forked from mindspore-Ecosystem/mindspore
!12895 [MD] C++ testcases cleanup: for random tensor ops and transforms ops
From: @tina_mengting_zhang Reviewed-by: @mikef,@robingrosman Signed-off-by: @robingrosman
This commit is contained in:
Gitee
commit
569e679c66
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@ -12,7 +12,6 @@ SET(DE_UT_SRCS
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btree_test.cc
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buddy_test.cc
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build_vocab_test.cc
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c_api_affine_test.cc
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c_api_cache_test.cc
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c_api_dataset_album_test.cc
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c_api_dataset_cifar_test.cc
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@ -37,6 +36,7 @@ SET(DE_UT_SRCS
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c_api_text_vocab_test.cc
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c_api_transforms_test.cc
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c_api_vision_a_to_q_test.cc
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c_api_vision_affine_test.cc
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c_api_vision_bounding_box_augment_test.cc
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c_api_vision_random_subselect_policy_test.cc
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c_api_vision_random_test.cc
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@ -77,6 +77,7 @@ SET(DE_UT_SRCS
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ir_sampler_test.cc
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ir_tensor_op_fusion_pass_test.cc
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ir_tree_adapter_test.cc
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ir_vision_random_test.cc
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ir_vision_test.cc
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jieba_tokenizer_op_test.cc
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main_test.cc
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@ -57,18 +57,17 @@ TEST_F(MindDataTestPipeline, TestComposeSuccess) {
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uint64_t i = 0;
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while (row.size() != 0) {
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i++;
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// auto image = row["image"];
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// auto label = row["label"];
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// MS_LOG(INFO) << "Tensor image shape: " << image->shape();
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// MS_LOG(INFO) << "Label shape: " << label->shape();
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// EXPECT_EQ(image->shape()[0], 777);
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// EXPECT_EQ(image->shape()[1], 777);
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auto image = row["image"];
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auto label = row["label"];
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MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
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MS_LOG(INFO) << "Label shape: " << label.Shape();
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EXPECT_EQ(image.Shape()[0], 777);
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EXPECT_EQ(image.Shape()[1], 777);
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iter->GetNextRow(&row);
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}
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EXPECT_EQ(i, 3);
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// Manually terminate the pipeline
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iter->Stop();
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}
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@ -165,10 +164,12 @@ TEST_F(MindDataTestPipeline, TestDuplicateSuccess) {
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uint64_t i = 0;
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while (row.size() != 0) {
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i++;
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// auto image = row["image"];
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// auto image_copy = row["image_copy"];
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// MS_LOG(INFO) << "Tensor image shape: " << image->shape();
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// EXPECT_EQ(*image, *image_copy);
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// FIXME
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// auto image = row["image"];
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// auto image_copy = row["image_copy"];
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// MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
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// auto n = memcmp(&image, &image_copy, image.DataSize());
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// EXPECT_EQ(n, 0);
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iter->GetNextRow(&row);
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}
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@ -179,6 +180,7 @@ TEST_F(MindDataTestPipeline, TestDuplicateSuccess) {
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}
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TEST_F(MindDataTestPipeline, TestOneHotSuccess1) {
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MS_LOG(INFO) << "Doing MindDataTestPipeline-TestOneHotSuccess1.";
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// Testing CutMixBatch on a batch of CHW images
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// Create a Cifar10 Dataset
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std::string folder_path = datasets_root_path_ + "/testCifar10Data/";
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@ -188,7 +190,6 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) {
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// Create objects for the tensor ops
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std::shared_ptr<TensorTransform> hwc_to_chw = std::make_shared<vision::HWC2CHW>();
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EXPECT_NE(hwc_to_chw, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({hwc_to_chw}, {"image"});
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@ -201,7 +202,6 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) {
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// Create objects for the tensor ops
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std::shared_ptr<TensorTransform> one_hot_op = std::make_shared<transforms::OneHot>(number_of_classes);
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EXPECT_NE(one_hot_op, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({one_hot_op}, {"label"});
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@ -209,7 +209,6 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) {
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std::shared_ptr<TensorTransform> cutmix_batch_op =
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std::make_shared<vision::CutMixBatch>(mindspore::dataset::ImageBatchFormat::kNCHW, 1.0, 1.0);
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EXPECT_NE(cutmix_batch_op, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({cutmix_batch_op}, {"image", "label"});
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@ -227,16 +226,15 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) {
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uint64_t i = 0;
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while (row.size() != 0) {
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i++;
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// auto image = row["image"];
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// auto label = row["label"];
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// MS_LOG(INFO) << "Tensor image shape: " << image->shape();
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// MS_LOG(INFO) << "Label shape: " << label->shape();
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// EXPECT_EQ(image->shape().AsVector().size() == 4 && batch_size == image->shape()[0] && 3 == image->shape()[1] &&
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// 32 == image->shape()[2] && 32 == image->shape()[3],
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// true);
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// EXPECT_EQ(label->shape().AsVector().size() == 2 && batch_size == label->shape()[0] &&
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// number_of_classes == label->shape()[1],
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// true);
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auto image = row["image"];
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auto label = row["label"];
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MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
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MS_LOG(INFO) << "Label shape: " << label.Shape();
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EXPECT_EQ(image.Shape().size() == 4 && batch_size == image.Shape()[0] && 3 == image.Shape()[1] &&
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32 == image.Shape()[2] && 32 == image.Shape()[3],
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true);
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EXPECT_EQ(label.Shape().size() == 2 && batch_size == label.Shape()[0] && number_of_classes == label.Shape()[1],
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true);
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iter->GetNextRow(&row);
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}
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@ -247,6 +245,7 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess1) {
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}
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TEST_F(MindDataTestPipeline, TestOneHotSuccess2) {
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MS_LOG(INFO) << "Doing MindDataTestPipeline-TestOneHotSuccess2.";
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// Create a Cifar10 Dataset
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std::string folder_path = datasets_root_path_ + "/testCifar10Data/";
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std::shared_ptr<Dataset> ds = Cifar10(folder_path, "all", std::make_shared<RandomSampler>(false, 10));
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@ -259,14 +258,12 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess2) {
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// Create objects for the tensor ops
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std::shared_ptr<TensorTransform> one_hot_op = std::make_shared<transforms::OneHot>(10);
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EXPECT_NE(one_hot_op, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({one_hot_op}, {"label"});
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EXPECT_NE(ds, nullptr);
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std::shared_ptr<TensorTransform> mixup_batch_op = std::make_shared<vision::MixUpBatch>(2.0);
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EXPECT_NE(mixup_batch_op, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({mixup_batch_op}, {"image", "label"});
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@ -284,8 +281,8 @@ TEST_F(MindDataTestPipeline, TestOneHotSuccess2) {
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uint64_t i = 0;
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while (row.size() != 0) {
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i++;
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// auto image = row["image"];
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// MS_LOG(INFO) << "Tensor image shape: " << image->shape();
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auto image = row["image"];
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MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
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iter->GetNextRow(&row);
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}
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@ -305,7 +302,6 @@ TEST_F(MindDataTestPipeline, TestOneHotFail1) {
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// incorrect num_class
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std::shared_ptr<TensorTransform> one_hot_op = std::make_shared<transforms::OneHot>(0);
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EXPECT_NE(one_hot_op, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({one_hot_op}, {"label"});
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@ -326,7 +322,6 @@ TEST_F(MindDataTestPipeline, TestOneHotFail2) {
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// incorrect num_class
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std::shared_ptr<TensorTransform> one_hot_op = std::make_shared<transforms::OneHot>(-5);
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EXPECT_NE(one_hot_op, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({one_hot_op}, {"label"});
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@ -365,10 +360,10 @@ TEST_F(MindDataTestPipeline, TestRandomApplySuccess) {
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uint64_t i = 0;
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while (row.size() != 0) {
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i++;
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// auto image = row["image"];
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// auto label = row["label"];
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// MS_LOG(INFO) << "Tensor image shape: " << image->shape();
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// MS_LOG(INFO) << "Label shape: " << label->shape();
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auto image = row["image"];
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auto label = row["label"];
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MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
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MS_LOG(INFO) << "Label shape: " << label.Shape();
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iter->GetNextRow(&row);
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}
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@ -590,17 +585,16 @@ TEST_F(MindDataTestPipeline, TestTypeCastSuccess) {
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iter->GetNextRow(&row);
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// Check original data type of dataset
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// auto image = row["image"];
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// std::string ori_type = image->type().ToString();
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// MS_LOG(INFO) << "Original data type: " << ori_type;
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// EXPECT_NE(ori_type.c_str(), "uint8");
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auto image = row["image"];
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auto ori_type = image.DataType();
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MS_LOG(INFO) << "Original data type id: " << ori_type;
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EXPECT_EQ(ori_type, mindspore::DataType(mindspore::TypeId::kNumberTypeUInt8));
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// Manually terminate the pipeline
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iter->Stop();
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// Create objects for the tensor ops
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std::shared_ptr<TensorTransform> type_cast = std::make_shared<transforms::TypeCast>("uint16");
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EXPECT_NE(type_cast, nullptr);
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// Create a Map operation on ds
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std::shared_ptr<Dataset> ds2 = ds->Map({type_cast}, {"image"});
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@ -613,10 +607,10 @@ TEST_F(MindDataTestPipeline, TestTypeCastSuccess) {
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// Check current data type of dataset
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iter2->GetNextRow(&row);
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// auto image2 = row["image"];
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// std::string cur_type = image2->type().ToString();
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// MS_LOG(INFO) << "Current data type: " << cur_type;
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// EXPECT_NE(cur_type.c_str(), "uint16");
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auto image2 = row["image"];
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auto cur_type = image2.DataType();
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MS_LOG(INFO) << "Current data type id: " << cur_type;
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EXPECT_EQ(cur_type, mindspore::DataType(mindspore::TypeId::kNumberTypeUInt16));
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// Manually terminate the pipeline
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iter2->Stop();
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@ -632,7 +626,6 @@ TEST_F(MindDataTestPipeline, TestTypeCastFail) {
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// incorrect data type
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std::shared_ptr<TensorTransform> type_cast = std::make_shared<transforms::TypeCast>("char");
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EXPECT_NE(type_cast, nullptr);
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// Create a Map operation on ds
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ds = ds->Map({type_cast}, {"image", "label"});
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@ -23,7 +23,7 @@ using mindspore::dataset::InterpolationMode;
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using mindspore::dataset::Tensor;
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class MindDataTestPipeline : public UT::DatasetOpTesting {
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protected:
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protected:
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};
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TEST_F(MindDataTestPipeline, TestAffineAPI) {
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@ -94,4 +94,3 @@ TEST_F(MindDataTestPipeline, TestAffineAPIFail) {
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std::shared_ptr<Iterator> iter = ds->CreateIterator();
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EXPECT_EQ(iter, nullptr);
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}
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File diff suppressed because it is too large
Load Diff
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@ -0,0 +1,242 @@
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/**
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* Copyright 2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <memory>
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#include "common/common.h"
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#include "minddata/dataset/kernels/ir/vision/vision_ir.h"
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using namespace mindspore::dataset;
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class MindDataTestIRVision : public UT::DatasetOpTesting {
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public:
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MindDataTestIRVision() = default;
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};
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TEST_F(MindDataTestIRVision, TestRandomColorIRFail) {
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MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomColorIRFail.";
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// Testing invalid lower bound > upper bound
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std::shared_ptr<TensorOperation> random_color1(new vision::RandomColorOperation(1.0, 0.1));
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Status rc1 = random_color1->ValidateParams();
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EXPECT_ERROR(rc1);
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// Testing invalid negative lower bound
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std::shared_ptr<TensorOperation> random_color2(new vision::RandomColorOperation(-0.5, 0.5));
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Status rc2 = random_color2->ValidateParams();
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EXPECT_ERROR(rc2);
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}
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TEST_F(MindDataTestIRVision, TestRandomColorAdjustIRFail) {
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MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomColorAdjustIRFail.";
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// Testing invalid brightness out of range
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std::shared_ptr<TensorOperation> random_color_adjust1(
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new vision::RandomColorAdjustOperation({-1.0}, {0.0}, {0.0}, {0.0}));
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Status rc1 = random_color_adjust1->ValidateParams();
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EXPECT_ERROR(rc1);
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// Testing invalid contrast out of range
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std::shared_ptr<TensorOperation> random_color_adjust2(
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new vision::RandomColorAdjustOperation({1.0}, {-0.1}, {0.0}, {0.0}));
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Status rc2 = random_color_adjust2->ValidateParams();
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EXPECT_ERROR(rc2);
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// Testing invalid saturation out of range
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std::shared_ptr<TensorOperation> random_color_adjust3(
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new vision::RandomColorAdjustOperation({0.0}, {0.0}, {-0.2}, {0.0}));
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Status rc3 = random_color_adjust3->ValidateParams();
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EXPECT_ERROR(rc3);
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// Testing invalid hue out of range
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std::shared_ptr<TensorOperation> random_color_adjust4(
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new vision::RandomColorAdjustOperation({0.0}, {0.0}, {0.0}, {-0.6}));
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Status rc4 = random_color_adjust4->ValidateParams();
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EXPECT_ERROR(rc4);
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// Testing invalid hue out of range
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std::shared_ptr<TensorOperation> random_color_adjust5(
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new vision::RandomColorAdjustOperation({0.0}, {0.0}, {0.0}, {-0.5, 0.6}));
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Status rc5 = random_color_adjust5->ValidateParams();
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EXPECT_ERROR(rc5);
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// Testing invalid hue
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std::shared_ptr<TensorOperation> random_color_adjust6(
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new vision::RandomColorAdjustOperation({0.0}, {0.0}, {0.0}, {0.51}));
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Status rc6 = random_color_adjust4->ValidateParams();
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EXPECT_ERROR(rc6);
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}
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TEST_F(MindDataTestIRVision, TestRandomHorizontalFlipIRFail) {
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MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomHorizontalFlipIRFail.";
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// Testing invalid negative input
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std::shared_ptr<TensorOperation> random_horizontal_flip1(new vision::RandomHorizontalFlipOperation(-0.5));
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Status rc1 = random_horizontal_flip1->ValidateParams();
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EXPECT_ERROR(rc1);
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// Testing invalid >1 input
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std::shared_ptr<TensorOperation> random_horizontal_flip2(new vision::RandomHorizontalFlipOperation(2));
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Status rc2 = random_horizontal_flip2->ValidateParams();
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EXPECT_ERROR(rc2);
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}
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TEST_F(MindDataTestIRVision, TestRandomHorizontalFlipWithBBoxIRFail) {
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MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomHorizontalFlipWithBBoxIRFail.";
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// Testing invalid negative input
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std::shared_ptr<TensorOperation> random_horizontal_flip_bbox1(
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new vision::RandomHorizontalFlipWithBBoxOperation(-1.0));
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Status rc1 = random_horizontal_flip_bbox1->ValidateParams();
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EXPECT_ERROR(rc1);
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// Testing invalid >1 input
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std::shared_ptr<TensorOperation> random_horizontal_flip_bbox2(new vision::RandomHorizontalFlipWithBBoxOperation(2.0));
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Status rc2 = random_horizontal_flip_bbox2->ValidateParams();
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EXPECT_ERROR(rc2);
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}
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TEST_F(MindDataTestIRVision, TestRandomPosterizeIRFail) {
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MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomPosterizeIRFail.";
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// Testing invalid max > 8
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std::shared_ptr<TensorOperation> random_posterize1(new vision::RandomPosterizeOperation({1, 9}));
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Status rc1 = random_posterize1->ValidateParams();
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EXPECT_ERROR(rc1);
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// Testing invalid min < 1
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std::shared_ptr<TensorOperation> random_posterize2(new vision::RandomPosterizeOperation({0, 8}));
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Status rc2 = random_posterize2->ValidateParams();
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EXPECT_ERROR(rc2);
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// Testing invalid min > max
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std::shared_ptr<TensorOperation> random_posterize3(new vision::RandomPosterizeOperation({8, 1}));
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Status rc3 = random_posterize3->ValidateParams();
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EXPECT_ERROR(rc3);
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// Testing invalid empty input
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std::shared_ptr<TensorOperation> random_posterize4(new vision::RandomPosterizeOperation({}));
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Status rc4 = random_posterize4->ValidateParams();
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EXPECT_ERROR(rc4);
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}
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TEST_F(MindDataTestIRVision, TestRandomResizeIRFail) {
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MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomResizeIRFail.";
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// Testing invalid: size must only contain positive integers
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std::shared_ptr<TensorOperation> random_resize1(new vision::RandomResizeOperation({-66, 77}));
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Status rc1 = random_resize1->ValidateParams();
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EXPECT_ERROR(rc1);
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// Testing invalid: size must only contain positive integers
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std::shared_ptr<TensorOperation> random_resize2(new vision::RandomResizeOperation({0, 77}));
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Status rc2 = random_resize2->ValidateParams();
|
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EXPECT_ERROR(rc2);
|
||||
|
||||
// Testing invalid: size must be a vector of one or two values
|
||||
std::shared_ptr<TensorOperation> random_resize3(new vision::RandomResizeOperation({1, 2, 3}));
|
||||
Status rc3 = random_resize3->ValidateParams();
|
||||
EXPECT_ERROR(rc3);
|
||||
|
||||
// Testing invalid: size must be a vector of one or two values
|
||||
std::shared_ptr<TensorOperation> random_resize4(new vision::RandomResizeOperation({}));
|
||||
Status rc4 = random_resize4->ValidateParams();
|
||||
EXPECT_ERROR(rc4);
|
||||
}
|
||||
|
||||
TEST_F(MindDataTestIRVision, TestRandomResizeWithBBoxIRFail) {
|
||||
MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomResizeWithBBoxIRFail.";
|
||||
|
||||
// Testing invalid: size must only contain positive integers
|
||||
std::shared_ptr<TensorOperation> random_resize_with_bbox1(new vision::RandomResizeWithBBoxOperation({-66, 77}));
|
||||
Status rc1 = random_resize_with_bbox1->ValidateParams();
|
||||
EXPECT_ERROR(rc1);
|
||||
|
||||
// Testing invalid: size must be a vector of one or two values
|
||||
std::shared_ptr<TensorOperation> random_resize_with_bbox2(new vision::RandomResizeWithBBoxOperation({1, 2, 3}));
|
||||
Status rc2 = random_resize_with_bbox2->ValidateParams();
|
||||
EXPECT_ERROR(rc2);
|
||||
|
||||
// Testing invalid: size must be a vector of one or two values
|
||||
std::shared_ptr<TensorOperation> random_resize_with_bbox3(new vision::RandomResizeWithBBoxOperation({}));
|
||||
Status rc3 = random_resize_with_bbox3->ValidateParams();
|
||||
EXPECT_ERROR(rc3);
|
||||
}
|
||||
|
||||
TEST_F(MindDataTestIRVision, TestRandomSharpnessIRFail) {
|
||||
MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomSharpnessIRFail.";
|
||||
|
||||
// Testing invalid empty degrees vector
|
||||
std::shared_ptr<TensorOperation> random_sharpness1(new vision::RandomSharpnessOperation({}));
|
||||
Status rc1 = random_sharpness1->ValidateParams();
|
||||
EXPECT_ERROR(rc1);
|
||||
|
||||
// Testing invalid single degree value
|
||||
std::shared_ptr<TensorOperation> random_sharpness2(new vision::RandomSharpnessOperation({0.1}));
|
||||
Status rc2 = random_sharpness2->ValidateParams();
|
||||
EXPECT_ERROR(rc2);
|
||||
}
|
||||
|
||||
TEST_F(MindDataTestIRVision, TestRandomSolarizeIRFail) {
|
||||
MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomSolarizeIRFail.";
|
||||
|
||||
// Testing invalid lower bound > upper bound
|
||||
std::shared_ptr<TensorOperation> random_solarize1(new vision::RandomSolarizeOperation({13, 1}));
|
||||
Status rc1 = random_solarize1->ValidateParams();
|
||||
EXPECT_ERROR(rc1);
|
||||
|
||||
// Testing invalid threshold must be a vector of two values
|
||||
std::shared_ptr<TensorOperation> random_solarize2(new vision::RandomSolarizeOperation({1, 2, 3}));
|
||||
Status rc2 = random_solarize2->ValidateParams();
|
||||
EXPECT_ERROR(rc2);
|
||||
|
||||
// Testing invalid threshold must be a vector of two values
|
||||
std::shared_ptr<TensorOperation> random_solarize3(new vision::RandomSolarizeOperation({1}));
|
||||
Status rc3 = random_solarize3->ValidateParams();
|
||||
EXPECT_ERROR(rc3);
|
||||
|
||||
// Testing invalid empty threshold
|
||||
std::shared_ptr<TensorOperation> random_solarize4(new vision::RandomSolarizeOperation({}));
|
||||
Status rc4 = random_solarize4->ValidateParams();
|
||||
EXPECT_ERROR(rc4);
|
||||
}
|
||||
|
||||
TEST_F(MindDataTestIRVision, TestRandomVerticalFlipIRFail) {
|
||||
MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomVerticalFlipIRFail.";
|
||||
|
||||
// Testing invalid negative input
|
||||
std::shared_ptr<TensorOperation> random_vertical_flip1(new vision::RandomVerticalFlipOperation(-0.5));
|
||||
Status rc1 = random_vertical_flip1->ValidateParams();
|
||||
EXPECT_ERROR(rc1);
|
||||
|
||||
// Testing invalid >1 input
|
||||
std::shared_ptr<TensorOperation> random_vertical_flip2(new vision::RandomVerticalFlipOperation(1.1));
|
||||
Status rc2 = random_vertical_flip2->ValidateParams();
|
||||
EXPECT_ERROR(rc2);
|
||||
}
|
||||
|
||||
TEST_F(MindDataTestIRVision, TestRandomVerticalFlipWithBBoxIRFail) {
|
||||
MS_LOG(INFO) << "Doing MindDataTestIRVision-TestRandomVerticalFlipWithBBoxIRFail.";
|
||||
|
||||
// Testing invalid negative input
|
||||
std::shared_ptr<TensorOperation> random_vertical_flip1(new vision::RandomVerticalFlipWithBBoxOperation(-0.5));
|
||||
Status rc1 = random_vertical_flip1->ValidateParams();
|
||||
EXPECT_ERROR(rc1);
|
||||
|
||||
// Testing invalid >1 input
|
||||
std::shared_ptr<TensorOperation> random_vertical_flip2(new vision::RandomVerticalFlipWithBBoxOperation(3.0));
|
||||
Status rc2 = random_vertical_flip2->ValidateParams();
|
||||
EXPECT_ERROR(rc2);
|
||||
}
|
||||
Loading…
Reference in New Issue