From d9aa18dfcae7495720bbece48155fee28e7b8dd9 Mon Sep 17 00:00:00 2001
From: liyong <liyong126@huawei.com>
Date: Mon, 18 Oct 2021 17:55:28 +0800
Subject: [PATCH] refactor md ut

---
 tests/ut/python/dataset/test_minddataset.py   | 143 ++++-----
 .../python/dataset/test_minddataset_padded.py |  54 ++--
 .../dataset/test_minddataset_sampler.py       |  85 ++++--
 tests/ut/python/dataset/test_save_op.py       | 204 ++++++++-----
 .../ut/python/dataset/test_serdes_dataset.py  |  34 ---
 .../mindrecord/test_mindrecord_exception.py   | 288 ++++++++++++------
 6 files changed, 478 insertions(+), 330 deletions(-)

diff --git a/tests/ut/python/dataset/test_minddataset.py b/tests/ut/python/dataset/test_minddataset.py
index c53408ca6a4..06a60b50684 100644
--- a/tests/ut/python/dataset/test_minddataset.py
+++ b/tests/ut/python/dataset/test_minddataset.py
@@ -31,20 +31,15 @@ from mindspore.dataset.vision import Inter
 from mindspore.mindrecord import FileWriter
 
 FILES_NUM = 4
-CV_FILE_NAME = "../data/mindrecord/imagenet.mindrecord"
-CV1_FILE_NAME = "../data/mindrecord/imagenet1.mindrecord"
-CV2_FILE_NAME = "../data/mindrecord/imagenet2.mindrecord"
 CV_DIR_NAME = "../data/mindrecord/testImageNetData"
-NLP_FILE_NAME = "../data/mindrecord/aclImdb.mindrecord"
-OLD_NLP_FILE_NAME = "../data/mindrecord/testOldVersion/aclImdb.mindrecord"
 NLP_FILE_POS = "../data/mindrecord/testAclImdbData/pos"
 NLP_FILE_VOCAB = "../data/mindrecord/testAclImdbData/vocab.txt"
 
-
 @pytest.fixture
 def add_and_remove_cv_file():
     """add/remove cv file"""
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -52,7 +47,7 @@ def add_and_remove_cv_file():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(CV_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = get_data(CV_DIR_NAME)
         cv_schema_json = {"id": {"type": "int32"},
                           "file_name": {"type": "string"},
@@ -77,7 +72,8 @@ def add_and_remove_cv_file():
 @pytest.fixture
 def add_and_remove_nlp_file():
     """add/remove nlp file"""
-    paths = ["{}{}".format(NLP_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -85,7 +81,7 @@ def add_and_remove_nlp_file():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(NLP_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = [x for x in get_nlp_data(NLP_FILE_POS, NLP_FILE_VOCAB, 10)]
         nlp_schema_json = {"id": {"type": "string"}, "label": {"type": "int32"},
                            "rating": {"type": "float32"},
@@ -117,7 +113,8 @@ def add_and_remove_nlp_file():
 @pytest.fixture
 def add_and_remove_nlp_compress_file():
     """add/remove nlp file"""
-    paths = ["{}{}".format(NLP_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -125,7 +122,7 @@ def add_and_remove_nlp_compress_file():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(NLP_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = []
         for row_id in range(16):
             data.append({
@@ -183,8 +180,9 @@ def test_nlp_compress_data(add_and_remove_nlp_compress_file):
             "array_d": np.reshape(np.array([[-10, -127], [10, 127]]), [2, -1])
         })
     num_readers = 1
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     data_set = ds.MindDataset(
-        NLP_FILE_NAME + "0", None, num_readers, shuffle=False)
+        file_name + "0", None, num_readers, shuffle=False)
     assert data_set.get_dataset_size() == 16
     num_iter = 0
     for x, item in zip(data, data_set.create_dict_iterator(num_epochs=1, output_numpy=True)):
@@ -197,29 +195,10 @@ def test_nlp_compress_data(add_and_remove_nlp_compress_file):
     assert num_iter == 16
 
 
-def test_nlp_compress_data_old_version(add_and_remove_nlp_compress_file):
-    """tutorial for nlp minderdataset."""
-    num_readers = 1
-    data_set = ds.MindDataset(
-        NLP_FILE_NAME + "0", None, num_readers, shuffle=False)
-    old_data_set = ds.MindDataset(
-        OLD_NLP_FILE_NAME + "0", None, num_readers, shuffle=False)
-    assert old_data_set.get_dataset_size() == 16
-    num_iter = 0
-    for x, item in zip(old_data_set.create_dict_iterator(num_epochs=1, output_numpy=True),
-                       data_set.create_dict_iterator(num_epochs=1, output_numpy=True)):
-        assert (item["array_a"] == x["array_a"]).all()
-        assert (item["array_b"] == x["array_b"]).all()
-        assert (item["array_c"] == x["array_c"]).all()
-        assert (item["array_d"] == x["array_d"]).all()
-        assert item["label"] == x["label"]
-        num_iter += 1
-    assert num_iter == 16
-
-
 def test_cv_minddataset_writer_tutorial():
     """tutorial for cv dataset writer."""
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -227,7 +206,7 @@ def test_cv_minddataset_writer_tutorial():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(CV_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = get_data(CV_DIR_NAME)
         cv_schema_json = {"file_name": {"type": "string"}, "label": {"type": "int32"},
                           "data": {"type": "bytes"}}
@@ -250,10 +229,11 @@ def test_cv_minddataset_partition_tutorial(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards, shard_id=partition_id)
             num_iter = 0
             for item in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
@@ -272,10 +252,11 @@ def test_cv_minddataset_partition_num_samples_0(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id, num_samples=1)
 
@@ -297,10 +278,11 @@ def test_cv_minddataset_partition_num_samples_1(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id, num_samples=2)
 
@@ -322,10 +304,11 @@ def test_cv_minddataset_partition_num_samples_2(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, expect):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id, num_samples=3)
 
@@ -346,8 +329,9 @@ def test_cv_minddataset_partition_num_samples_3(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers, num_shards=1, shard_id=0, num_samples=5)
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers, num_shards=1, shard_id=0, num_samples=5)
 
     assert data_set.get_dataset_size() == 5
     num_iter = 0
@@ -366,9 +350,10 @@ def test_cv_minddataset_partition_tutorial_check_shuffle_result(add_and_remove_c
     epoch1 = []
     epoch2 = []
     epoch3 = []
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     for partition_id in range(num_shards):
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   num_shards=num_shards, shard_id=partition_id)
 
         data_set = data_set.repeat(3)
@@ -401,13 +386,14 @@ def test_cv_minddataset_partition_tutorial_check_whole_reshuffle_result_per_epoc
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     num_shards = 3
     epoch_result = [[["", "", "", ""], ["", "", "", ""], ["", "", "", ""]],  # save partition 0 result
                     [["", "", "", ""], ["", "", "", ""], ["", "", "", ""]],  # save partition 1 result
                     [["", "", "", ""], ["", "", "", ""], ["", "", "", ""]]]  # svae partition 2 result
 
     for partition_id in range(num_shards):
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   num_shards=num_shards, shard_id=partition_id)
 
         data_set = data_set.repeat(3)
@@ -436,13 +422,14 @@ def test_cv_minddataset_check_shuffle_result(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     ds.config.set_seed(54321)
     epoch1 = []
     epoch2 = []
     epoch3 = []
 
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     data_set = data_set.repeat(3)
 
     num_iter = 0
@@ -468,7 +455,7 @@ def test_cv_minddataset_check_shuffle_result(add_and_remove_cv_file):
     epoch2_new_dataset = []
     epoch3_new_dataset = []
 
-    data_set2 = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    data_set2 = ds.MindDataset(file_name + "0", columns_list, num_readers)
     data_set2 = data_set2.repeat(3)
 
     num_iter = 0
@@ -499,7 +486,7 @@ def test_cv_minddataset_check_shuffle_result(add_and_remove_cv_file):
     epoch2_new_dataset2 = []
     epoch3_new_dataset2 = []
 
-    data_set3 = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    data_set3 = ds.MindDataset(file_name + "0", columns_list, num_readers)
     data_set3 = data_set3.repeat(3)
 
     num_iter = 0
@@ -530,7 +517,8 @@ def test_cv_minddataset_dataset_size(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     assert data_set.get_dataset_size() == 10
     repeat_num = 2
     data_set = data_set.repeat(repeat_num)
@@ -544,7 +532,7 @@ def test_cv_minddataset_dataset_size(add_and_remove_cv_file):
             "-------------- item[data]: {} ----------------------".format(item["data"]))
         num_iter += 1
     assert num_iter == 20
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               num_shards=4, shard_id=3)
     assert data_set.get_dataset_size() == 3
 
@@ -553,7 +541,8 @@ def test_cv_minddataset_repeat_reshuffle(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     decode_op = vision.Decode()
     data_set = data_set.map(
         input_columns=["data"], operations=decode_op, num_parallel_workers=2)
@@ -584,7 +573,8 @@ def test_cv_minddataset_batch_size_larger_than_records(add_and_remove_cv_file):
     """tutorial for cv minddataset."""
     columns_list = ["data", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     decode_op = vision.Decode()
     data_set = data_set.map(
         input_columns=["data"], operations=decode_op, num_parallel_workers=2)
@@ -608,7 +598,8 @@ def test_cv_minddataset_issue_888(add_and_remove_cv_file):
     """issue 888 test."""
     columns_list = ["data", "label"]
     num_readers = 2
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers, shuffle=False, num_shards=5, shard_id=1)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers, shuffle=False, num_shards=5, shard_id=1)
     data_set = data_set.shuffle(2)
     data_set = data_set.repeat(9)
     num_iter = 0
@@ -621,7 +612,8 @@ def test_cv_minddataset_reader_file_list(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    data_set = ds.MindDataset([CV_FILE_NAME + str(x)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset([file_name + str(x)
                                for x in range(FILES_NUM)], columns_list, num_readers)
     assert data_set.get_dataset_size() == 10
     num_iter = 0
@@ -644,7 +636,8 @@ def test_cv_minddataset_reader_one_partition(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    data_set = ds.MindDataset([CV_FILE_NAME + "0"], columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset([file_name + "0"], columns_list, num_readers)
     assert data_set.get_dataset_size() < 10
     num_iter = 0
     for item in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
@@ -664,6 +657,8 @@ def test_cv_minddataset_reader_one_partition(add_and_remove_cv_file):
 
 def test_cv_minddataset_reader_two_dataset(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
+    CV1_FILE_NAME = "../data/mindrecord/test_cv_minddataset_reader_two_dataset_1.mindrecord"
+    CV2_FILE_NAME = "../data/mindrecord/test_cv_minddataset_reader_two_dataset_2.mindrecord"
     try:
         if os.path.exists(CV1_FILE_NAME):
             os.remove(CV1_FILE_NAME)
@@ -696,7 +691,8 @@ def test_cv_minddataset_reader_two_dataset(add_and_remove_cv_file):
         writer.commit()
         columns_list = ["data", "file_name", "label"]
         num_readers = 4
-        data_set = ds.MindDataset([CV_FILE_NAME + str(x) for x in range(FILES_NUM)] + [CV1_FILE_NAME, CV2_FILE_NAME],
+        file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+        data_set = ds.MindDataset([file_name + str(x) for x in range(FILES_NUM)] + [CV1_FILE_NAME, CV2_FILE_NAME],
                                   columns_list, num_readers)
         assert data_set.get_dataset_size() == 30
         num_iter = 0
@@ -735,6 +731,7 @@ def test_cv_minddataset_reader_two_dataset(add_and_remove_cv_file):
 
 
 def test_cv_minddataset_reader_two_dataset_partition(add_and_remove_cv_file):
+    CV1_FILE_NAME = "../data/mindrecord/test_cv_minddataset_reader_two_dataset_partition_1"
     paths = ["{}{}".format(CV1_FILE_NAME, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
@@ -756,7 +753,8 @@ def test_cv_minddataset_reader_two_dataset_partition(add_and_remove_cv_file):
 
         columns_list = ["data", "file_name", "label"]
         num_readers = 4
-        data_set = ds.MindDataset([CV_FILE_NAME + str(x) for x in range(2)] +
+        file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+        data_set = ds.MindDataset([file_name + str(x) for x in range(2)] +
                                   [CV1_FILE_NAME + str(x) for x in range(2, 4)],
                                   columns_list, num_readers)
         assert data_set.get_dataset_size() < 20
@@ -789,7 +787,8 @@ def test_cv_minddataset_reader_basic_tutorial(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     assert data_set.get_dataset_size() == 10
     num_iter = 0
     for item in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
@@ -810,7 +809,8 @@ def test_cv_minddataset_reader_basic_tutorial(add_and_remove_cv_file):
 def test_nlp_minddataset_reader_basic_tutorial(add_and_remove_nlp_file):
     """tutorial for nlp minderdataset."""
     num_readers = 4
-    data_set = ds.MindDataset(NLP_FILE_NAME + "0", None, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", None, num_readers)
     assert data_set.get_dataset_size() == 10
     num_iter = 0
     for item in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
@@ -839,7 +839,8 @@ def test_cv_minddataset_reader_basic_tutorial_5_epoch(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     assert data_set.get_dataset_size() == 10
     for _ in range(5):
         num_iter = 0
@@ -855,7 +856,8 @@ def test_cv_minddataset_reader_basic_tutorial_5_epoch_with_batch(add_and_remove_
     """tutorial for cv minderdataset."""
     columns_list = ["data", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
 
     resize_height = 32
     resize_width = 32
@@ -881,7 +883,8 @@ def test_cv_minddataset_reader_basic_tutorial_5_epoch_with_batch(add_and_remove_
 
 def test_cv_minddataset_reader_no_columns(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
-    data_set = ds.MindDataset(CV_FILE_NAME + "0")
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0")
     assert data_set.get_dataset_size() == 10
     num_iter = 0
     for item in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
@@ -903,7 +906,8 @@ def test_cv_minddataset_reader_repeat_tutorial(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers)
     repeat_num = 2
     data_set = data_set.repeat(repeat_num)
     num_iter = 0
@@ -1753,7 +1757,8 @@ def test_write_with_multi_array_and_MindDataset():
 
 
 def test_numpy_generic():
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -1761,7 +1766,7 @@ def test_numpy_generic():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(CV_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         cv_schema_json = {"label1": {"type": "int32"}, "label2": {"type": "int64"},
                           "label3": {"type": "float32"}, "label4": {"type": "float64"}}
         data = []
@@ -1777,7 +1782,7 @@ def test_numpy_generic():
         writer.commit()
 
         num_readers = 4
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", None, num_readers, shuffle=False)
+        data_set = ds.MindDataset(file_name + "0", None, num_readers, shuffle=False)
         assert data_set.get_dataset_size() == 10
         idx = 0
         for item in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
@@ -1799,7 +1804,7 @@ def test_numpy_generic():
 
 
 def test_write_with_float32_float64_float32_array_float64_array_and_MindDataset():
-    mindrecord_file_name = "test.mindrecord"
+    mindrecord_file_name = "test_write_with_float32_float64_float32_array_float64_array_and_MindDataset.mindrecord"
     try:
         data = [{"float32_array": np.array([1.2, 2.78, 3.1234, 4.9871, 5.12341], dtype=np.float32),
                  "float64_array": np.array([48.1234556789, 49.3251241431, 50.13514312414, 51.8971298471,
@@ -2570,7 +2575,8 @@ def test_distributed_shuffle_with_multi_epochs(create_multi_mindrecord_files):
 
 def test_field_is_null_numpy():
     """add/remove nlp file"""
-    paths = ["{}{}".format(NLP_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     for x in paths:
         if os.path.exists("{}".format(x)):
@@ -2578,7 +2584,7 @@ def test_field_is_null_numpy():
         if os.path.exists("{}.db".format(x)):
             os.remove("{}.db".format(x))
 
-    writer = FileWriter(NLP_FILE_NAME, FILES_NUM)
+    writer = FileWriter(file_name, FILES_NUM)
     data = []
     # field array_d is null
     for row_id in range(16):
@@ -2607,7 +2613,7 @@ def test_field_is_null_numpy():
     writer.write_raw_data(data)
     writer.commit()
 
-    data_set = ds.MindDataset(dataset_file=NLP_FILE_NAME + "0",
+    data_set = ds.MindDataset(dataset_file=file_name + "0",
                               columns_list=["label", "array_a", "array_b", "array_d"],
                               num_parallel_workers=2,
                               shuffle=False)
@@ -2639,8 +2645,9 @@ def test_for_loop_dataset_iterator(add_and_remove_nlp_compress_file):
             "array_d": np.reshape(np.array([[-10, -127], [10, 127]]), [2, -1])
         })
     num_readers = 1
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     data_set = ds.MindDataset(
-        NLP_FILE_NAME + "0", None, num_readers, shuffle=False)
+        file_name + "0", None, num_readers, shuffle=False)
     assert data_set.get_dataset_size() == 16
 
     # create_dict_iterator in for loop
diff --git a/tests/ut/python/dataset/test_minddataset_padded.py b/tests/ut/python/dataset/test_minddataset_padded.py
index 97daba392af..a268adf4eee 100644
--- a/tests/ut/python/dataset/test_minddataset_padded.py
+++ b/tests/ut/python/dataset/test_minddataset_padded.py
@@ -28,26 +28,22 @@ from mindspore import log as logger
 from mindspore.mindrecord import FileWriter
 
 FILES_NUM = 4
-CV_FILE_NAME = "../data/mindrecord/imagenet.mindrecord"
-CV1_FILE_NAME = "../data/mindrecord/imagenet1.mindrecord"
-CV2_FILE_NAME = "../data/mindrecord/imagenet2.mindrecord"
 CV_DIR_NAME = "../data/mindrecord/testImageNetData"
-NLP_FILE_NAME = "../data/mindrecord/aclImdb.mindrecord"
 NLP_FILE_POS = "../data/mindrecord/testAclImdbData/pos"
 NLP_FILE_VOCAB = "../data/mindrecord/testAclImdbData/vocab.txt"
 
-
 @pytest.fixture
 def add_and_remove_cv_file():
     """add/remove cv file"""
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
             os.remove("{}".format(x)) if os.path.exists("{}".format(x)) else None
             os.remove("{}.db".format(x)) if os.path.exists(
                 "{}.db".format(x)) else None
-        writer = FileWriter(CV_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = get_data(CV_DIR_NAME)
         cv_schema_json = {"id": {"type": "int32"},
                           "file_name": {"type": "string"},
@@ -72,7 +68,8 @@ def add_and_remove_cv_file():
 @pytest.fixture
 def add_and_remove_nlp_file():
     """add/remove nlp file"""
-    paths = ["{}{}".format(NLP_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -80,7 +77,7 @@ def add_and_remove_nlp_file():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(NLP_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = [x for x in get_nlp_data(NLP_FILE_POS, NLP_FILE_VOCAB, 10)]
         nlp_schema_json = {"id": {"type": "string"}, "label": {"type": "int32"},
                            "rating": {"type": "float32"},
@@ -118,7 +115,8 @@ def test_cv_minddataset_reader_basic_padded_samples(add_and_remove_cv_file):
     padded_sample['label'] = -1
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers, padded_sample=padded_sample, num_padded=5)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers, padded_sample=padded_sample, num_padded=5)
     assert data_set.get_dataset_size() == 15
     num_iter = 0
     num_padded_iter = 0
@@ -145,7 +143,8 @@ def test_cv_minddataset_reader_basic_padded_samples_type_cast(add_and_remove_cv_
     padded_sample['label'] = -1
     padded_sample['file_name'] = 99999
     num_readers = 4
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers, padded_sample=padded_sample, num_padded=5)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers, padded_sample=padded_sample, num_padded=5)
     assert data_set.get_dataset_size() == 15
     num_iter = 0
     num_padded_iter = 0
@@ -173,12 +172,13 @@ def test_cv_minddataset_partition_padded_samples(add_and_remove_cv_file):
     padded_sample['label'] = -2
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded, dataset_size):
         num_padded_iter = 0
         num_iter = 0
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -213,6 +213,7 @@ def test_cv_minddataset_partition_padded_samples_multi_epoch(add_and_remove_cv_f
     padded_sample['label'] = -2
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded, dataset_size):
         repeat_size = 5
@@ -224,7 +225,7 @@ def test_cv_minddataset_partition_padded_samples_multi_epoch(add_and_remove_cv_f
             epoch3_shuffle_result = []
             epoch4_shuffle_result = []
             epoch5_shuffle_result = []
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -285,10 +286,11 @@ def test_cv_minddataset_partition_padded_samples_no_dividsible(add_and_remove_cv
     padded_sample['label'] = -2
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -310,10 +312,11 @@ def test_cv_minddataset_partition_padded_samples_dataset_size_no_divisible(add_a
     padded_sample['label'] = -2
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -332,10 +335,11 @@ def test_cv_minddataset_partition_padded_samples_no_equal_column_list(add_and_re
     padded_sample.pop('label', None)
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -356,10 +360,11 @@ def test_cv_minddataset_partition_padded_samples_no_column_list(add_and_remove_c
     padded_sample['label'] = -2
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", None, num_readers,
+            data_set = ds.MindDataset(file_name + "0", None, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -380,10 +385,11 @@ def test_cv_minddataset_partition_padded_samples_no_num_padded(add_and_remove_cv
     padded_sample = data[0]
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", None, num_readers,
+            data_set = ds.MindDataset(file_name + "0", None, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample)
@@ -403,10 +409,11 @@ def test_cv_minddataset_partition_padded_samples_no_padded_samples(add_and_remov
     padded_sample = data[0]
     padded_sample['file_name'] = 'dummy.jpg'
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded):
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(CV_FILE_NAME + "0", None, num_readers,
+            data_set = ds.MindDataset(file_name + "0", None, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       num_padded=num_padded)
@@ -429,12 +436,13 @@ def test_nlp_minddataset_reader_basic_padded_samples(add_and_remove_nlp_file):
     padded_sample['input_ids'] = np.array([-1, -1, -1, -1], dtype=np.int64)
     padded_sample['rating'] = 1.0
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded, dataset_size):
         num_padded_iter = 0
         num_iter = 0
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(NLP_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -470,6 +478,7 @@ def test_nlp_minddataset_reader_basic_padded_samples_multi_epoch(add_and_remove_
     padded_sample['rating'] = 1.0
     num_readers = 4
     repeat_size = 3
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded, dataset_size):
         num_padded_iter = 0
@@ -479,7 +488,7 @@ def test_nlp_minddataset_reader_basic_padded_samples_multi_epoch(add_and_remove_
             epoch1_shuffle_result = []
             epoch2_shuffle_result = []
             epoch3_shuffle_result = []
-            data_set = ds.MindDataset(NLP_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
@@ -534,6 +543,7 @@ def test_nlp_minddataset_reader_basic_padded_samples_check_whole_reshuffle_resul
     padded_sample['rating'] = 1.0
     num_readers = 4
     repeat_size = 3
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     def partitions(num_shards, num_padded, dataset_size):
         num_padded_iter = 0
@@ -542,7 +552,7 @@ def test_nlp_minddataset_reader_basic_padded_samples_check_whole_reshuffle_resul
         epoch_result = [[["" for i in range(dataset_size)] for i in range(repeat_size)] for i in range(num_shards)]
 
         for partition_id in range(num_shards):
-            data_set = ds.MindDataset(NLP_FILE_NAME + "0", columns_list, num_readers,
+            data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                       num_shards=num_shards,
                                       shard_id=partition_id,
                                       padded_sample=padded_sample,
diff --git a/tests/ut/python/dataset/test_minddataset_sampler.py b/tests/ut/python/dataset/test_minddataset_sampler.py
index 16abdac939c..a41c7795fc8 100644
--- a/tests/ut/python/dataset/test_minddataset_sampler.py
+++ b/tests/ut/python/dataset/test_minddataset_sampler.py
@@ -25,14 +25,13 @@ from mindspore.dataset.text import to_str
 from mindspore.mindrecord import FileWriter
 
 FILES_NUM = 4
-CV_FILE_NAME = "../data/mindrecord/imagenet.mindrecord"
 CV_DIR_NAME = "../data/mindrecord/testImageNetData"
 
-
 @pytest.fixture
 def add_and_remove_cv_file():
     """add/remove cv file"""
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     try:
         for x in paths:
@@ -40,7 +39,7 @@ def add_and_remove_cv_file():
                 os.remove("{}".format(x))
             if os.path.exists("{}.db".format(x)):
                 os.remove("{}.db".format(x))
-        writer = FileWriter(CV_FILE_NAME, FILES_NUM)
+        writer = FileWriter(file_name, FILES_NUM)
         data = get_data(CV_DIR_NAME, True)
         cv_schema_json = {"id": {"type": "int32"},
                           "file_name": {"type": "string"},
@@ -66,7 +65,8 @@ def test_cv_minddataset_pk_sample_no_column(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     num_readers = 4
     sampler = ds.PKSampler(2)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", None, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", None, num_readers,
                               sampler=sampler)
 
     assert data_set.get_dataset_size() == 6
@@ -86,7 +86,8 @@ def test_cv_minddataset_pk_sample_basic(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(2)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
 
     assert data_set.get_dataset_size() == 6
@@ -108,7 +109,8 @@ def test_cv_minddataset_pk_sample_shuffle(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(3, None, True)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
 
     assert data_set.get_dataset_size() == 9
@@ -129,7 +131,8 @@ def test_cv_minddataset_pk_sample_shuffle_1(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(3, None, True, 'label', 5)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
 
     assert data_set.get_dataset_size() == 5
@@ -150,7 +153,8 @@ def test_cv_minddataset_pk_sample_shuffle_2(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(3, None, True, 'label', 10)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
 
     assert data_set.get_dataset_size() == 9
@@ -171,7 +175,8 @@ def test_cv_minddataset_pk_sample_out_of_range_0(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(5, None, True)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 15
     num_iter = 0
@@ -191,7 +196,8 @@ def test_cv_minddataset_pk_sample_out_of_range_1(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(5, None, True, 'label', 20)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 15
     num_iter = 0
@@ -211,7 +217,8 @@ def test_cv_minddataset_pk_sample_out_of_range_2(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.PKSampler(5, None, True, 'label', 10)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 10
     num_iter = 0
@@ -230,10 +237,11 @@ def test_cv_minddataset_subset_random_sample_basic(add_and_remove_cv_file):
     """tutorial for cv minderdataset."""
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     indices = [1, 2, 3, 5, 7]
     samplers = (ds.SubsetRandomSampler(indices), ds.SubsetSampler(indices))
     for sampler in samplers:
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   sampler=sampler)
         assert data_set.get_dataset_size() == 5
         num_iter = 0
@@ -255,9 +263,10 @@ def test_cv_minddataset_subset_random_sample_replica(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     indices = [1, 2, 2, 5, 7, 9]
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     samplers = ds.SubsetRandomSampler(indices), ds.SubsetSampler(indices)
     for sampler in samplers:
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   sampler=sampler)
         assert data_set.get_dataset_size() == 6
         num_iter = 0
@@ -279,9 +288,10 @@ def test_cv_minddataset_subset_random_sample_empty(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     indices = []
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     samplers = ds.SubsetRandomSampler(indices), ds.SubsetSampler(indices)
     for sampler in samplers:
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   sampler=sampler)
         assert data_set.get_dataset_size() == 0
         num_iter = 0
@@ -304,8 +314,9 @@ def test_cv_minddataset_subset_random_sample_out_of_range(add_and_remove_cv_file
     num_readers = 4
     indices = [1, 2, 4, 11, 13]
     samplers = ds.SubsetRandomSampler(indices), ds.SubsetSampler(indices)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     for sampler in samplers:
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   sampler=sampler)
         assert data_set.get_dataset_size() == 5
         num_iter = 0
@@ -327,8 +338,9 @@ def test_cv_minddataset_subset_random_sample_negative(add_and_remove_cv_file):
     num_readers = 4
     indices = [1, 2, 4, -1, -2]
     samplers = ds.SubsetRandomSampler(indices), ds.SubsetSampler(indices)
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     for sampler in samplers:
-        data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+        data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                                   sampler=sampler)
         assert data_set.get_dataset_size() == 5
         num_iter = 0
@@ -350,7 +362,8 @@ def test_cv_minddataset_random_sampler_basic(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
     sampler = ds.RandomSampler()
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 10
     num_iter = 0
@@ -373,8 +386,9 @@ def test_cv_minddataset_random_sampler_basic(add_and_remove_cv_file):
 def test_cv_minddataset_random_sampler_repeat(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.RandomSampler()
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 10
     ds1 = data_set.repeat(3)
@@ -407,8 +421,9 @@ def test_cv_minddataset_random_sampler_repeat(add_and_remove_cv_file):
 def test_cv_minddataset_random_sampler_replacement(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.RandomSampler(replacement=True, num_samples=5)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 5
     num_iter = 0
@@ -428,8 +443,9 @@ def test_cv_minddataset_random_sampler_replacement(add_and_remove_cv_file):
 def test_cv_minddataset_random_sampler_replacement_false_1(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.RandomSampler(replacement=False, num_samples=2)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 2
     num_iter = 0
@@ -449,8 +465,9 @@ def test_cv_minddataset_random_sampler_replacement_false_1(add_and_remove_cv_fil
 def test_cv_minddataset_random_sampler_replacement_false_2(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.RandomSampler(replacement=False, num_samples=20)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 10
     num_iter = 0
@@ -471,8 +488,9 @@ def test_cv_minddataset_sequential_sampler_basic(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.SequentialSampler(1, 4)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     assert data_set.get_dataset_size() == 4
     num_iter = 0
@@ -495,8 +513,9 @@ def test_cv_minddataset_sequential_sampler_offeset(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.SequentialSampler(2, 10)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     dataset_size = data_set.get_dataset_size()
     assert dataset_size == 10
@@ -520,8 +539,9 @@ def test_cv_minddataset_sequential_sampler_exceed_size(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     sampler = ds.SequentialSampler(2, 20)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
+    data_set = ds.MindDataset(file_name + "0", columns_list, num_readers,
                               sampler=sampler)
     dataset_size = data_set.get_dataset_size()
     assert dataset_size == 10
@@ -545,7 +565,8 @@ def test_cv_minddataset_split_basic(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    d = ds.MindDataset(CV_FILE_NAME + "0", columns_list,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    d = ds.MindDataset(file_name + "0", columns_list,
                        num_readers, shuffle=False)
     d1, d2 = d.split([8, 2], randomize=False)
     assert d.get_dataset_size() == 10
@@ -581,7 +602,8 @@ def test_cv_minddataset_split_exact_percent(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    d = ds.MindDataset(CV_FILE_NAME + "0", columns_list,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    d = ds.MindDataset(file_name + "0", columns_list,
                        num_readers, shuffle=False)
     d1, d2 = d.split([0.8, 0.2], randomize=False)
     assert d.get_dataset_size() == 10
@@ -617,7 +639,8 @@ def test_cv_minddataset_split_fuzzy_percent(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    d = ds.MindDataset(CV_FILE_NAME + "0", columns_list,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    d = ds.MindDataset(file_name + "0", columns_list,
                        num_readers, shuffle=False)
     d1, d2 = d.split([0.41, 0.59], randomize=False)
     assert d.get_dataset_size() == 10
@@ -652,7 +675,8 @@ def test_cv_minddataset_split_fuzzy_percent(add_and_remove_cv_file):
 def test_cv_minddataset_split_deterministic(add_and_remove_cv_file):
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    d = ds.MindDataset(CV_FILE_NAME + "0", columns_list,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    d = ds.MindDataset(file_name + "0", columns_list,
                        num_readers, shuffle=False)
     # should set seed to avoid data overlap
     ds.config.set_seed(111)
@@ -693,7 +717,8 @@ def test_cv_minddataset_split_sharding(add_and_remove_cv_file):
     data = get_data(CV_DIR_NAME, True)
     columns_list = ["data", "file_name", "label"]
     num_readers = 4
-    d = ds.MindDataset(CV_FILE_NAME + "0", columns_list,
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    d = ds.MindDataset(file_name + "0", columns_list,
                        num_readers, shuffle=False)
     # should set seed to avoid data overlap
     ds.config.set_seed(111)
diff --git a/tests/ut/python/dataset/test_save_op.py b/tests/ut/python/dataset/test_save_op.py
index 037460952b6..bc87cca64bb 100644
--- a/tests/ut/python/dataset/test_save_op.py
+++ b/tests/ut/python/dataset/test_save_op.py
@@ -23,38 +23,25 @@ import mindspore.dataset as ds
 from mindspore import log as logger
 from mindspore.mindrecord import FileWriter
 
-TEMP_FILE = "../data/mindrecord/testMindDataSet/temp.mindrecord"
-AUTO_FILE = "../data/mindrecord/testMindDataSet/auto.mindrecord"
 TFRECORD_FILES = "../data/mindrecord/testTFRecordData/dummy.tfrecord"
 FILES_NUM = 1
 num_readers = 1
 
 
-@pytest.fixture(name="add_remove_file")
-def fixture_remove():
+def remove_file(file_name):
     """add/remove cv file"""
-    if os.path.exists("{}".format(TEMP_FILE)):
-        os.remove("{}".format(TEMP_FILE))
-    if os.path.exists("{}.db".format(TEMP_FILE)):
-        os.remove("{}.db".format(TEMP_FILE))
+    if os.path.exists("{}".format(file_name)):
+        os.remove("{}".format(file_name))
+    if os.path.exists("{}.db".format(file_name)):
+        os.remove("{}.db".format(file_name))
 
-    if os.path.exists("{}".format(AUTO_FILE)):
-        os.remove("{}".format(AUTO_FILE))
-    if os.path.exists("{}.db".format(AUTO_FILE)):
-        os.remove("{}.db".format(AUTO_FILE))
-    yield "yield_cv_data"
-    if os.path.exists("{}".format(TEMP_FILE)):
-        os.remove("{}".format(TEMP_FILE))
-    if os.path.exists("{}.db".format(TEMP_FILE)):
-        os.remove("{}.db".format(TEMP_FILE))
-
-    if os.path.exists("{}".format(AUTO_FILE)):
-        os.remove("{}".format(AUTO_FILE))
-    if os.path.exists("{}.db".format(AUTO_FILE)):
-        os.remove("{}.db".format(AUTO_FILE))
-
-
-def test_case_00(add_remove_file):  # only bin data
+def test_case_00():
+    """
+    Feature: save op
+    Description: all bin data
+    Expectation: generated mindrecord file
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     data = [{"image1": bytes("image1 bytes abc", encoding='UTF-8'),
              "image2": bytes("image1 bytes def", encoding='UTF-8'),
              "image3": bytes("image1 bytes ghi", encoding='UTF-8'),
@@ -86,13 +73,16 @@ def test_case_00(add_remove_file):  # only bin data
         "image3": {"type": "bytes"},
         "image4": {"type": "bytes"},
         "image5": {"type": "bytes"}}
-    writer = FileWriter(TEMP_FILE, FILES_NUM)
+    writer = FileWriter(file_name, FILES_NUM)
     writer.add_schema(schema, "schema")
     writer.write_raw_data(data)
     writer.commit()
 
-    d1 = ds.MindDataset(TEMP_FILE, None, num_readers, shuffle=False)
-    d1.save(AUTO_FILE, FILES_NUM)
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
+    d1 = ds.MindDataset(file_name, None, num_readers, shuffle=False)
+    d1.save(file_name_auto, FILES_NUM)
     data_value_to_list = []
 
     for item in data:
@@ -104,7 +94,7 @@ def test_case_00(add_remove_file):  # only bin data
         new_data['image5'] = np.asarray(list(item["image5"]), dtype=np.uint8)
         data_value_to_list.append(new_data)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
     assert d2.get_dataset_size() == 5
@@ -119,9 +109,12 @@ def test_case_00(add_remove_file):  # only bin data
                 assert item[field] == data_value_to_list[num_iter][field]
         num_iter += 1
     assert num_iter == 5
+    remove_file(file_name)
+    remove_file(file_name_auto)
 
 
-def test_case_01(add_remove_file):  # only raw data
+    file_name_auto = './'
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     data = [{"file_name": "001.jpg", "label": 43},
             {"file_name": "002.jpg", "label": 91},
             {"file_name": "003.jpg", "label": 61},
@@ -132,13 +125,16 @@ def test_case_01(add_remove_file):  # only raw data
               "label": {"type": "int32"}
               }
 
-    writer = FileWriter(TEMP_FILE, FILES_NUM)
+    writer = FileWriter(file_name, FILES_NUM)
     writer.add_schema(schema, "schema")
     writer.write_raw_data(data)
     writer.commit()
 
-    d1 = ds.MindDataset(TEMP_FILE, None, num_readers, shuffle=False)
-    d1.save(AUTO_FILE, FILES_NUM)
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
+    d1 = ds.MindDataset(file_name, None, num_readers, shuffle=False)
+    d1.save(file_name_auto, FILES_NUM)
 
     data_value_to_list = []
     for item in data:
@@ -147,7 +143,7 @@ def test_case_01(add_remove_file):  # only raw data
         new_data['label'] = np.asarray(list([item["label"]]), dtype=np.int32)
         data_value_to_list.append(new_data)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
     assert d2.get_dataset_size() == 6
@@ -163,9 +159,17 @@ def test_case_01(add_remove_file):  # only raw data
                 assert item[field] == data_value_to_list[num_iter][field]
         num_iter += 1
     assert num_iter == 6
+    remove_file(file_name)
+    remove_file(file_name_auto)
 
 
-def test_case_02(add_remove_file):  # muti-bytes
+def test_case_02():  # muti-bytes
+    """
+    Feature: save op
+    Description: multiple byte fields
+    Expectation: generated mindrecord file
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     data = [{"file_name": "001.jpg", "label": 43,
              "float32_array": np.array([1.2, 2.78, 3.1234, 4.9871, 5.12341], dtype=np.float32),
              "float64_array": np.array([48.1234556789, 49.3251241431, 50.13514312414, 51.8971298471,
@@ -258,13 +262,16 @@ def test_case_02(add_remove_file):  # muti-bytes
               "label": {"type": "int32"},
               "image4": {"type": "bytes"},
               "image5": {"type": "bytes"}}
-    writer = FileWriter(TEMP_FILE, FILES_NUM)
+    writer = FileWriter(file_name, FILES_NUM)
     writer.add_schema(schema, "schema")
     writer.write_raw_data(data)
     writer.commit()
 
-    d1 = ds.MindDataset(TEMP_FILE, None, num_readers, shuffle=False)
-    d1.save(AUTO_FILE, FILES_NUM)
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
+    d1 = ds.MindDataset(file_name, None, num_readers, shuffle=False)
+    d1.save(file_name_auto, FILES_NUM)
     data_value_to_list = []
 
     for item in data:
@@ -284,7 +291,7 @@ def test_case_02(add_remove_file):  # muti-bytes
         new_data['image5'] = np.asarray(list(item["image5"]), dtype=np.uint8)
         data_value_to_list.append(new_data)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
     assert d2.get_dataset_size() == 6
@@ -303,6 +310,8 @@ def test_case_02(add_remove_file):  # muti-bytes
                 assert item[field] == data_value_to_list[num_iter][field]
         num_iter += 1
     assert num_iter == 6
+    remove_file(file_name)
+    remove_file(file_name_auto)
 
 
 def generator_1d():
@@ -310,14 +319,21 @@ def generator_1d():
         yield (np.array([i]),)
 
 
-def test_case_03(add_remove_file):
-
+def test_case_03():
+    """
+    Feature: save op
+    Description: 1D numpy array
+    Expectation: generated mindrecord file
+    """
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
     # apply dataset operations
     d1 = ds.GeneratorDataset(generator_1d, ["data"], shuffle=False)
 
-    d1.save(AUTO_FILE)
+    d1.save(file_name_auto)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
 
@@ -327,6 +343,7 @@ def test_case_03(add_remove_file):
         golden = np.array([i])
         np.testing.assert_array_equal(item["data"], golden)
         i = i + 1
+    remove_file(file_name_auto)
 
 
 def generator_with_type(t):
@@ -335,6 +352,9 @@ def generator_with_type(t):
 
 
 def type_tester(t):
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
     logger.info("Test with Type {}".format(t.__name__))
 
     # apply dataset operations
@@ -344,9 +364,9 @@ def type_tester(t):
 
     data1 = data1.repeat(3)
 
-    data1.save(AUTO_FILE)
+    data1.save(file_name_auto)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
 
@@ -362,10 +382,7 @@ def type_tester(t):
             i = 0
             num_repeat += 1
     assert num_repeat == 3
-    if os.path.exists("{}".format(AUTO_FILE)):
-        os.remove("{}".format(AUTO_FILE))
-    if os.path.exists("{}.db".format(AUTO_FILE)):
-        os.remove("{}.db".format(AUTO_FILE))
+    remove_file(file_name_auto)
 
 
 def test_case_04():
@@ -377,20 +394,31 @@ def test_case_04():
         type_tester(t)
 
 
-def test_case_05(add_remove_file):
+def test_case_05():
+    """
+    Feature: save op
+    Description: Exception Test
+    Expectation: exception
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     d1 = ds.GeneratorDataset(generator_1d, ["data"], shuffle=False)
 
     with pytest.raises(Exception, match="num_files should between 0 and 1000."):
-        d1.save(AUTO_FILE, 0)
+        d1.save(file_name, 0)
 
 
-def test_case_06(add_remove_file):
-
+def test_case_06():
+    """
+    Feature: save op
+    Description: Exception Test
+    Expectation: exception
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     d1 = ds.GeneratorDataset(generator_1d, ["data"], shuffle=False)
 
     with pytest.raises(Exception, match="tfrecord dataset format is not supported."):
-        d1.save(AUTO_FILE, 1, "tfrecord")
+        d1.save(file_name, 1, "tfrecord")
 
 
 def cast_name(key):
@@ -405,16 +433,20 @@ def cast_name(key):
 
 
 def test_case_07():
-    if os.path.exists("{}".format(AUTO_FILE)):
-        os.remove("{}".format(AUTO_FILE))
-    if os.path.exists("{}.db".format(AUTO_FILE)):
-        os.remove("{}.db".format(AUTO_FILE))
+    """
+    Feature: save op
+    Description: save tfrecord files
+    Expectation: generated mindrecord file
+    """
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
     d1 = ds.TFRecordDataset(TFRECORD_FILES, shuffle=False)
     tf_data = []
     for x in d1.create_dict_iterator(num_epochs=1, output_numpy=True):
         tf_data.append(x)
-    d1.save(AUTO_FILE, FILES_NUM)
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d1.save(file_name_auto, FILES_NUM)
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
     mr_data = []
@@ -429,11 +461,7 @@ def test_case_07():
                 assert v == mr_data[count][cast_name(k)]
         count += 1
     assert count == 10
-
-    if os.path.exists("{}".format(AUTO_FILE)):
-        os.remove("{}".format(AUTO_FILE))
-    if os.path.exists("{}.db".format(AUTO_FILE)):
-        os.remove("{}.db".format(AUTO_FILE))
+    remove_file(file_name_auto)
 
 
 def generator_dynamic_1d():
@@ -461,14 +489,21 @@ def generator_dynamic_2d_1():
             yield (np.arange(10).reshape([5, 2]),)
 
 
-def test_case_08(add_remove_file):
-
+def test_case_08():
+    """
+    Feature: save op
+    Description: save dynamic 1D numpy array
+    Expectation: generated mindrecord file
+    """
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
     # apply dataset operations
     d1 = ds.GeneratorDataset(generator_dynamic_1d, ["data"], shuffle=False)
 
-    d1.save(AUTO_FILE)
+    d1.save(file_name_auto)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
 
@@ -481,16 +516,23 @@ def test_case_08(add_remove_file):
         golden = np.array(arr)
         np.testing.assert_array_equal(item["data"], golden)
         i = i + 1
+    remove_file(file_name_auto)
 
-
-def test_case_09(add_remove_file):
-
+def test_case_09():
+    """
+    Feature: save op
+    Description: save dynamic 2D numpy array
+    Expectation: generated mindrecord file
+    """
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
     # apply dataset operations
     d1 = ds.GeneratorDataset(generator_dynamic_2d_0, ["data"], shuffle=False)
 
-    d1.save(AUTO_FILE)
+    d1.save(file_name_auto)
 
-    d2 = ds.MindDataset(dataset_file=AUTO_FILE,
+    d2 = ds.MindDataset(dataset_file=file_name_auto,
                         num_parallel_workers=num_readers,
                         shuffle=False)
 
@@ -502,13 +544,23 @@ def test_case_09(add_remove_file):
             golden = np.arange(10).reshape([2, 5])
         np.testing.assert_array_equal(item["data"], golden)
         i = i + 1
+    remove_file(file_name_auto)
 
 
-def test_case_10(add_remove_file):
+def test_case_10():
+    """
+    Feature: save op
+    Description: save 2D Tensor of different shape
+    Expectation: Exception
+    """
+    file_name_auto = './'
+    file_name_auto += os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    file_name_auto += '_auto'
 
     # apply dataset operations
     d1 = ds.GeneratorDataset(generator_dynamic_2d_1, ["data"], shuffle=False)
 
     with pytest.raises(Exception, match=
                        "Error: besides dimension 0, other dimension shape is different from the previous's"):
-        d1.save(AUTO_FILE)
+        d1.save(file_name_auto)
+    remove_file(file_name_auto)
diff --git a/tests/ut/python/dataset/test_serdes_dataset.py b/tests/ut/python/dataset/test_serdes_dataset.py
index f3320fdb6fb..d8e3db5c1ae 100644
--- a/tests/ut/python/dataset/test_serdes_dataset.py
+++ b/tests/ut/python/dataset/test_serdes_dataset.py
@@ -22,7 +22,6 @@ import os
 import pytest
 
 import numpy as np
-from test_minddataset_sampler import add_and_remove_cv_file, get_data, CV_DIR_NAME, CV_FILE_NAME
 from util import config_get_set_num_parallel_workers, config_get_set_seed
 
 import mindspore.common.dtype as mstype
@@ -509,38 +508,6 @@ def delete_json_files():
         except IOError:
             logger.info("Error while deleting: {}".format(f))
 
-
-# Test save load minddataset
-def skip_test_minddataset(add_and_remove_cv_file=True):
-    """tutorial for cv minderdataset."""
-    columns_list = ["data", "file_name", "label"]
-    num_readers = 4
-    indices = [1, 2, 3, 5, 7]
-    sampler = ds.SubsetRandomSampler(indices)
-    data_set = ds.MindDataset(CV_FILE_NAME + "0", columns_list, num_readers,
-                              sampler=sampler)
-
-    # Serializing into python dictionary
-    ds1_dict = ds.serialize(data_set)
-    # Serializing into json object
-    ds1_json = json.dumps(ds1_dict, sort_keys=True)
-
-    # Reconstruct dataset pipeline from its serialized form
-    data_set = ds.deserialize(input_dict=ds1_dict)
-    ds2_dict = ds.serialize(data_set)
-    # Serializing into json object
-    ds2_json = json.dumps(ds2_dict, sort_keys=True)
-
-    assert ds1_json == ds2_json
-
-    _ = get_data(CV_DIR_NAME)
-    assert data_set.get_dataset_size() == 5
-    num_iter = 0
-    for _ in data_set.create_dict_iterator(num_epochs=1, output_numpy=True):
-        num_iter += 1
-    assert num_iter == 5
-
-
 if __name__ == '__main__':
     test_serdes_imagefolder_dataset()
     test_serdes_mnist_dataset()
@@ -555,4 +522,3 @@ if __name__ == '__main__':
     test_serdes_uniform_augment()
     skip_test_serdes_fill()
     test_serdes_exception()
-    skip_test_minddataset()
diff --git a/tests/ut/python/mindrecord/test_mindrecord_exception.py b/tests/ut/python/mindrecord/test_mindrecord_exception.py
index 628f674e77b..fc8aedbd5ee 100644
--- a/tests/ut/python/mindrecord/test_mindrecord_exception.py
+++ b/tests/ut/python/mindrecord/test_mindrecord_exception.py
@@ -23,8 +23,6 @@ from mindspore import log as logger
 from mindspore.mindrecord import FileWriter, FileReader, MindPage, SUCCESS
 from mindspore.mindrecord import ParamValueError, MRMGetMetaError
 
-CV_FILE_NAME = "./imagenet.mindrecord"
-NLP_FILE_NAME = "./aclImdb.mindrecord"
 FILES_NUM = 4
 
 def remove_one_file(x):
@@ -42,20 +40,6 @@ def remove_file(file_name):
         x = file_name + str(i) + ".db"
         remove_one_file(x)
 
-@pytest.fixture
-def fixture_cv_file():
-    """add/remove file"""
-    remove_file(CV_FILE_NAME)
-    yield "yield_fixture_data"
-    remove_file(CV_FILE_NAME)
-
-@pytest.fixture
-def fixture_nlp_file():
-    """add/remove file"""
-    remove_file(NLP_FILE_NAME)
-    yield "yield_fixture_data"
-    remove_file(NLP_FILE_NAME)
-
 def test_cv_file_writer_shard_num_none():
     """test cv file writer when shard num is None."""
     with pytest.raises(Exception, match="Shard num is illegal."):
@@ -71,29 +55,29 @@ def test_cv_file_writer_shard_num_str():
 def test_cv_page_reader_consumer_num_none():
     """test cv page reader when consumer number is None."""
     with pytest.raises(Exception, match="Consumer number is illegal."):
-        MindPage(CV_FILE_NAME + "0", None)
+        MindPage("dummy.mindrecord", None)
 
 
 def test_cv_page_reader_consumer_num_str():
     """test cv page reader when consumer number is string."""
     with pytest.raises(Exception, match="Consumer number is illegal."):
-        MindPage(CV_FILE_NAME + "0", "2")
+        MindPage("dummy.mindrecord", "2")
 
 
 def test_nlp_file_reader_consumer_num_none():
     """test nlp file reader when consumer number is None."""
     with pytest.raises(Exception, match="Consumer number is illegal."):
-        FileReader(NLP_FILE_NAME + "0", None)
+        FileReader("dummy.mindrecord", None)
 
 
 def test_nlp_file_reader_consumer_num_str():
     """test nlp file reader when consumer number is string."""
     with pytest.raises(Exception, match="Consumer number is illegal."):
-        FileReader(NLP_FILE_NAME + "0", "4")
+        FileReader("dummy.mindrecord", "4")
 
 
-def create_cv_mindrecord(files_num):
-    writer = FileWriter(CV_FILE_NAME, files_num)
+def create_cv_mindrecord(files_num, file_name):
+    writer = FileWriter(file_name, files_num)
     data = get_data("../data/mindrecord/testImageNetData/")
     cv_schema_json = {"file_name": {"type": "string"},
                       "label": {"type": "int64"}, "data": {"type": "bytes"}}
@@ -104,139 +88,218 @@ def create_cv_mindrecord(files_num):
 
 
 def test_lack_partition_and_db():
-    """test file reader when mindrecord file does not exist."""
+    """
+    Feature: FileReader
+    Description: test file reader when mindrecord file does not exist
+    Expectation: exception occur
+    """
     with pytest.raises(RuntimeError) as err:
         reader = FileReader('dummy.mindrecord')
         reader.close()
     assert 'Unexpected error. Invalid file, path:' in str(err.value)
 
-def test_lack_db(fixture_cv_file):
-    """test file reader when db file does not exist."""
-    create_cv_mindrecord(1)
-    os.remove("{}.db".format(CV_FILE_NAME))
+def test_lack_db():
+    """
+    Feature: FileReader
+    Description: test file reader when db file does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(1, file_name)
+    os.remove("{}.db".format(file_name))
     with pytest.raises(RuntimeError) as err:
-        reader = FileReader(CV_FILE_NAME)
+        reader = FileReader(file_name)
         reader.close()
     assert 'Unexpected error. Invalid database file, path:' in str(err.value)
+    remove_file(file_name)
 
-def test_lack_some_partition_and_db(fixture_cv_file):
-    """test file reader when some partition and db do not exist."""
-    create_cv_mindrecord(4)
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+def test_lack_some_partition_and_db():
+    """
+    Feature: FileReader
+    Description: test file reader when some partition and db do not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     os.remove("{}".format(paths[3]))
     os.remove("{}.db".format(paths[3]))
     with pytest.raises(RuntimeError) as err:
-        reader = FileReader(CV_FILE_NAME + "0")
+        reader = FileReader(file_name + "0")
         reader.close()
     assert 'Unexpected error. Invalid file, path:' in str(err.value)
+    remove_file(file_name)
 
-def test_lack_some_partition_first(fixture_cv_file):
-    """test file reader when first partition does not exist."""
-    create_cv_mindrecord(4)
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+def test_lack_some_partition_first():
+    """
+    Feature: FileReader
+    Description: test file reader when first partition does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     os.remove("{}".format(paths[0]))
     with pytest.raises(RuntimeError) as err:
-        reader = FileReader(CV_FILE_NAME + "0")
+        reader = FileReader(file_name + "0")
         reader.close()
     assert 'Unexpected error. Invalid file, path:' in str(err.value)
+    remove_file(file_name)
 
-def test_lack_some_partition_middle(fixture_cv_file):
-    """test file reader when some partition does not exist."""
-    create_cv_mindrecord(4)
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+def test_lack_some_partition_middle():
+    """
+    Feature: FileReader
+    Description: test file reader when some partition does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     os.remove("{}".format(paths[1]))
     with pytest.raises(RuntimeError) as err:
-        reader = FileReader(CV_FILE_NAME + "0")
+        reader = FileReader(file_name + "0")
         reader.close()
     assert 'Unexpected error. Invalid file, path:' in str(err.value)
+    remove_file(file_name)
 
-def test_lack_some_partition_last(fixture_cv_file):
-    """test file reader when last partition does not exist."""
-    create_cv_mindrecord(4)
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+def test_lack_some_partition_last():
+    """
+    Feature: FileReader
+    Description: test file reader when last partition does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     os.remove("{}".format(paths[3]))
     with pytest.raises(RuntimeError) as err:
-        reader = FileReader(CV_FILE_NAME + "0")
+        reader = FileReader(file_name + "0")
         reader.close()
     assert 'Unexpected error. Invalid file, path:' in str(err.value)
+    remove_file(file_name)
 
-def test_mindpage_lack_some_partition(fixture_cv_file):
-    """test page reader when some partition does not exist."""
-    create_cv_mindrecord(4)
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+def test_mindpage_lack_some_partition():
+    """
+    Feature: MindPage
+    Description: test page reader when some partition does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     os.remove("{}".format(paths[0]))
     with pytest.raises(RuntimeError) as err:
-        MindPage(CV_FILE_NAME + "0")
+        MindPage(file_name + "0")
     assert 'Unexpected error. Invalid file, path:' in str(err.value)
+    remove_file(file_name)
 
-def test_lack_some_db(fixture_cv_file):
-    """test file reader when some db does not exist."""
-    create_cv_mindrecord(4)
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+def test_lack_some_db():
+    """
+    Feature: FileReader
+    Description: test file reader when some db does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    paths = ["{}{}".format(file_name, str(x).rjust(1, '0'))
              for x in range(FILES_NUM)]
     os.remove("{}.db".format(paths[3]))
     with pytest.raises(RuntimeError) as err:
-        reader = FileReader(CV_FILE_NAME + "0")
+        reader = FileReader(file_name + "0")
         reader.close()
     assert 'Unexpected error. Invalid database file, path:' in str(err.value)
-
+    remove_file(file_name)
 
 def test_invalid_mindrecord():
-    """test file reader when the content of mindrecord is illegal."""
-    with open(CV_FILE_NAME, 'w') as f:
+    """
+    Feature: FileReader
+    Description: test file reader when the content of mindrecord is illegal
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    with open(file_name, 'w') as f:
         dummy = 's' * 100
         f.write(dummy)
     with pytest.raises(RuntimeError) as err:
-        FileReader(CV_FILE_NAME)
+        FileReader(file_name)
     assert "Unexpected error. Invalid file content, incorrect file or file header" in str(err.value)
-    os.remove(CV_FILE_NAME)
+    remove_file(file_name)
 
-def test_invalid_db(fixture_cv_file):
-    """test file reader when the content of db is illegal."""
-    create_cv_mindrecord(1)
-    os.remove("imagenet.mindrecord.db")
-    with open('imagenet.mindrecord.db', 'w') as f:
+def test_invalid_db():
+    """
+    Feature: FileReader
+    Description: test file reader when the content of db is illegal
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(1, file_name)
+    os.remove(file_name + ".db")
+    with open(file_name + ".db", 'w') as f:
         f.write('just for test')
     with pytest.raises(RuntimeError) as err:
-        FileReader('imagenet.mindrecord')
+        FileReader(file_name)
     assert "Unexpected error. Failed to execute sql [ SELECT NAME from SHARD_NAME; ], " in str(err.value)
+    remove_file(file_name)
 
-def test_overwrite_invalid_mindrecord(fixture_cv_file):
-    """test file writer when overwrite invalid mindreocrd file."""
-    with open(CV_FILE_NAME, 'w') as f:
+def test_overwrite_invalid_mindrecord():
+    """
+    Feature: FileWriter
+    Description: test file writer when overwrite invalid mindreocrd file
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    with open(file_name, 'w') as f:
         f.write('just for test')
     with pytest.raises(RuntimeError) as err:
-        create_cv_mindrecord(1)
+        create_cv_mindrecord(1, file_name)
     assert 'Unexpected error. Invalid file, Mindrecord files already existed in path:' in str(err.value)
+    remove_file(file_name)
 
-def test_overwrite_invalid_db(fixture_cv_file):
-    """test file writer when overwrite invalid db file."""
-    with open('imagenet.mindrecord.db', 'w') as f:
+def test_overwrite_invalid_db():
+    """
+    Feature: FileWriter
+    Description: test file writer when overwrite invalid db file
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    with open(file_name + '.db', 'w') as f:
         f.write('just for test')
     with pytest.raises(RuntimeError) as err:
-        create_cv_mindrecord(1)
+        create_cv_mindrecord(1, file_name)
     assert 'Unexpected error. Failed to write data to db.' in str(err.value)
+    remove_file(file_name)
 
-def test_read_after_close(fixture_cv_file):
-    """test file reader when close read."""
-    create_cv_mindrecord(1)
-    reader = FileReader(CV_FILE_NAME)
+def test_read_after_close():
+    """
+    Feature: FileReader
+    Description: test file reader when close read
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(1, file_name)
+    reader = FileReader(file_name)
     reader.close()
     count = 0
     for index, x in enumerate(reader.get_next()):
         count = count + 1
         logger.info("#item{}: {}".format(index, x))
     assert count == 0
+    remove_file(file_name)
 
-def test_file_read_after_read(fixture_cv_file):
-    """test file reader when finish read."""
-    create_cv_mindrecord(1)
-    reader = FileReader(CV_FILE_NAME)
+def test_file_read_after_read():
+    """
+    Feature: FileReader
+    Description: test file reader when finish read
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(1, file_name)
+    reader = FileReader(file_name)
     count = 0
     for index, x in enumerate(reader.get_next()):
         assert len(x) == 3
@@ -249,25 +312,40 @@ def test_file_read_after_read(fixture_cv_file):
         cnt = cnt + 1
         logger.info("#item{}: {}".format(index, x))
     assert cnt == 0
+    remove_file(file_name)
 
 
 def test_cv_file_writer_shard_num_greater_than_1000():
-    """test cv file writer shard number greater than 1000."""
+    """
+    Feature: FileWriter
+    Description: test cv file writer shard number greater than 1000
+    Expectation: exception occur
+    """
     with pytest.raises(ParamValueError) as err:
-        FileWriter(CV_FILE_NAME, 1001)
+        FileWriter('dummy.mindrecord', 1001)
     assert 'Shard number should between' in str(err.value)
 
 
 def test_add_index_without_add_schema():
+    """
+    Feature: FileWriter
+    Description: test add index without adding schema
+    Expectation: exception occur
+    """
     with pytest.raises(MRMGetMetaError) as err:
-        fw = FileWriter(CV_FILE_NAME)
+        fw = FileWriter('dummy.mindrecord')
         fw.add_index(["label"])
     assert 'Failed to get meta info' in str(err.value)
 
-def test_mindpage_pageno_pagesize_not_int(fixture_cv_file):
-    """test page reader when some partition does not exist."""
-    create_cv_mindrecord(4)
-    reader = MindPage(CV_FILE_NAME + "0")
+def test_mindpage_pageno_pagesize_not_int():
+    """
+    Feature: MindPage
+    Description: test page reader when some partition does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    reader = MindPage(file_name + "0")
     fields = reader.get_category_fields()
     assert fields == ['file_name', 'label'], \
         'failed on getting candidate category fields.'
@@ -293,12 +371,18 @@ def test_mindpage_pageno_pagesize_not_int(fixture_cv_file):
     with pytest.raises(RuntimeError, match=r"Unexpected error. Invalid data, "
                        r"category_id: 99999 must be in the range \[0, 10\]."):
         reader.read_at_page_by_id(99999, 0, 1)
+    remove_file(file_name)
 
 
-def test_mindpage_filename_not_exist(fixture_cv_file):
-    """test page reader when some partition does not exist."""
-    create_cv_mindrecord(4)
-    reader = MindPage(CV_FILE_NAME + "0")
+def test_mindpage_filename_not_exist():
+    """
+    Feature: FileWrite
+    Description: test page reader when some partition does not exist
+    Expectation: exception occur
+    """
+    file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
+    create_cv_mindrecord(4, file_name)
+    reader = MindPage(file_name + "0")
     fields = reader.get_category_fields()
     assert fields == ['file_name', 'label'], \
         'failed on getting candidate category fields.'
@@ -319,11 +403,15 @@ def test_mindpage_filename_not_exist(fixture_cv_file):
     with pytest.raises(ParamValueError):
         reader.read_at_page_by_name(1, 0, 1)
 
-    _ = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
-         for x in range(FILES_NUM)]
+    remove_file(file_name)
 
 def test_invalid_schema():
-    mindrecord_file_name = "test.mindrecord"
+    """
+    Feature: FileWrite
+    Description: test invalid schema
+    Expectation: exception occur
+    """
+    mindrecord_file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
     writer = FileWriter(mindrecord_file_name)
 
     # string  =>  str
@@ -462,7 +550,7 @@ def test_invalid_schema():
         os.remove("{}.db".format(mindrecord_file_name))
 
 def test_write_with_invalid_data():
-    mindrecord_file_name = "test.mindrecord"
+    mindrecord_file_name = os.environ.get('PYTEST_CURRENT_TEST').split(':')[-1].split(' ')[0]
 
     # field: file_name  =>  filename
     with pytest.raises(RuntimeError, match="Unexpected error. Invalid data, schema count should be positive."):