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reorganize headers and tests

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remove headers

fix iterator file

fix pr comments

fix new file
pull/4252/head
tony_liu2 5 years ago
parent 64b0feb7a2
commit deb1146474
10 changed files with 979 additions and 1196 deletions
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42
tests/ut/cpp/dataset/c_api_dataset_cifar_test.cc
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@ -13,37 +13,11 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <fstream>
#include <iostream>
#include <memory>
#include <vector>
#include <string>
#include "utils/log_adapter.h"
#include "utils/ms_utils.h"
#include "common/common.h"
#include "gtest/gtest.h"
#include "securec.h"
#include "minddata/dataset/include/datasets.h"
#include "minddata/dataset/include/status.h"
#include "minddata/dataset/include/transforms.h"
#include "minddata/dataset/include/iterator.h"
#include "minddata/dataset/core/constants.h"
#include "minddata/dataset/core/tensor_shape.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/include/samplers.h"
using namespace mindspore::dataset::api;
using mindspore::MsLogLevel::ERROR;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;
using mindspore::dataset::Tensor;
using mindspore::dataset::TensorShape;
using mindspore::dataset::TensorImpl;
using mindspore::dataset::DataType;
using mindspore::dataset::Status;
using mindspore::dataset::BorderType;
using mindspore::dataset::dsize_t;
class MindDataTestPipeline : public UT::DatasetOpTesting {
protected:
@ -83,14 +57,6 @@ TEST_F(MindDataTestPipeline, TestCifar10Dataset) {
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestCifar10DatasetFail1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCifar10DatasetFail1.";
// Create a Cifar10 Dataset
std::shared_ptr<Dataset> ds = Cifar10("", RandomSampler(false, 10));
EXPECT_EQ(ds, nullptr);
}
TEST_F(MindDataTestPipeline, TestCifar100Dataset) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCifar100Dataset.";
@ -133,3 +99,11 @@ TEST_F(MindDataTestPipeline, TestCifar100DatasetFail1) {
std::shared_ptr<Dataset> ds = Cifar100("", RandomSampler(false, 10));
EXPECT_EQ(ds, nullptr);
}
TEST_F(MindDataTestPipeline, TestCifar10DatasetFail1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCifar10DatasetFail1.";
// Create a Cifar10 Dataset
std::shared_ptr<Dataset> ds = Cifar10("", RandomSampler(false, 10));
EXPECT_EQ(ds, nullptr);
}

348
tests/ut/cpp/dataset/c_api_dataset_clue_test.cc
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152
tests/ut/cpp/dataset/c_api_dataset_coco_test.cc
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@ -13,49 +13,25 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <fstream>
#include <iostream>
#include <memory>
#include <vector>
#include <string>
#include "utils/log_adapter.h"
#include "utils/ms_utils.h"
#include "common/common.h"
#include "gtest/gtest.h"
#include "securec.h"
#include "minddata/dataset/include/datasets.h"
#include "minddata/dataset/include/status.h"
#include "minddata/dataset/include/transforms.h"
#include "minddata/dataset/include/iterator.h"
#include "minddata/dataset/core/constants.h"
#include "minddata/dataset/core/tensor_shape.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/include/samplers.h"
using namespace mindspore::dataset::api;
using mindspore::MsLogLevel::ERROR;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;
using mindspore::dataset::Tensor;
using mindspore::dataset::TensorShape;
using mindspore::dataset::TensorImpl;
using mindspore::dataset::DataType;
using mindspore::dataset::Status;
using mindspore::dataset::BorderType;
using mindspore::dataset::dsize_t;
class MindDataTestPipeline : public UT::DatasetOpTesting {
protected:
};
TEST_F(MindDataTestPipeline, TestCocoDetection) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoDetection.";
TEST_F(MindDataTestPipeline, TestCocoDefault) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoDefault.";
// Create a Coco Dataset
std::string folder_path = datasets_root_path_ + "/testCOCO/train";
std::string annotation_file = datasets_root_path_ + "/testCOCO/annotations/train.json";
std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file, "Detection", false, SequentialSampler(0, 6));
std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file);
EXPECT_NE(ds, nullptr);
// Create an iterator over the result of the above dataset
@ -67,28 +43,14 @@ TEST_F(MindDataTestPipeline, TestCocoDetection) {
std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
iter->GetNextRow(&row);
std::string expect_file[] = {"000000391895", "000000318219", "000000554625", "000000574769", "000000060623",
"000000309022"};
std::vector<std::vector<float>> expect_bbox_vector = {{10.0, 10.0, 10.0, 10.0, 70.0, 70.0, 70.0, 70.0},
{20.0, 20.0, 20.0, 20.0, 80.0, 80.0, 80.0, 80.0},
{30.0, 30.0, 30.0, 30.0}, {40.0, 40.0, 40.0, 40.0},
{50.0, 50.0, 50.0, 50.0}, {60.0, 60.0, 60.0, 60.0}};
std::vector<std::vector<uint32_t>> expect_catagoryid_list = {{1, 7}, {2, 8}, {3}, {4}, {5}, {6}};
uint64_t i = 0;
while (row.size() != 0) {
auto image = row["image"];
auto bbox = row["bbox"];
auto category_id = row["category_id"];
std::shared_ptr<Tensor> expect_image;
Tensor::CreateFromFile(folder_path + "/" + expect_file[i] + ".jpg", &expect_image);
EXPECT_EQ(*image, *expect_image);
std::shared_ptr<Tensor> expect_bbox;
dsize_t bbox_num = static_cast<dsize_t>(expect_bbox_vector[i].size() / 4);
Tensor::CreateFromVector(expect_bbox_vector[i], TensorShape({bbox_num, 4}), &expect_bbox);
EXPECT_EQ(*bbox, *expect_bbox);
std::shared_ptr<Tensor> expect_categoryid;
Tensor::CreateFromVector(expect_catagoryid_list[i], TensorShape({bbox_num, 1}), &expect_categoryid);
EXPECT_EQ(*category_id, *expect_categoryid);
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);
i++;
}
@ -99,13 +61,13 @@ TEST_F(MindDataTestPipeline, TestCocoDetection) {
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestCocoStuff) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoStuff.";
TEST_F(MindDataTestPipeline, TestCocoDetection) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoDetection.";
// Create a Coco Dataset
std::string folder_path = datasets_root_path_ + "/testCOCO/train";
std::string annotation_file = datasets_root_path_ + "/testCOCO/annotations/train.json";
std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file, "Stuff", false, SequentialSampler(0, 6));
std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file, "Detection", false, SequentialSampler(0, 6));
EXPECT_NE(ds, nullptr);
// Create an iterator over the result of the above dataset
@ -119,27 +81,26 @@ TEST_F(MindDataTestPipeline, TestCocoStuff) {
std::string expect_file[] = {"000000391895", "000000318219", "000000554625", "000000574769", "000000060623",
"000000309022"};
std::vector<std::vector<float>> expect_segmentation_vector =
{{10.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0,
70.0, 72.0, 73.0, 74.0, 75.0, -1.0, -1.0, -1.0, -1.0, -1.0},
{20.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0,
10.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, -1.0},
{40.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 40.0, 41.0, 42.0},
{50.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0},
{60.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0, 74.0},
{60.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0, 74.0}};
std::vector<std::vector<dsize_t>> expect_size = {{2, 10}, {2, 11}, {1, 12}, {1, 13}, {1, 14}, {2, 7}};
std::vector<std::vector<float>> expect_bbox_vector = {{10.0, 10.0, 10.0, 10.0, 70.0, 70.0, 70.0, 70.0},
{20.0, 20.0, 20.0, 20.0, 80.0, 80.0, 80.0, 80.0},
{30.0, 30.0, 30.0, 30.0}, {40.0, 40.0, 40.0, 40.0},
{50.0, 50.0, 50.0, 50.0}, {60.0, 60.0, 60.0, 60.0}};
std::vector<std::vector<uint32_t>> expect_catagoryid_list = {{1, 7}, {2, 8}, {3}, {4}, {5}, {6}};
uint64_t i = 0;
while (row.size() != 0) {
auto image = row["image"];
auto segmentation = row["segmentation"];
auto iscrowd = row["iscrowd"];
auto bbox = row["bbox"];
auto category_id = row["category_id"];
std::shared_ptr<Tensor> expect_image;
Tensor::CreateFromFile(folder_path + "/" + expect_file[i] + ".jpg", &expect_image);
EXPECT_EQ(*image, *expect_image);
std::shared_ptr<Tensor> expect_segmentation;
Tensor::CreateFromVector(expect_segmentation_vector[i], TensorShape(expect_size[i]), &expect_segmentation);
EXPECT_EQ(*segmentation, *expect_segmentation);
std::shared_ptr<Tensor> expect_bbox;
dsize_t bbox_num = static_cast<dsize_t>(expect_bbox_vector[i].size() / 4);
Tensor::CreateFromVector(expect_bbox_vector[i], TensorShape({bbox_num, 4}), &expect_bbox);
EXPECT_EQ(*bbox, *expect_bbox);
std::shared_ptr<Tensor> expect_categoryid;
Tensor::CreateFromVector(expect_catagoryid_list[i], TensorShape({bbox_num, 1}), &expect_categoryid);
EXPECT_EQ(*category_id, *expect_categoryid);
iter->GetNextRow(&row);
i++;
}
@ -150,6 +111,24 @@ TEST_F(MindDataTestPipeline, TestCocoStuff) {
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestCocoException) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoException.";
// Create a Coco Dataset
std::string folder_path = datasets_root_path_ + "/testCOCO/train";
std::string annotation_file = datasets_root_path_ + "/testCOCO/annotations/train.json";
std::string invalid_folder_path = "./NotExist";
std::string invalid_annotation_file = "./NotExistFile";
std::shared_ptr<Dataset> ds = Coco(invalid_folder_path, annotation_file);
EXPECT_EQ(ds, nullptr);
std::shared_ptr<Dataset> ds1 = Coco(folder_path, invalid_annotation_file);
EXPECT_EQ(ds1, nullptr);
std::shared_ptr<Dataset> ds2 = Coco(folder_path, annotation_file, "valid_mode");
EXPECT_EQ(ds2, nullptr);
}
TEST_F(MindDataTestPipeline, TestCocoKeypoint) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoKeypoint.";
// Create a Coco Dataset
@ -261,13 +240,13 @@ TEST_F(MindDataTestPipeline, TestCocoPanoptic) {
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestCocoDefault) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoDetection.";
TEST_F(MindDataTestPipeline, TestCocoStuff) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoStuff.";
// Create a Coco Dataset
std::string folder_path = datasets_root_path_ + "/testCOCO/train";
std::string annotation_file = datasets_root_path_ + "/testCOCO/annotations/train.json";
std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file);
std::shared_ptr<Dataset> ds = Coco(folder_path, annotation_file, "Stuff", false, SequentialSampler(0, 6));
EXPECT_NE(ds, nullptr);
// Create an iterator over the result of the above dataset
@ -279,14 +258,29 @@ TEST_F(MindDataTestPipeline, TestCocoDefault) {
std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
iter->GetNextRow(&row);
std::string expect_file[] = {"000000391895", "000000318219", "000000554625", "000000574769", "000000060623",
"000000309022"};
std::vector<std::vector<float>> expect_segmentation_vector =
{{10.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0,
70.0, 72.0, 73.0, 74.0, 75.0, -1.0, -1.0, -1.0, -1.0, -1.0},
{20.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0,
10.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, -1.0},
{40.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 48.0, 49.0, 40.0, 41.0, 42.0},
{50.0, 52.0, 53.0, 54.0, 55.0, 56.0, 57.0, 58.0, 59.0, 60.0, 61.0, 62.0, 63.0},
{60.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0, 74.0},
{60.0, 62.0, 63.0, 64.0, 65.0, 66.0, 67.0, 68.0, 69.0, 70.0, 71.0, 72.0, 73.0, 74.0}};
std::vector<std::vector<dsize_t>> expect_size = {{2, 10}, {2, 11}, {1, 12}, {1, 13}, {1, 14}, {2, 7}};
uint64_t i = 0;
while (row.size() != 0) {
auto image = row["image"];
auto bbox = row["bbox"];
auto category_id = row["category_id"];
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();
auto segmentation = row["segmentation"];
auto iscrowd = row["iscrowd"];
std::shared_ptr<Tensor> expect_image;
Tensor::CreateFromFile(folder_path + "/" + expect_file[i] + ".jpg", &expect_image);
EXPECT_EQ(*image, *expect_image);
std::shared_ptr<Tensor> expect_segmentation;
Tensor::CreateFromVector(expect_segmentation_vector[i], TensorShape(expect_size[i]), &expect_segmentation);
EXPECT_EQ(*segmentation, *expect_segmentation);
iter->GetNextRow(&row);
i++;
}
@ -296,21 +290,3 @@ TEST_F(MindDataTestPipeline, TestCocoDefault) {
// Manually terminate the pipeline
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestCocoException) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCocoDetection.";
// Create a Coco Dataset
std::string folder_path = datasets_root_path_ + "/testCOCO/train";
std::string annotation_file = datasets_root_path_ + "/testCOCO/annotations/train.json";
std::string invalid_folder_path = "./NotExist";
std::string invalid_annotation_file = "./NotExistFile";
std::shared_ptr<Dataset> ds = Coco(invalid_folder_path, annotation_file);
EXPECT_EQ(ds, nullptr);
std::shared_ptr<Dataset> ds1 = Coco(folder_path, invalid_annotation_file);
EXPECT_EQ(ds1, nullptr);
std::shared_ptr<Dataset> ds2 = Coco(folder_path, annotation_file, "valid_mode");
EXPECT_EQ(ds2, nullptr);
}

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tests/ut/cpp/dataset/c_api_dataset_filetext_test.cc
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tests/ut/cpp/dataset/c_api_dataset_iterator_test.cc
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tests/ut/cpp/dataset/c_api_dataset_ops_test.cc
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tests/ut/cpp/dataset/c_api_dataset_voc_test.cc
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@ -13,54 +13,30 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <fstream>
#include <iostream>
#include <memory>
#include <vector>
#include <string>
#include "utils/log_adapter.h"
#include "utils/ms_utils.h"
#include "common/common.h"
#include "gtest/gtest.h"
#include "securec.h"
#include "minddata/dataset/include/datasets.h"
#include "minddata/dataset/include/status.h"
#include "minddata/dataset/include/transforms.h"
#include "minddata/dataset/include/iterator.h"
#include "minddata/dataset/core/constants.h"
#include "minddata/dataset/core/tensor_shape.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/include/samplers.h"
#include "minddata/dataset/engine/datasetops/source/voc_op.h"
#include "minddata/dataset/include/datasets.h"
using namespace mindspore::dataset::api;
using mindspore::MsLogLevel::ERROR;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;
using mindspore::dataset::Tensor;
using mindspore::dataset::TensorShape;
using mindspore::dataset::TensorImpl;
using mindspore::dataset::DataType;
using mindspore::dataset::Status;
using mindspore::dataset::BorderType;
using mindspore::dataset::dsize_t;
class MindDataTestPipeline : public UT::DatasetOpTesting {
protected:
};
TEST_F(MindDataTestPipeline, TestVOCSegmentation) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCSegmentation.";
TEST_F(MindDataTestPipeline, TestVOCClassIndex) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCClassIndex.";
// Create a VOC Dataset
std::string folder_path = datasets_root_path_ + "/testVOC2012_2";
std::shared_ptr<Dataset> ds = VOC(folder_path, "Segmentation", "train", {}, false, SequentialSampler(0, 3));
EXPECT_NE(ds, nullptr);
std::map<std::string, int32_t> class_index;
class_index["car"] = 0;
class_index["cat"] = 1;
class_index["train"] = 9;
// Create a Repeat operation on ds
int32_t repeat_num = 2;
ds = ds->Repeat(repeat_num);
std::shared_ptr<Dataset> ds = VOC(folder_path, "Detection", "train", class_index, false, SequentialSampler(0, 6));
EXPECT_NE(ds, nullptr);
// Create an iterator over the result of the above dataset
@ -72,23 +48,20 @@ TEST_F(MindDataTestPipeline, TestVOCSegmentation) {
std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
iter->GetNextRow(&row);
// Check if VOCOp read correct images/targets
using Tensor = mindspore::dataset::Tensor;
std::string expect_file[] = {"32", "33", "39", "32", "33", "39"};
// Check if VOCOp read correct labels
// When we provide class_index, label of ["car","cat","train"] become [0,1,9]
std::shared_ptr<Tensor> expect_label;
Tensor::CreateFromMemory(TensorShape({1, 1}), DataType(DataType::DE_UINT32), nullptr, &expect_label);
uint32_t expect[] = {9, 9, 9, 1, 1, 0};
uint64_t i = 0;
while (row.size() != 0) {
auto image = row["image"];
auto target = row["target"];
auto label = row["label"];
MS_LOG(INFO) << "Tensor image shape: " << image->shape();
MS_LOG(INFO) << "Tensor target shape: " << target->shape();
std::shared_ptr<Tensor> expect_image;
Tensor::CreateFromFile(folder_path + "/JPEGImages/" + expect_file[i] + ".jpg", &expect_image);
EXPECT_EQ(*image, *expect_image);
std::shared_ptr<Tensor> expect_target;
Tensor::CreateFromFile(folder_path + "/SegmentationClass/" + expect_file[i] + ".png", &expect_target);
EXPECT_EQ(*target, *expect_target);
MS_LOG(INFO) << "Tensor label shape: " << label->shape();
expect_label->SetItemAt({0, 0}, expect[i]);
EXPECT_EQ(*label, *expect_label);
iter->GetNextRow(&row);
i++;
@ -100,33 +73,6 @@ TEST_F(MindDataTestPipeline, TestVOCSegmentation) {
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestVOCSegmentationError1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCSegmentationError1.";
// Create a VOC Dataset
std::map<std::string, int32_t> class_index;
class_index["car"] = 0;
std::string folder_path = datasets_root_path_ + "/testVOC2012_2";
std::shared_ptr<Dataset> ds = VOC(folder_path, "Segmentation", "train", class_index, false, RandomSampler(false, 6));
// Expect nullptr for segmentation task with class_index
EXPECT_EQ(ds, nullptr);
}
TEST_F(MindDataTestPipeline, TestVOCInvalidTaskOrMode) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCInvalidTaskOrMode.";
// Create a VOC Dataset
std::string folder_path = datasets_root_path_ + "/testVOC2012_2";
std::shared_ptr<Dataset> ds_1 = VOC(folder_path, "Classification", "train", {}, false, SequentialSampler(0, 3));
// Expect nullptr for invalid task
EXPECT_EQ(ds_1, nullptr);
std::shared_ptr<Dataset> ds_2 = VOC(folder_path, "Segmentation", "validation", {}, false, RandomSampler(false, 4));
// Expect nullptr for invalid mode
EXPECT_EQ(ds_2, nullptr);
}
TEST_F(MindDataTestPipeline, TestVOCDetection) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCDetection.";
@ -173,17 +119,31 @@ TEST_F(MindDataTestPipeline, TestVOCDetection) {
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestVOCClassIndex) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCClassIndex.";
TEST_F(MindDataTestPipeline, TestVOCInvalidTaskOrMode) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCInvalidTaskOrMode.";
// Create a VOC Dataset
std::string folder_path = datasets_root_path_ + "/testVOC2012_2";
std::map<std::string, int32_t> class_index;
class_index["car"] = 0;
class_index["cat"] = 1;
class_index["train"] = 9;
std::shared_ptr<Dataset> ds_1 = VOC(folder_path, "Classification", "train", {}, false, SequentialSampler(0, 3));
// Expect nullptr for invalid task
EXPECT_EQ(ds_1, nullptr);
std::shared_ptr<Dataset> ds = VOC(folder_path, "Detection", "train", class_index, false, SequentialSampler(0, 6));
std::shared_ptr<Dataset> ds_2 = VOC(folder_path, "Segmentation", "validation", {}, false, RandomSampler(false, 4));
// Expect nullptr for invalid mode
EXPECT_EQ(ds_2, nullptr);
}
TEST_F(MindDataTestPipeline, TestVOCSegmentation) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCSegmentation.";
// Create a VOC Dataset
std::string folder_path = datasets_root_path_ + "/testVOC2012_2";
std::shared_ptr<Dataset> ds = VOC(folder_path, "Segmentation", "train", {}, false, SequentialSampler(0, 3));
EXPECT_NE(ds, nullptr);
// Create a Repeat operation on ds
int32_t repeat_num = 2;
ds = ds->Repeat(repeat_num);
EXPECT_NE(ds, nullptr);
// Create an iterator over the result of the above dataset
@ -195,20 +155,23 @@ TEST_F(MindDataTestPipeline, TestVOCClassIndex) {
std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
iter->GetNextRow(&row);
// Check if VOCOp read correct labels
// When we provide class_index, label of ["car","cat","train"] become [0,1,9]
std::shared_ptr<Tensor> expect_label;
Tensor::CreateFromMemory(TensorShape({1, 1}), DataType(DataType::DE_UINT32), nullptr, &expect_label);
uint32_t expect[] = {9, 9, 9, 1, 1, 0};
// Check if VOCOp read correct images/targets
using Tensor = mindspore::dataset::Tensor;
std::string expect_file[] = {"32", "33", "39", "32", "33", "39"};
uint64_t i = 0;
while (row.size() != 0) {
auto image = row["image"];
auto label = row["label"];
auto target = row["target"];
MS_LOG(INFO) << "Tensor image shape: " << image->shape();
MS_LOG(INFO) << "Tensor label shape: " << label->shape();
expect_label->SetItemAt({0, 0}, expect[i]);
EXPECT_EQ(*label, *expect_label);
MS_LOG(INFO) << "Tensor target shape: " << target->shape();
std::shared_ptr<Tensor> expect_image;
Tensor::CreateFromFile(folder_path + "/JPEGImages/" + expect_file[i] + ".jpg", &expect_image);
EXPECT_EQ(*image, *expect_image);
std::shared_ptr<Tensor> expect_target;
Tensor::CreateFromFile(folder_path + "/SegmentationClass/" + expect_file[i] + ".png", &expect_target);
EXPECT_EQ(*target, *expect_target);
iter->GetNextRow(&row);
i++;
@ -219,3 +182,16 @@ TEST_F(MindDataTestPipeline, TestVOCClassIndex) {
// Manually terminate the pipeline
iter->Stop();
}
TEST_F(MindDataTestPipeline, TestVOCSegmentationError1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestVOCSegmentationError1.";
// Create a VOC Dataset
std::map<std::string, int32_t> class_index;
class_index["car"] = 0;
std::string folder_path = datasets_root_path_ + "/testVOC2012_2";
std::shared_ptr<Dataset> ds = VOC(folder_path, "Segmentation", "train", class_index, false, RandomSampler(false, 6));
// Expect nullptr for segmentation task with class_index
EXPECT_EQ(ds, nullptr);
}

57
tests/ut/cpp/dataset/c_api_datasets_test.cc
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@ -13,58 +13,17 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <fstream>
#include <iostream>
#include <memory>
#include <vector>
#include <string>
#include "utils/log_adapter.h"
#include "utils/ms_utils.h"
#include "common/common.h"
#include "gtest/gtest.h"
#include "securec.h"
#include "minddata/dataset/include/datasets.h"
#include "minddata/dataset/include/status.h"
#include "minddata/dataset/include/transforms.h"
#include "minddata/dataset/include/iterator.h"
#include "minddata/dataset/core/constants.h"
#include "minddata/dataset/core/tensor_shape.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/include/samplers.h"
using namespace mindspore::dataset::api;
using mindspore::MsLogLevel::ERROR;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;
using mindspore::dataset::Tensor;
using mindspore::dataset::TensorShape;
using mindspore::dataset::TensorImpl;
using mindspore::dataset::DataType;
using mindspore::dataset::Status;
using mindspore::dataset::BorderType;
using mindspore::dataset::dsize_t;
class MindDataTestPipeline : public UT::DatasetOpTesting {
protected:
};
TEST_F(MindDataTestPipeline, TestMnistFail1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestMnistFail1.";
// Create a Mnist Dataset
std::shared_ptr<Dataset> ds = Mnist("", RandomSampler(false, 10));
EXPECT_EQ(ds, nullptr);
}
TEST_F(MindDataTestPipeline, TestImageFolderFail1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestImageFolderFail1.";
// Create an ImageFolder Dataset
std::shared_ptr<Dataset> ds = ImageFolder("", true, nullptr);
EXPECT_EQ(ds, nullptr);
}
TEST_F(MindDataTestPipeline, TestCelebADataset) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCelebADataset.";
@ -158,3 +117,19 @@ TEST_F(MindDataTestPipeline, TestCelebAException) {
std::shared_ptr<Dataset> ds1 = CelebA(folder_path, invalid_dataset_type);
EXPECT_EQ(ds1, nullptr);
}
TEST_F(MindDataTestPipeline, TestImageFolderFail1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestImageFolderFail1.";
// Create an ImageFolder Dataset
std::shared_ptr<Dataset> ds = ImageFolder("", true, nullptr);
EXPECT_EQ(ds, nullptr);
}
TEST_F(MindDataTestPipeline, TestMnistFail1) {
MS_LOG(INFO) << "Doing MindDataTestPipeline-TestMnistFail1.";
// Create a Mnist Dataset
std::shared_ptr<Dataset> ds = Mnist("", RandomSampler(false, 10));
EXPECT_EQ(ds, nullptr);
}

22
tests/ut/cpp/dataset/c_api_samplers_test.cc
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@ -13,33 +13,11 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <fstream>
#include <iostream>
#include <memory>
#include <vector>
#include <string>
#include "utils/log_adapter.h"
#include "utils/ms_utils.h"
#include "common/common.h"
#include "gtest/gtest.h"
#include "securec.h"
#include "minddata/dataset/include/datasets.h"
#include "minddata/dataset/include/status.h"
#include "minddata/dataset/include/transforms.h"
#include "minddata/dataset/include/iterator.h"
#include "minddata/dataset/core/constants.h"
#include "minddata/dataset/core/tensor_shape.h"
#include "minddata/dataset/core/tensor.h"
#include "minddata/dataset/include/samplers.h"
using namespace mindspore::dataset::api;
using mindspore::MsLogLevel::ERROR;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;
using mindspore::dataset::Tensor;
using mindspore::dataset::Status;
using mindspore::dataset::BorderType;
class MindDataTestPipeline : public UT::DatasetOpTesting {
protected:

314
tests/ut/cpp/dataset/c_api_transforms_test.cc
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