST_F(MindDataTestPipeline, TestWhitespaceTokenizerSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected = { | |||
| {"This", "is", "a", "text", "file."}, {"Be", "happy", "every", "day."}, {"Good", "luck", "to", "everyone."}}; | |||
| @@ -3466,7 +3466,7 @@ TEST_F(MindDataTestPipeline, TestWhitespaceTokenizerSuccess) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -3501,7 +3501,7 @@ TEST_F(MindDataTestPipeline, TestWhitespaceTokenizerSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::string>> expected_tokens = { | |||
| {"Welcome", "to", "Beijing!"}, {"北京欢迎您!"}, {"我喜欢English!"}, {""}}; | |||
| @@ -3534,7 +3534,7 @@ TEST_F(MindDataTestPipeline, TestWhitespaceTokenizerSuccess1) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_offsets_limit)); | |||
| EXPECT_MSTENSOR_EQ(limit, ms_expected_offsets_limit); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -70,7 +70,7 @@ TEST_F(MindDataTestPipeline, TestVocabLookupOp) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| std::vector<int32_t> expected = {2, 1, 4, 5, 6, 7}; | |||
| @@ -84,7 +84,7 @@ TEST_F(MindDataTestPipeline, TestVocabLookupOp) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_item)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -118,7 +118,7 @@ TEST_F(MindDataTestPipeline, TestVocabLookupOpEmptyString) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| std::vector<int32_t> expected = {2, 1, 4, 5, 6, 7}; | |||
| @@ -132,7 +132,7 @@ TEST_F(MindDataTestPipeline, TestVocabLookupOpEmptyString) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_item)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -218,7 +218,7 @@ TEST_F(MindDataTestPipeline, TestVocabFromDataset) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| std::vector<int32_t> expected = {4, 5, 3, 6, 7, 2}; | |||
| @@ -232,7 +232,7 @@ TEST_F(MindDataTestPipeline, TestVocabFromDataset) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_item)); | |||
| EXPECT_MSTENSOR_EQ(ind, ms_expected_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -268,7 +268,7 @@ TEST_F(MindDataTestPipeline, TestVocabFromDatasetDefault) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| std::vector<int32_t> expected = {2, 3, 1, 4, 5, 0}; | |||
| @@ -290,7 +290,7 @@ TEST_F(MindDataTestPipeline, TestVocabFromDatasetDefault) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_not_expected_item)); | |||
| EXPECT_MSTENSOR_DATA_NE(ind, ms_not_expected_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -385,7 +385,7 @@ TEST_F(MindDataTestPipeline, TestVocabFromDatasetInt64) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| std::vector<int64_t> expected = {2, 3, 1, 4, 5, 0}; | |||
| @@ -407,7 +407,7 @@ TEST_F(MindDataTestPipeline, TestVocabFromDatasetInt64) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_not_expected_item)); | |||
| EXPECT_MSTENSOR_DATA_NE(ind, ms_not_expected_item); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| } | |||
| @@ -52,7 +52,7 @@ TEST_F(MindDataTestPipeline, TestComposeSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -63,7 +63,7 @@ TEST_F(MindDataTestPipeline, TestComposeSuccess) { | |||
| MS_LOG(INFO) << "Label shape: " << label.Shape(); | |||
| EXPECT_EQ(image.Shape()[0], 777); | |||
| EXPECT_EQ(image.Shape()[1], 777); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -144,7 +144,7 @@ TEST_F(MindDataTestPipeline, TestConcatenateSuccess) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(246); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {1}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(4, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -176,7 +176,7 @@ TEST_F(MindDataTestPipeline, TestConcatenateSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::int16_t>> expected = { | |||
| {1, 2, 31354, 3}, {1, 2, -5655, 3}, {1, 2, -17734, 3}, {1, 2, -17220, 3}}; | |||
| @@ -190,7 +190,7 @@ TEST_F(MindDataTestPipeline, TestConcatenateSuccess) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -223,7 +223,7 @@ TEST_F(MindDataTestPipeline, TestDuplicateSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -232,7 +232,7 @@ TEST_F(MindDataTestPipeline, TestDuplicateSuccess) { | |||
| auto image_copy = row["image_copy"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_MSTENSOR_EQ(image, image_copy); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -248,7 +248,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessInt) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(864); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt32, {6}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt32, {6})); | |||
| std::shared_ptr<Dataset> ds = RandomData(5, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(3); | |||
| @@ -270,7 +270,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessInt) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<int32_t>> expected = { | |||
| {3, 3, 3, 3, 3, 3}, {3, 3, 3, 3, 3, 3}, {3, 3, 3, 3, 3, 3}, {3, 3, 3, 3, 3, 3}, {3, 3, 3, 3, 3, 3}}; | |||
| @@ -285,7 +285,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessInt) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -303,7 +303,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessBool) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(963); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeBool, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeBool, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -325,7 +325,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessBool) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<bool>> expected = { | |||
| {true, true, true, true}, {true, true, true, true}, {true, true, true, true}}; | |||
| @@ -340,7 +340,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessBool) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -358,7 +358,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecast) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(963); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeUInt8, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeUInt8, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -380,7 +380,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecast) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Note: 2**8 -3 = 256 -3 = 253 | |||
| std::vector<std::vector<uint8_t>> expected = {{253, 253, 253, 253}, {253, 253, 253, 253}, {253, 253, 253, 253}}; | |||
| @@ -395,7 +395,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecast) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -413,7 +413,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecastZero) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(963); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeUInt8, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeUInt8, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -435,7 +435,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecastZero) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Note: 2**8 = 256 | |||
| std::vector<std::vector<uint8_t>> expected = {{0, 0, 0, 0}, {0, 0, 0, 0}, {0, 0, 0, 0}}; | |||
| @@ -450,7 +450,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecastZero) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -468,7 +468,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecast16) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(963); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeUInt16, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeUInt16, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(3, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -490,7 +490,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecast16) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Note: 2**16 -3 = 65536 -3 = 65533 | |||
| std::vector<std::vector<uint16_t>> expected = { | |||
| @@ -506,7 +506,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessDownTypecast16) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -524,7 +524,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessUpTypecast) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(963); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeFloat32, {2}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeFloat32, {2})); | |||
| std::shared_ptr<Dataset> ds = RandomData((float)4.0, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -546,7 +546,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessUpTypecast) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<float_t>> expected = {{0.0, 0.0}, {0.0, 0.0}, {0.0, 0.0}, {0.0, 0.0}}; | |||
| @@ -560,7 +560,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessUpTypecast) { | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -607,7 +607,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessString) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::string> expected = {"Hello", "Hello", "Hello", "Hello", "Hello"}; | |||
| std::shared_ptr<Tensor> de_expected_tensor; | |||
| @@ -620,7 +620,7 @@ TEST_F(MindDataTestPipeline, TestFillSuccessString) { | |||
| auto ind = row["text"]; | |||
| TEST_MS_LOG_MSTENSOR(INFO, "ind: ", ind); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -676,7 +676,7 @@ TEST_F(MindDataTestPipeline, TestMaskSuccess) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(246); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {4}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {4})); | |||
| std::shared_ptr<Dataset> ds = RandomData(4, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -698,7 +698,7 @@ TEST_F(MindDataTestPipeline, TestMaskSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<bool>> expected = { | |||
| {true, true, true, true}, {false, false, false, false}, {false, false, false, false}, {false, false, false, false}}; | |||
| @@ -711,7 +711,7 @@ TEST_F(MindDataTestPipeline, TestMaskSuccess) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -764,7 +764,7 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -778,7 +778,7 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) { | |||
| true); | |||
| EXPECT_EQ(label.Shape().size() == 2 && batch_size == label.Shape()[0] && number_of_classes == label.Shape()[1], | |||
| true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -819,14 +819,14 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -882,7 +882,7 @@ TEST_F(MindDataTestPipeline, TestPadEndSuccess) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(246); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {1}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(4, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -905,7 +905,7 @@ TEST_F(MindDataTestPipeline, TestPadEndSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::int16_t>> expected = {{31354, 0, 0}, {-5655, 0, 0}, {-17734, 0, 0}, {-17220, 0, 0}}; | |||
| @@ -917,7 +917,7 @@ TEST_F(MindDataTestPipeline, TestPadEndSuccess) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -951,7 +951,7 @@ TEST_F(MindDataTestPipeline, TestRandomApplySuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -960,7 +960,7 @@ TEST_F(MindDataTestPipeline, TestRandomApplySuccess) { | |||
| auto label = row["label"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Label shape: " << label.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 5); | |||
| @@ -1079,7 +1079,7 @@ TEST_F(MindDataTestPipeline, TestRandomChoiceSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -1088,7 +1088,7 @@ TEST_F(MindDataTestPipeline, TestRandomChoiceSuccess) { | |||
| auto label = row["label"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| MS_LOG(INFO) << "Label shape: " << label.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -1170,7 +1170,7 @@ TEST_F(MindDataTestPipeline, TestSliceSuccess) { | |||
| u_int32_t curr_seed = GlobalContext::config_manager()->seed(); | |||
| GlobalContext::config_manager()->set_seed(246); | |||
| std::shared_ptr<SchemaObj> schema = Schema(); | |||
| schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {1}); | |||
| ASSERT_OK(schema->add_column("col1", mindspore::DataType::kNumberTypeInt16, {1})); | |||
| std::shared_ptr<Dataset> ds = RandomData(4, schema); | |||
| EXPECT_NE(ds, nullptr); | |||
| ds = ds->SetNumWorkers(2); | |||
| @@ -1202,7 +1202,7 @@ TEST_F(MindDataTestPipeline, TestSliceSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| std::vector<std::vector<std::int16_t>> expected = {{1, 3}, {1, 3}, {1, 3}, {1, 3}}; | |||
| @@ -1215,7 +1215,7 @@ TEST_F(MindDataTestPipeline, TestSliceSuccess) { | |||
| mindspore::MSTensor expected_tensor = | |||
| mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(de_expected_tensor)); | |||
| EXPECT_MSTENSOR_EQ(ind, expected_tensor); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| i++; | |||
| } | |||
| @@ -1241,7 +1241,7 @@ TEST_F(MindDataTestPipeline, TestTypeCastSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| // Check original data type of dataset | |||
| auto image = row["image"]; | |||
| @@ -1266,7 +1266,7 @@ TEST_F(MindDataTestPipeline, TestTypeCastSuccess) { | |||
| EXPECT_NE(iter2, nullptr); | |||
| // Check current data type of dataset | |||
| iter2->GetNextRow(&row); | |||
| ASSERT_OK(iter2->GetNextRow(&row)); | |||
| auto image2 = row["image"]; | |||
| auto cur_type = image2.DataType(); | |||
| MS_LOG(INFO) << "Current data type id: " << cur_type; | |||
| @@ -60,14 +60,14 @@ TEST_F(MindDataTestPipeline, TestAutoContrastSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 15); | |||
| @@ -109,14 +109,14 @@ TEST_F(MindDataTestPipeline, TestAutoContrastSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 15); | |||
| @@ -158,14 +158,14 @@ TEST_F(MindDataTestPipeline, TestCenterCrop) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 15); | |||
| @@ -220,7 +220,7 @@ TEST_F(MindDataTestPipeline, TestCutMixBatchSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -234,7 +234,7 @@ TEST_F(MindDataTestPipeline, TestCutMixBatchSuccess1) { | |||
| true); | |||
| EXPECT_EQ(label.Shape().size() == 2 && batch_size == label.Shape()[0] && number_of_classes == label.Shape()[1], | |||
| true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -281,7 +281,7 @@ TEST_F(MindDataTestPipeline, TestCutMixBatchSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -296,7 +296,7 @@ TEST_F(MindDataTestPipeline, TestCutMixBatchSuccess2) { | |||
| EXPECT_EQ(label.Shape().size() == 2 && batch_size == label.Shape()[0] && number_of_classes == label.Shape()[1], | |||
| true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -478,14 +478,14 @@ TEST_F(MindDataTestPipeline, TestCutOut) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -527,14 +527,14 @@ TEST_F(MindDataTestPipeline, TestDecode) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -575,7 +575,7 @@ TEST_F(MindDataTestPipeline, TestHwcToChw) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -586,7 +586,7 @@ TEST_F(MindDataTestPipeline, TestHwcToChw) { | |||
| EXPECT_EQ( | |||
| batch_size == image.Shape()[0] && 3 == image.Shape()[1] && 2268 == image.Shape()[2] && 4032 == image.Shape()[3], | |||
| true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -617,14 +617,14 @@ TEST_F(MindDataTestPipeline, TestInvert) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -735,14 +735,14 @@ TEST_F(MindDataTestPipeline, TestMixUpBatchSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -786,14 +786,14 @@ TEST_F(MindDataTestPipeline, TestMixUpBatchSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -835,14 +835,14 @@ TEST_F(MindDataTestPipeline, TestNormalize) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -880,7 +880,7 @@ TEST_F(MindDataTestPipeline, TestNormalizePad) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -889,7 +889,7 @@ TEST_F(MindDataTestPipeline, TestNormalizePad) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[2], 4); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -933,14 +933,14 @@ TEST_F(MindDataTestPipeline, TestPad) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -52,7 +52,7 @@ TEST_F(MindDataTestPipeline, TestAffineAPI) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -60,7 +60,7 @@ TEST_F(MindDataTestPipeline, TestAffineAPI) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(row["image"].Shape().at(0), 256); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 15); | |||
| @@ -50,14 +50,14 @@ TEST_F(MindDataTestPipeline, TestBoundingBoxAugmentSuccess1Shr) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -90,14 +90,14 @@ TEST_F(MindDataTestPipeline, TestBoundingBoxAugmentSuccess2Auto) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -133,14 +133,14 @@ TEST_F(MindDataTestPipeline, TestBoundingBoxAugmentSuccess3Obj) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -40,7 +40,7 @@ TEST_F(MindDataTestPipeline, TestRescaleSucess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| auto image = row["image"]; | |||
| @@ -62,7 +62,7 @@ TEST_F(MindDataTestPipeline, TestRescaleSucess1) { | |||
| // Iterate the dataset and get each row1 | |||
| std::unordered_map<std::string, mindspore::MSTensor> row1; | |||
| iter1->GetNextRow(&row1); | |||
| ASSERT_OK(iter1->GetNextRow(&row1)); | |||
| auto image1 = row1["image"]; | |||
| @@ -93,14 +93,14 @@ TEST_F(MindDataTestPipeline, TestRescaleSucess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 1); | |||
| @@ -141,14 +141,14 @@ TEST_F(MindDataTestPipeline, TestResize1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 24); | |||
| @@ -181,14 +181,14 @@ TEST_F(MindDataTestPipeline, TestResizeWithBBoxSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -216,14 +216,14 @@ TEST_F(MindDataTestPipeline, TestRGB2GRAYSucess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 1); | |||
| @@ -61,14 +61,14 @@ TEST_F(MindDataTestPipeline, TestRandomSelectSubpolicySuccess1Shr) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 7); | |||
| @@ -114,14 +114,14 @@ TEST_F(MindDataTestPipeline, TestRandomSelectSubpolicySuccess2Auto) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 7); | |||
| @@ -171,14 +171,14 @@ TEST_F(MindDataTestPipeline, TestRandomSelectSubpolicySuccess3Obj) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 7); | |||
| @@ -223,14 +223,14 @@ TEST_F(MindDataTestPipeline, TestRandomSelectSubpolicySuccess4MultiPolicy) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 7); | |||
| @@ -99,14 +99,14 @@ TEST_F(MindDataTestPipeline, TestRandomAffineSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -147,14 +147,14 @@ TEST_F(MindDataTestPipeline, TestRandomAffineSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -199,14 +199,14 @@ TEST_F(MindDataTestPipeline, TestRandomColor) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -263,14 +263,14 @@ TEST_F(MindDataTestPipeline, TestRandomColorAdjust) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -320,14 +320,14 @@ TEST_F(MindDataTestPipeline, TestRandomCropSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -466,7 +466,7 @@ TEST_F(MindDataTestPipeline, TestRandomCropWithBboxSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -475,7 +475,7 @@ TEST_F(MindDataTestPipeline, TestRandomCropWithBboxSuccess) { | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0], 128); | |||
| EXPECT_EQ(image.Shape()[1], 128); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -596,14 +596,14 @@ TEST_F(MindDataTestPipeline, TestRandomHorizontalFlipWithBBoxSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -644,14 +644,14 @@ TEST_F(MindDataTestPipeline, TestRandomHorizontalAndVerticalFlip) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -692,14 +692,14 @@ TEST_F(MindDataTestPipeline, TestRandomPosterizeSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -740,14 +740,14 @@ TEST_F(MindDataTestPipeline, TestRandomPosterizeSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -778,7 +778,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -786,7 +786,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeSuccess1) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 66, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 5); | |||
| @@ -822,7 +822,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -830,7 +830,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeSuccess2) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 66 && image.Shape()[1] == 77, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 6); | |||
| @@ -865,7 +865,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeWithBBoxSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -873,7 +873,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeWithBBoxSuccess1) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 88, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -912,7 +912,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeWithBBoxSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -920,7 +920,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizeWithBBoxSuccess2) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 88 && image.Shape()[1] == 99, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 8); | |||
| @@ -952,7 +952,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -960,7 +960,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropSuccess1) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 5 && image.Shape()[1] == 5, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -992,7 +992,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -1000,7 +1000,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropSuccess2) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 5 && image.Shape()[1] == 10, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -1114,7 +1114,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropWithBBoxSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -1122,7 +1122,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropWithBBoxSuccess1) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 5 && image.Shape()[1] == 5, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -1158,7 +1158,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropWithBBoxSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -1166,7 +1166,7 @@ TEST_F(MindDataTestPipeline, TestRandomResizedCropWithBBoxSuccess2) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 5 && image.Shape()[1] == 10, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -1290,14 +1290,14 @@ TEST_F(MindDataTestPipeline, TestRandomRotation) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -1424,14 +1424,14 @@ TEST_F(MindDataTestPipeline, TestRandomSharpness) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -1464,14 +1464,14 @@ TEST_F(MindDataTestPipeline, TestRandomSolarizeSucess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -1502,14 +1502,14 @@ TEST_F(MindDataTestPipeline, TestRandomSolarizeSucess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 10); | |||
| @@ -1540,14 +1540,14 @@ TEST_F(MindDataTestPipeline, TestRandomVerticalFlipWithBBoxSuccess) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 3); | |||
| @@ -51,7 +51,7 @@ TEST_F(MindDataTestPipeline, TestSoftDvppDecodeRandomCropResizeJpegSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -59,7 +59,7 @@ TEST_F(MindDataTestPipeline, TestSoftDvppDecodeRandomCropResizeJpegSuccess1) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 500 && image.Shape()[1] == 500, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 4); | |||
| @@ -93,7 +93,7 @@ TEST_F(MindDataTestPipeline, TestSoftDvppDecodeRandomCropResizeJpegSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| @@ -101,7 +101,7 @@ TEST_F(MindDataTestPipeline, TestSoftDvppDecodeRandomCropResizeJpegSuccess2) { | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| EXPECT_EQ(image.Shape()[0] == 500 && image.Shape()[1] == 600, true); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 6); | |||
| @@ -137,14 +137,14 @@ TEST_F(MindDataTestPipeline, TestSoftDvppDecodeResizeJpegSuccess1) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 12); | |||
| @@ -175,14 +175,14 @@ TEST_F(MindDataTestPipeline, TestSoftDvppDecodeResizeJpegSuccess2) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 2); | |||
| @@ -58,14 +58,14 @@ TEST_F(MindDataTestPipeline, TestUniformAugWithOps1Shr) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -106,14 +106,14 @@ TEST_F(MindDataTestPipeline, TestUniformAugWithOps2Auto) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -159,14 +159,14 @@ TEST_F(MindDataTestPipeline, TestUniformAugWithOps3Obj) { | |||
| // Iterate the dataset and get each row | |||
| std::unordered_map<std::string, mindspore::MSTensor> row; | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| uint64_t i = 0; | |||
| while (row.size() != 0) { | |||
| i++; | |||
| auto image = row["image"]; | |||
| MS_LOG(INFO) << "Tensor image shape: " << image.Shape(); | |||
| iter->GetNextRow(&row); | |||
| ASSERT_OK(iter->GetNextRow(&row)); | |||
| } | |||
| EXPECT_EQ(i, 20); | |||
| @@ -72,17 +72,17 @@ TEST_F(MindDataTestCelebaDataset, TestSequentialCeleba) { | |||
| EXPECT_TRUE(false); | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tersor_map; | |||
| di.GetNextAsMap(&tersor_map); | |||
| TensorMap tensor_map; | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| while (tersor_map.size() != 0) { | |||
| while (tensor_map.size() != 0) { | |||
| uint32_t label; | |||
| for (int index = 0; index < 40; index++) { | |||
| tersor_map["attr"]->GetItemAt<uint32_t>(&label, {index}); | |||
| tensor_map["attr"]->GetItemAt<uint32_t>(&label, {index}); | |||
| EXPECT_TRUE(expect_labels[count][index] == label); | |||
| } | |||
| count++; | |||
| di.GetNextAsMap(&tersor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(count == 4); | |||
| } | |||
| @@ -119,17 +119,17 @@ TEST_F(MindDataTestCelebaDataset, TestCelebaRepeat) { | |||
| EXPECT_TRUE(false); | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tersor_map; | |||
| di.GetNextAsMap(&tersor_map); | |||
| TensorMap tensor_map; | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| while (tersor_map.size() != 0) { | |||
| while (tensor_map.size() != 0) { | |||
| uint32_t label; | |||
| for (int index = 0; index < 40; index++) { | |||
| tersor_map["attr"]->GetItemAt<uint32_t>(&label, {index}); | |||
| tensor_map["attr"]->GetItemAt<uint32_t>(&label, {index}); | |||
| EXPECT_TRUE(expect_labels[count][index] == label); | |||
| } | |||
| count++; | |||
| di.GetNextAsMap(&tersor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(count == 8); | |||
| } | |||
| @@ -151,17 +151,17 @@ TEST_F(MindDataTestCelebaDataset, TestSubsetRandomSamplerCeleba) { | |||
| EXPECT_TRUE(false); | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tersor_map; | |||
| di.GetNextAsMap(&tersor_map); | |||
| TensorMap tensor_map; | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| while (tersor_map.size() != 0) { | |||
| while (tensor_map.size() != 0) { | |||
| uint32_t label; | |||
| for (int index = 0; index < 40; index++) { | |||
| tersor_map["attr"]->GetItemAt<uint32_t>(&label, {index}); | |||
| tensor_map["attr"]->GetItemAt<uint32_t>(&label, {index}); | |||
| EXPECT_TRUE(expect_labels[count][index] == label); | |||
| } | |||
| count++; | |||
| di.GetNextAsMap(&tersor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(count == 1); | |||
| } | |||
| @@ -75,7 +75,7 @@ TEST_F(MindDataTestCifarOp, TestSequentialSamplerCifar10) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| uint32_t label = 0; | |||
| @@ -84,7 +84,7 @@ TEST_F(MindDataTestCifarOp, TestSequentialSamplerCifar10) { | |||
| tensor_map["label"]->GetItemAt<uint32_t>(&label, {}); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 100); | |||
| } | |||
| @@ -104,7 +104,7 @@ TEST_F(MindDataTestCifarOp, TestRandomSamplerCifar10) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| uint32_t label = 0; | |||
| @@ -112,7 +112,7 @@ TEST_F(MindDataTestCifarOp, TestRandomSamplerCifar10) { | |||
| tensor_map["label"]->GetItemAt<uint32_t>(&label, {}); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 12); | |||
| } | |||
| @@ -130,7 +130,7 @@ TEST_F(MindDataTestCifarOp, TestSequentialSamplerCifar100) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| uint32_t coarse = 0; | |||
| @@ -142,7 +142,7 @@ TEST_F(MindDataTestCifarOp, TestSequentialSamplerCifar100) { | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << " coarse:" | |||
| << coarse << " fine:" << fine << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 100); | |||
| } | |||
| @@ -94,7 +94,7 @@ TEST_F(MindDataTestImageFolderSampler, TestSequentialImageFolderWithRepeat) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -103,7 +103,7 @@ TEST_F(MindDataTestImageFolderSampler, TestSequentialImageFolderWithRepeat) { | |||
| EXPECT_TRUE(res[(i % 44) / 11] == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 88); | |||
| } | |||
| @@ -120,7 +120,7 @@ TEST_F(MindDataTestImageFolderSampler, TestRandomImageFolder) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -128,7 +128,7 @@ TEST_F(MindDataTestImageFolderSampler, TestRandomImageFolder) { | |||
| tensor_map["label"]->GetItemAt<int32_t>(&label, {}); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 44); | |||
| } | |||
| @@ -150,7 +150,7 @@ TEST_F(MindDataTestImageFolderSampler, TestRandomSamplerImageFolder) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -159,7 +159,7 @@ TEST_F(MindDataTestImageFolderSampler, TestRandomSamplerImageFolder) { | |||
| EXPECT_TRUE(res[i] == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 12); | |||
| } | |||
| @@ -186,7 +186,7 @@ TEST_F(MindDataTestImageFolderSampler, TestSequentialImageFolderWithRepeatBatch) | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| while (tensor_map.size() != 0) { | |||
| @@ -196,7 +196,7 @@ TEST_F(MindDataTestImageFolderSampler, TestSequentialImageFolderWithRepeatBatch) | |||
| MS_LOG(DEBUG) << "row: " << i << " " << tensor_map["image"]->shape() << " (*label):" << (*label) | |||
| << " *tensor_map[label]: " << *tensor_map["label"] << std::endl; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 8); | |||
| } | |||
| @@ -227,7 +227,7 @@ TEST_F(MindDataTestImageFolderSampler, TestSubsetRandomSamplerImageFolder) { | |||
| tensor_map["label"]->GetItemAt<int32_t>(&label, {}); | |||
| res[label]--; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_EQ(res[0], 0); | |||
| EXPECT_EQ(res[1], 0); | |||
| @@ -263,7 +263,7 @@ TEST_F(MindDataTestImageFolderSampler, TestWeightedRandomSamplerImageFolder) { | |||
| while (tensor_map.size() != 0) { | |||
| tensor_map["label"]->GetItemAt<int32_t>(&label, {}); | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 12); | |||
| } | |||
| @@ -285,7 +285,7 @@ TEST_F(MindDataTestImageFolderSampler, TestImageFolderClassIndex) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -294,7 +294,7 @@ TEST_F(MindDataTestImageFolderSampler, TestImageFolderClassIndex) { | |||
| EXPECT_TRUE(label == res[i / 11]); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 22); | |||
| } | |||
| @@ -326,7 +326,7 @@ TEST_F(MindDataTestImageFolderSampler, TestDistributedSampler) { | |||
| EXPECT_EQ(i % 4, label); | |||
| MS_LOG(DEBUG) << "row:" << i << "\tlabel:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 16); | |||
| } | |||
| @@ -346,7 +346,7 @@ TEST_F(MindDataTestImageFolderSampler, TestPKSamplerImageFolder) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -355,7 +355,7 @@ TEST_F(MindDataTestImageFolderSampler, TestPKSamplerImageFolder) { | |||
| EXPECT_TRUE(res[i] == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 12); | |||
| } | |||
| @@ -380,7 +380,7 @@ TEST_F(MindDataTestImageFolderSampler, TestImageFolderDecode) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -391,7 +391,7 @@ TEST_F(MindDataTestImageFolderSampler, TestImageFolderDecode) { | |||
| TensorShape({2268, 4032, 3})); // verify shapes are correct after decode | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 20); | |||
| } | |||
| @@ -421,7 +421,7 @@ TEST_F(MindDataTestImageFolderSampler, TestImageFolderSharding1) { | |||
| EXPECT_EQ(labels[i], label); | |||
| MS_LOG(DEBUG) << "row:" << i << "\tlabel:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 5); | |||
| } | |||
| @@ -451,7 +451,7 @@ TEST_F(MindDataTestImageFolderSampler, TestImageFolderSharding2) { | |||
| EXPECT_EQ(labels[i], label); | |||
| MS_LOG(DEBUG) << "row:" << i << "\tlabel:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 11); | |||
| } | |||
| @@ -236,7 +236,7 @@ TEST_F(MindDataTestCallback, TestMultiEpochCallback) { | |||
| TensorMap tensor_map; | |||
| size_t num_epochs = 2; | |||
| for (int ep_num = 0; ep_num < num_epochs; ++ep_num) { | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| while (tensor_map.size() != 0) { | |||
| @@ -301,7 +301,7 @@ TEST_F(MindDataTestCallback, TestSelectedCallback) { | |||
| TensorMap tensor_map; | |||
| size_t num_epochs = 2; | |||
| for (int ep_num = 0; ep_num < num_epochs; ++ep_num) { | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| while (tensor_map.size() != 0) { | |||
| @@ -77,7 +77,7 @@ TEST_F(MindDataTestManifest, TestSequentialManifestWithRepeat) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -86,7 +86,7 @@ TEST_F(MindDataTestManifest, TestSequentialManifestWithRepeat) { | |||
| EXPECT_TRUE(res[i] == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 4); | |||
| } | |||
| @@ -114,7 +114,7 @@ TEST_F(MindDataTestManifest, TestSubsetRandomSamplerManifest) { | |||
| while (tensor_map.size() != 0) { | |||
| tensor_map["label"]->GetItemAt<int32_t>(&label, {}); | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_EQ(label, 1); | |||
| } | |||
| EXPECT_TRUE(i == 1); | |||
| @@ -137,7 +137,7 @@ TEST_F(MindDataTestManifest, MindDataTestManifestClassIndex) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -146,7 +146,7 @@ TEST_F(MindDataTestManifest, MindDataTestManifestClassIndex) { | |||
| EXPECT_TRUE(label == res[i]); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 2); | |||
| } | |||
| @@ -170,7 +170,7 @@ TEST_F(MindDataTestManifest, MindDataTestManifestNumSamples) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -179,7 +179,7 @@ TEST_F(MindDataTestManifest, MindDataTestManifestNumSamples) { | |||
| EXPECT_TRUE(0 == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 4); | |||
| } | |||
| @@ -199,7 +199,7 @@ TEST_F(MindDataTestManifest, MindDataTestManifestEval) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -208,7 +208,7 @@ TEST_F(MindDataTestManifest, MindDataTestManifestEval) { | |||
| EXPECT_TRUE(0 == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 1); | |||
| } | |||
| @@ -634,7 +634,7 @@ TEST_F(MindDataTestMapOp, ImageFolder_Decode_Repeat_Resize) { | |||
| // Start the loop of reading tensors from our pipeline | |||
| DatasetIterator di(my_tree_); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -646,7 +646,7 @@ TEST_F(MindDataTestMapOp, ImageFolder_Decode_Repeat_Resize) { | |||
| EXPECT_TRUE(img_class[(i % 44) / 11] == label); | |||
| // Dump all the image into string, to be used as a comparison later. | |||
| result.append((char *)tensor_map["image"]->GetBuffer(), (int64_t)tensor_map["image"]->Size()); | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| i++; | |||
| } | |||
| EXPECT_TRUE(i == 88); | |||
| @@ -684,7 +684,7 @@ TEST_F(MindDataTestMapOp, ImageFolder_Decode_Repeat_Resize) { | |||
| // Start the loop of reading tensors from our pipeline | |||
| DatasetIterator di2(my_tree_2); | |||
| di2.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di2.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| i = 0; | |||
| label = 0; | |||
| @@ -694,7 +694,7 @@ TEST_F(MindDataTestMapOp, ImageFolder_Decode_Repeat_Resize) { | |||
| MS_LOG(DEBUG) << "row:" << i << "\tlabel:" << label << "\n"; | |||
| EXPECT_TRUE(img_class[(i % 44) / 11] == label); | |||
| result2.append((char *)tensor_map["image"]->GetBuffer(), (int64_t)tensor_map["image"]->Size()); | |||
| di2.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di2.GetNextAsMap(&tensor_map)); | |||
| i++; | |||
| } | |||
| EXPECT_TRUE(i == 88); | |||
| @@ -747,7 +747,7 @@ TEST_F(MindDataTestMapOp, ImageFolder_Decode_Repeat_Resize_NoInputColumns) { | |||
| // Start the loop of reading tensors from our pipeline | |||
| DatasetIterator di(my_tree_); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| int32_t label = 0; | |||
| @@ -756,7 +756,7 @@ TEST_F(MindDataTestMapOp, ImageFolder_Decode_Repeat_Resize_NoInputColumns) { | |||
| while (tensor_map.size() != 0) { | |||
| tensor_map["label"]->GetItemAt<int32_t>(&label, {}); | |||
| EXPECT_TRUE(img_class[(i % 44) / 11] == label); | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| i++; | |||
| } | |||
| EXPECT_TRUE(i == 88); | |||
| @@ -92,7 +92,7 @@ TEST_F(MindDataTestMnistSampler, TestSequentialMnistWithRepeat) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| uint32_t label = 0; | |||
| @@ -101,7 +101,7 @@ TEST_F(MindDataTestMnistSampler, TestSequentialMnistWithRepeat) { | |||
| EXPECT_TRUE(res[i % 10] == label); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << label << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 20); | |||
| } | |||
| @@ -130,7 +130,7 @@ TEST_F(MindDataTestMnistSampler, TestSequentialImageFolderWithRepeatBatch) { | |||
| } else { | |||
| DatasetIterator di(tree); | |||
| TensorMap tensor_map; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| EXPECT_TRUE(rc.IsOk()); | |||
| uint64_t i = 0; | |||
| while (tensor_map.size() != 0) { | |||
| @@ -139,7 +139,7 @@ TEST_F(MindDataTestMnistSampler, TestSequentialImageFolderWithRepeatBatch) { | |||
| EXPECT_TRUE((*label) == (*tensor_map["label"])); | |||
| MS_LOG(DEBUG) << "row: " << i << "\t" << tensor_map["image"]->shape() << "label:" << *tensor_map["label"] << "\n"; | |||
| i++; | |||
| di.GetNextAsMap(&tensor_map); | |||
| ASSERT_OK(di.GetNextAsMap(&tensor_map)); | |||
| } | |||
| EXPECT_TRUE(i == 4); | |||
| } | |||
| @@ -40,7 +40,7 @@ TEST_F(MindDataTestOptimizationPass, MindDataTestAutoWorkerPass) { | |||
| MS_LOG(INFO) << "Doing MindDataTestOptimizationPass-MindDataTestAutoWorkerPass."; | |||
| std::shared_ptr<SchemaObj> schema = std::make_shared<SchemaObj>(); | |||
| ASSERT_TRUE(schema->add_column("label", "uint32", {})); | |||
| ASSERT_OK(schema->add_column("label", "uint32", {})); | |||
| std::shared_ptr<Dataset> map_leaf = ImageFolder("dir")->SetNumWorkers(0); | |||
| std::shared_ptr<Dataset> nonmap_leaf = RandomData(44, schema)->SetNumWorkers(0); | |||
| std::shared_ptr<Dataset> batch = Zip({map_leaf, nonmap_leaf})->Batch(1)->SetNumWorkers(0); | |||