Cleanup dataset UT: Replace save_and_check

tests/ut/data/dataset/testImageNetData2/dataDistributionAll.json

-{
-  "deviceNum":4,
-  "deviceId": 2,
-  "shardConfig":"ALL",
-  "shuffle":"ON",
-  "seed": 0,
-  "epoch": 2
-}

tests/ut/data/dataset/testImageNetData2/dataDistributionRandom.json

-{
-  "deviceNum":4,
-  "deviceId": 2,
-  "shardConfig":"RANDOM",
-  "shuffle":"ON",
-  "seed": 0,
-  "epoch": 1
-}

tests/ut/data/dataset/testImageNetData2/dataDistributionUnique.json

-{
-  "deviceNum":4,
-  "deviceId": 2,
-  "shardConfig":"UNIQUE",
-  "shuffle":"ON",
-  "seed": 0,
-  "epoch": 3
-}

tests/ut/data/dataset/testPK/distribution.json

-{
-  "deviceNum":1,
-  "deviceId": 0,
-  "shardConfig":"RANDOM",
-  "shuffle":"OFF",
-  "seed": 0
-}

tests/ut/python/dataset/test_2ops.py

@@ -12,15 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
-from util import save_and_check
-
 import mindspore.dataset as ds
 from mindspore import log as logger
+from util import save_and_check_dict
 
 DATA_DIR = ["../data/dataset/testTFTestAllTypes/test.data"]
 SCHEMA_DIR = "../data/dataset/testTFTestAllTypes/datasetSchema.json"
-COLUMNS = ["col_1d", "col_2d", "col_3d", "col_binary", "col_float",
-           "col_sint16", "col_sint32", "col_sint64"]
 GENERATE_GOLDEN = False
 
 
@@ -33,9 +30,6 @@ def test_2ops_repeat_shuffle():
     repeat_count = 2
     buffer_size = 5
     seed = 0
-    parameters = {"params": {'repeat_count': repeat_count,
-                             'buffer_size': buffer_size,
-                             'seed': seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
@@ -44,7 +38,7 @@ def test_2ops_repeat_shuffle():
     data1 = data1.shuffle(buffer_size=buffer_size)
 
     filename = "test_2ops_repeat_shuffle.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_2ops_shuffle_repeat():
@@ -56,10 +50,6 @@ def test_2ops_shuffle_repeat():
     repeat_count = 2
     buffer_size = 5
     seed = 0
-    parameters = {"params": {'repeat_count': repeat_count,
-                             'buffer_size': buffer_size,
-                             'reshuffle_each_iteration': False,
-                             'seed': seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
@@ -68,7 +58,7 @@ def test_2ops_shuffle_repeat():
     data1 = data1.repeat(repeat_count)
 
     filename = "test_2ops_shuffle_repeat.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_2ops_repeat_batch():
@@ -79,8 +69,6 @@ def test_2ops_repeat_batch():
     # define parameters
     repeat_count = 2
     batch_size = 5
-    parameters = {"params": {'repeat_count': repeat_count,
-                             'batch_size': batch_size}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
@@ -88,7 +76,7 @@ def test_2ops_repeat_batch():
     data1 = data1.batch(batch_size, drop_remainder=True)
 
     filename = "test_2ops_repeat_batch.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_2ops_batch_repeat():
@@ -99,8 +87,6 @@ def test_2ops_batch_repeat():
     # define parameters
     repeat_count = 2
     batch_size = 5
-    parameters = {"params": {'repeat_count': repeat_count,
-                             'batch_size': batch_size}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
@@ -108,7 +94,7 @@ def test_2ops_batch_repeat():
     data1 = data1.repeat(repeat_count)
 
     filename = "test_2ops_batch_repeat.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_2ops_batch_shuffle():
@@ -120,9 +106,6 @@ def test_2ops_batch_shuffle():
     buffer_size = 5
     seed = 0
     batch_size = 2
-    parameters = {"params": {'buffer_size': buffer_size,
-                             'seed': seed,
-                             'batch_size': batch_size}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
@@ -131,7 +114,7 @@ def test_2ops_batch_shuffle():
     data1 = data1.shuffle(buffer_size=buffer_size)
 
     filename = "test_2ops_batch_shuffle.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_2ops_shuffle_batch():
@@ -143,9 +126,6 @@ def test_2ops_shuffle_batch():
     buffer_size = 5
     seed = 0
     batch_size = 2
-    parameters = {"params": {'buffer_size': buffer_size,
-                             'seed': seed,
-                             'batch_size': batch_size}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
@@ -154,7 +134,7 @@ def test_2ops_shuffle_batch():
     data1 = data1.batch(batch_size, drop_remainder=True)
 
     filename = "test_2ops_shuffle_batch.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 if __name__ == '__main__':

tests/ut/python/dataset/test_batch.py

@@ -14,7 +14,7 @@
 # ==============================================================================
 import mindspore.dataset as ds
 from mindspore import log as logger
-from util import save_and_check
+from util import save_and_check_dict
 
 # Note: Number of rows in test.data dataset:  12
 DATA_DIR = ["../data/dataset/testTFTestAllTypes/test.data"]
@@ -29,8 +29,6 @@ def test_batch_01():
     # define parameters
     batch_size = 2
     drop_remainder = True
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -38,7 +36,7 @@ def test_batch_01():
 
     assert sum([1 for _ in data1]) == 6
     filename = "batch_01_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_02():
@@ -49,8 +47,6 @@ def test_batch_02():
     # define parameters
     batch_size = 5
     drop_remainder = True
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -58,7 +54,7 @@ def test_batch_02():
 
     assert sum([1 for _ in data1]) == 2
     filename = "batch_02_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_03():
@@ -69,8 +65,6 @@ def test_batch_03():
     # define parameters
     batch_size = 3
     drop_remainder = False
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -78,7 +72,7 @@ def test_batch_03():
 
     assert sum([1 for _ in data1]) == 4
     filename = "batch_03_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_04():
@@ -89,8 +83,6 @@ def test_batch_04():
     # define parameters
     batch_size = 7
     drop_remainder = False
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -98,7 +90,7 @@ def test_batch_04():
 
     assert sum([1 for _ in data1]) == 2
     filename = "batch_04_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_05():
@@ -108,7 +100,6 @@ def test_batch_05():
     logger.info("test_batch_05")
     # define parameters
     batch_size = 1
-    parameters = {"params": {'batch_size': batch_size}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -116,7 +107,7 @@ def test_batch_05():
 
     assert sum([1 for _ in data1]) == 12
     filename = "batch_05_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_06():
@@ -127,8 +118,6 @@ def test_batch_06():
     # define parameters
     batch_size = 12
     drop_remainder = False
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -136,7 +125,7 @@ def test_batch_06():
 
     assert sum([1 for _ in data1]) == 1
     filename = "batch_06_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_07():
@@ -148,9 +137,6 @@ def test_batch_07():
     batch_size = 4
     drop_remainder = False
     num_parallel_workers = 2
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder,
-                             'num_parallel_workers': num_parallel_workers}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -159,7 +145,7 @@ def test_batch_07():
 
     assert sum([1 for _ in data1]) == 3
     filename = "batch_07_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_08():
@@ -170,8 +156,6 @@ def test_batch_08():
     # define parameters
     batch_size = 6
     num_parallel_workers = 1
-    parameters = {"params": {'batch_size': batch_size,
-                             'num_parallel_workers': num_parallel_workers}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -179,7 +163,7 @@ def test_batch_08():
 
     assert sum([1 for _ in data1]) == 2
     filename = "batch_08_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_09():
@@ -190,8 +174,6 @@ def test_batch_09():
     # define parameters
     batch_size = 13
     drop_remainder = False
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -199,7 +181,7 @@ def test_batch_09():
 
     assert sum([1 for _ in data1]) == 1
     filename = "batch_09_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_10():
@@ -210,8 +192,6 @@ def test_batch_10():
     # define parameters
     batch_size = 99
     drop_remainder = True
-    parameters = {"params": {'batch_size': batch_size,
-                             'drop_remainder': drop_remainder}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -219,7 +199,7 @@ def test_batch_10():
 
     assert sum([1 for _ in data1]) == 0
     filename = "batch_10_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_11():
@@ -229,7 +209,6 @@ def test_batch_11():
     logger.info("test_batch_11")
     # define parameters
     batch_size = 1
-    parameters = {"params": {'batch_size': batch_size}}
 
     # apply dataset operations
     # Use schema file with 1 row
@@ -239,7 +218,7 @@ def test_batch_11():
 
     assert sum([1 for _ in data1]) == 1
     filename = "batch_11_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_12():
@@ -249,7 +228,6 @@ def test_batch_12():
     logger.info("test_batch_12")
     # define parameters
     batch_size = True
-    parameters = {"params": {'batch_size': batch_size}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -257,7 +235,7 @@ def test_batch_12():
 
     assert sum([1 for _ in data1]) == 12
     filename = "batch_12_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_batch_exception_01():

tests/ut/python/dataset/test_datasets_clue.py

@@ -356,9 +356,13 @@ def test_clue_to_device():
 
 if __name__ == "__main__":
     test_clue()
+    test_clue_num_shards()
+    test_clue_num_samples()
+    test_textline_dataset_get_datasetsize()
     test_clue_afqmc()
     test_clue_cmnli()
     test_clue_csl()
     test_clue_iflytek()
     test_clue_tnews()
     test_clue_wsc()
+    test_clue_to_device()

tests/ut/python/dataset/test_generator.py → tests/ut/python/dataset/test_datasets_generator.py

@@ -26,7 +26,7 @@ def generator_1d():
         yield (np.array([i]),)
 
 
-def test_case_0():
+def test_generator_0():
     """
     Test 1D Generator
     """
@@ -48,7 +48,7 @@ def generator_md():
         yield (np.array([[i, i + 1], [i + 2, i + 3]]),)
 
 
-def test_case_1():
+def test_generator_1():
     """
     Test MD Generator
     """
@@ -70,7 +70,7 @@ def generator_mc(maxid=64):
         yield (np.array([i]), np.array([[i, i + 1], [i + 2, i + 3]]))
 
 
-def test_case_2():
+def test_generator_2():
     """
     Test multi column generator
     """
@@ -88,7 +88,7 @@ def test_case_2():
         i = i + 1
 
 
-def test_case_3():
+def test_generator_3():
     """
     Test 1D Generator + repeat(4)
     """
@@ -108,7 +108,7 @@ def test_case_3():
             i = 0
 
 
-def test_case_4():
+def test_generator_4():
     """
     Test fixed size 1D Generator + batch
     """
@@ -146,7 +146,7 @@ def type_tester(t):
         i = i + 4
 
 
-def test_case_5():
+def test_generator_5():
     """
     Test 1D Generator on different data type
     """
@@ -173,7 +173,7 @@ def type_tester_with_type_check(t, c):
         i = i + 4
 
 
-def test_case_6():
+def test_generator_6():
     """
     Test 1D Generator on different data type with type check
     """
@@ -208,7 +208,7 @@ def type_tester_with_type_check_2c(t, c):
         i = i + 4
 
 
-def test_case_7():
+def test_generator_7():
     """
     Test 2 column Generator on different data type with type check
     """
@@ -223,7 +223,7 @@ def test_case_7():
         type_tester_with_type_check_2c(np_types[i], [None, de_types[i]])
 
 
-def test_case_8():
+def test_generator_8():
     """
     Test multi column generator with few mapops
     """
@@ -249,7 +249,7 @@ def test_case_8():
         i = i + 1
 
 
-def test_case_9():
+def test_generator_9():
     """
     Test map column order when len(input_columns) == len(output_columns).
     """
@@ -280,7 +280,7 @@ def test_case_9():
         i = i + 1
 
 
-def test_case_10():
+def test_generator_10():
     """
     Test map column order when len(input_columns) != len(output_columns).
     """
@@ -303,7 +303,7 @@ def test_case_10():
         i = i + 1
 
 
-def test_case_11():
+def test_generator_11():
     """
     Test map column order when len(input_columns) != len(output_columns).
     """
@@ -327,7 +327,7 @@ def test_case_11():
         i = i + 1
 
 
-def test_case_12():
+def test_generator_12():
     """
     Test map column order when input_columns and output_columns are None.
     """
@@ -361,7 +361,7 @@ def test_case_12():
         i = i + 1
 
 
-def test_case_13():
+def test_generator_13():
     """
     Test map column order when input_columns is None.
     """
@@ -391,7 +391,7 @@ def test_case_13():
         i = i + 1
 
 
-def test_case_14():
+def test_generator_14():
     """
     Test 1D Generator MP + CPP sampler
     """
@@ -408,7 +408,7 @@ def test_case_14():
             i = 0
 
 
-def test_case_15():
+def test_generator_15():
     """
     Test 1D Generator MP + Python sampler
     """
@@ -426,7 +426,7 @@ def test_case_15():
             i = 0
 
 
-def test_case_16():
+def test_generator_16():
     """
     Test multi column generator Mp + CPP sampler
     """
@@ -445,7 +445,7 @@ def test_case_16():
         i = i + 1
 
 
-def test_case_17():
+def test_generator_17():
     """
     Test multi column generator Mp + Python sampler
     """
@@ -465,7 +465,7 @@ def test_case_17():
         i = i + 1
 
 
-def test_case_error_1():
+def test_generator_error_1():
     def generator_np():
         for i in range(64):
             yield (np.array([{i}]),)
@@ -477,7 +477,7 @@ def test_case_error_1():
     assert "Invalid data type" in str(info.value)
 
 
-def test_case_error_2():
+def test_generator_error_2():
     def generator_np():
         for i in range(64):
             yield ({i},)
@@ -489,7 +489,7 @@ def test_case_error_2():
     assert "Generator should return a tuple of numpy arrays" in str(info.value)
 
 
-def test_case_error_3():
+def test_generator_error_3():
     with pytest.raises(ValueError) as info:
         # apply dataset operations
         data1 = ds.GeneratorDataset(generator_mc(2048), ["label", "image"])
@@ -501,7 +501,7 @@ def test_case_error_3():
     assert "When (len(input_columns) != len(output_columns)), columns_order must be specified." in str(info.value)
 
 
-def test_case_error_4():
+def test_generator_error_4():
     with pytest.raises(RuntimeError) as info:
         # apply dataset operations
         data1 = ds.GeneratorDataset(generator_mc(2048), ["label", "image"])
@@ -513,7 +513,7 @@ def test_case_error_4():
     assert "Unexpected error. Result of a tensorOp doesn't match output column names" in str(info.value)
 
 
-def test_sequential_sampler():
+def test_generator_sequential_sampler():
     source = [(np.array([x]),) for x in range(64)]
     ds1 = ds.GeneratorDataset(source, ["data"], sampler=ds.SequentialSampler())
     i = 0
@@ -523,14 +523,14 @@ def test_sequential_sampler():
         i = i + 1
 
 
-def test_random_sampler():
+def test_generator_random_sampler():
     source = [(np.array([x]),) for x in range(64)]
     ds1 = ds.GeneratorDataset(source, ["data"], shuffle=True)
     for _ in ds1.create_dict_iterator():  # each data is a dictionary
         pass
 
 
-def test_distributed_sampler():
+def test_generator_distributed_sampler():
     source = [(np.array([x]),) for x in range(64)]
     for sid in range(8):
         ds1 = ds.GeneratorDataset(source, ["data"], shuffle=False, num_shards=8, shard_id=sid)
@@ -541,7 +541,7 @@ def test_distributed_sampler():
             i = i + 8
 
 
-def test_num_samples():
+def test_generator_num_samples():
     source = [(np.array([x]),) for x in range(64)]
     num_samples = 32
     ds1 = ds.GeneratorDataset(source, ["data"], sampler=ds.SequentialSampler(num_samples=num_samples))
@@ -564,7 +564,7 @@ def test_num_samples():
     assert count == num_samples
 
 
-def test_num_samples_underflow():
+def test_generator_num_samples_underflow():
     source = [(np.array([x]),) for x in range(64)]
     num_samples = 256
     ds2 = ds.GeneratorDataset(source, ["data"], sampler=[i for i in range(64)], num_samples=num_samples)
@@ -600,7 +600,7 @@ def type_tester_with_type_check_2c_schema(t, c):
         i = i + 4
 
 
-def test_schema():
+def test_generator_schema():
     """
     Test 2 column Generator on different data type with type check with schema input
     """
@@ -615,9 +615,9 @@ def test_schema():
         type_tester_with_type_check_2c_schema(np_types[i], [de_types[i], de_types[i]])
 
 
-def manual_test_keyborad_interrupt():
+def manual_test_generator_keyboard_interrupt():
     """
-    Test keyborad_interrupt
+    Test keyboard_interrupt
     """
     logger.info("Test 1D Generator MP : 0 - 63")
 
@@ -635,31 +635,31 @@ def manual_test_keyborad_interrupt():
 
 
 if __name__ == "__main__":
-    test_case_0()
-    test_case_1()
-    test_case_2()
-    test_case_3()
-    test_case_4()
-    test_case_5()
-    test_case_6()
-    test_case_7()
-    test_case_8()
-    test_case_9()
-    test_case_10()
-    test_case_11()
-    test_case_12()
-    test_case_13()
-    test_case_14()
-    test_case_15()
-    test_case_16()
-    test_case_17()
-    test_case_error_1()
-    test_case_error_2()
-    test_case_error_3()
-    test_case_error_4()
-    test_sequential_sampler()
-    test_distributed_sampler()
-    test_random_sampler()
-    test_num_samples()
-    test_num_samples_underflow()
-    test_schema()
+    test_generator_0()
+    test_generator_1()
+    test_generator_2()
+    test_generator_3()
+    test_generator_4()
+    test_generator_5()
+    test_generator_6()
+    test_generator_7()
+    test_generator_8()
+    test_generator_9()
+    test_generator_10()
+    test_generator_11()
+    test_generator_12()
+    test_generator_13()
+    test_generator_14()
+    test_generator_15()
+    test_generator_16()
+    test_generator_17()
+    test_generator_error_1()
+    test_generator_error_2()
+    test_generator_error_3()
+    test_generator_error_4()
+    test_generator_sequential_sampler()
+    test_generator_distributed_sampler()
+    test_generator_random_sampler()
+    test_generator_num_samples()
+    test_generator_num_samples_underflow()
+    test_generator_schema()

tests/ut/python/dataset/test_iterator.py

@@ -33,7 +33,7 @@ def check(project_columns):
         assert all([np.array_equal(d1, d2) for d1, d2 in zip(data_actual, data_expected)])
 
 
-def test_case_iterator():
+def test_iterator_create_tuple():
     """
     Test creating tuple iterator
     """
@@ -95,7 +95,9 @@ class MyDict(dict):
 
 
 def test_tree_copy():
-    #  Testing copying the tree with a pyfunc that cannot be pickled
+    """
+    Testing copying the tree with a pyfunc that cannot be pickled
+    """
 
     data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=COLUMNS)
     data1 = data.map(operations=[MyDict()])
@@ -110,4 +112,6 @@ def test_tree_copy():
 
 
 if __name__ == '__main__':
+    test_iterator_create_tuple()
+    test_iterator_weak_ref()
     test_tree_copy()

tests/ut/python/dataset/test_shuffle.py

@@ -13,10 +13,9 @@
 # limitations under the License.
 # ==============================================================================
 import numpy as np
-from util import save_and_check
-
 import mindspore.dataset as ds
 from mindspore import log as logger
+from util import save_and_check_dict
 
 # Note: Number of rows in test.data dataset:  12
 DATA_DIR = ["../data/dataset/testTFTestAllTypes/test.data"]
@@ -31,7 +30,6 @@ def test_shuffle_01():
     # define parameters
     buffer_size = 5
     seed = 1
-    parameters = {"params": {'buffer_size': buffer_size, "seed": seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -39,7 +37,7 @@ def test_shuffle_01():
     data1 = data1.shuffle(buffer_size=buffer_size)
 
     filename = "shuffle_01_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_shuffle_02():
@@ -50,7 +48,6 @@ def test_shuffle_02():
     # define parameters
     buffer_size = 12
     seed = 1
-    parameters = {"params": {'buffer_size': buffer_size, "seed": seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -58,7 +55,7 @@ def test_shuffle_02():
     data1 = data1.shuffle(buffer_size=buffer_size)
 
     filename = "shuffle_02_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_shuffle_03():
@@ -69,7 +66,6 @@ def test_shuffle_03():
     # define parameters
     buffer_size = 2
     seed = 1
-    parameters = {"params": {'buffer_size': buffer_size, "seed": seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -77,7 +73,7 @@ def test_shuffle_03():
     data1 = data1.shuffle(buffer_size)
 
     filename = "shuffle_03_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_shuffle_04():
@@ -88,7 +84,6 @@ def test_shuffle_04():
     # define parameters
     buffer_size = 2
     seed = 1
-    parameters = {"params": {'buffer_size': buffer_size, "seed": seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, num_samples=2)
@@ -96,7 +91,7 @@ def test_shuffle_04():
     data1 = data1.shuffle(buffer_size=buffer_size)
 
     filename = "shuffle_04_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_shuffle_05():
@@ -107,7 +102,6 @@ def test_shuffle_05():
     # define parameters
     buffer_size = 13
     seed = 1
-    parameters = {"params": {'buffer_size': buffer_size, "seed": seed}}
 
     # apply dataset operations
     data1 = ds.TFRecordDataset(DATA_DIR, shuffle=ds.Shuffle.FILES)
@@ -115,7 +109,7 @@ def test_shuffle_05():
     data1 = data1.shuffle(buffer_size=buffer_size)
 
     filename = "shuffle_05_result.npz"
-    save_and_check(data1, parameters, filename, generate_golden=GENERATE_GOLDEN)
+    save_and_check_dict(data1, filename, generate_golden=GENERATE_GOLDEN)
 
 
 def test_shuffle_06():

tests/ut/python/dataset/util.py

@@ -24,9 +24,6 @@ import numpy as np
 import mindspore.dataset as ds
 from mindspore import log as logger
 
-# These are the column names defined in the testTFTestAllTypes dataset
-COLUMNS = ["col_1d", "col_2d", "col_3d", "col_binary", "col_float",
-           "col_sint16", "col_sint32", "col_sint64"]
 # These are list of plot title in different visualize modes
 PLOT_TITLE_DICT = {
     1: ["Original image", "Transformed image"],
@@ -82,39 +79,6 @@ def _save_json(filename, parameters, result_dict):
     fout.write(jsbeautifier.beautify(json.dumps(out_dict), options))
 
 
-def save_and_check(data, parameters, filename, generate_golden=False):
-    """
-    Save the dataset dictionary and compare (as numpy array) with golden file.
-    Use create_dict_iterator to access the dataset.
-    Note: save_and_check() is deprecated; use save_and_check_dict().
-    """
-    num_iter = 0
-    result_dict = {}
-    for column_name in COLUMNS:
-        result_dict[column_name] = []
-
-    for item in data.create_dict_iterator():  # each data is a dictionary
-        for data_key in list(item.keys()):
-            if data_key not in result_dict:
-                result_dict[data_key] = []
-            result_dict[data_key].append(item[data_key].tolist())
-        num_iter += 1
-
-    logger.info("Number of data in data1: {}".format(num_iter))
-
-    cur_dir = os.path.dirname(os.path.realpath(__file__))
-    golden_ref_dir = os.path.join(cur_dir, "../../data/dataset", 'golden', filename)
-    if generate_golden:
-        # Save as the golden result
-        _save_golden(cur_dir, golden_ref_dir, result_dict)
-
-    _compare_to_golden(golden_ref_dir, result_dict)
-
-    if SAVE_JSON:
-        # Save result to a json file for inspection
-        _save_json(filename, parameters, result_dict)
-
-
 def save_and_check_dict(data, filename, generate_golden=False):
     """
     Save the dataset dictionary and compare (as dictionary) with golden file.
@@ -203,6 +167,29 @@ def save_and_check_tuple(data, parameters, filename, generate_golden=False):
         _save_json(filename, parameters, result_dict)
 
 
+def config_get_set_seed(seed_new):
+    """
+    Get and return the original configuration seed value.
+    Set the new configuration seed value.
+    """
+    seed_original = ds.config.get_seed()
+    ds.config.set_seed(seed_new)
+    logger.info("seed: original = {}  new = {} ".format(seed_original, seed_new))
+    return seed_original
+
+
+def config_get_set_num_parallel_workers(num_parallel_workers_new):
+    """
+    Get and return the original configuration num_parallel_workers value.
+    Set the new configuration num_parallel_workers value.
+    """
+    num_parallel_workers_original = ds.config.get_num_parallel_workers()
+    ds.config.set_num_parallel_workers(num_parallel_workers_new)
+    logger.info("num_parallel_workers: original = {}  new = {} ".format(num_parallel_workers_original,
+                                                                        num_parallel_workers_new))
+    return num_parallel_workers_original
+
+
 def diff_mse(in1, in2):
     mse = (np.square(in1.astype(float) / 255 - in2.astype(float) / 255)).mean()
     return mse * 100
@@ -265,29 +252,6 @@ def visualize_image(image_original, image_de, mse=None, image_lib=None):
     plt.show()
 
 
-def config_get_set_seed(seed_new):
-    """
-    Get and return the original configuration seed value.
-    Set the new configuration seed value.
-    """
-    seed_original = ds.config.get_seed()
-    ds.config.set_seed(seed_new)
-    logger.info("seed: original = {}  new = {} ".format(seed_original, seed_new))
-    return seed_original
-
-
-def config_get_set_num_parallel_workers(num_parallel_workers_new):
-    """
-    Get and return the original configuration num_parallel_workers value.
-    Set the new configuration num_parallel_workers value.
-    """
-    num_parallel_workers_original = ds.config.get_num_parallel_workers()
-    ds.config.set_num_parallel_workers(num_parallel_workers_new)
-    logger.info("num_parallel_workers: original = {}  new = {} ".format(num_parallel_workers_original,
-                                                                        num_parallel_workers_new))
-    return num_parallel_workers_original
-
-
 def visualize_with_bounding_boxes(orig, aug, annot_name="annotation", plot_rows=3):
     """
     Take a list of un-augmented and augmented images with "annotation" bounding boxes