add paramter check for numpyslices and num_shards

mindspore/dataset/engine/datasets.py

@@ -3069,7 +3069,7 @@ class GeneratorDataset(MappableDataset):
         sampler (Sampler/Iterable, optional): Object used to choose samples from the dataset. Random accessible input is
             required (default=None, expected order behavior shown in the table).
         num_shards (int, optional): Number of shards that the dataset should be divided into (default=None).
-            This argument should be specified only when 'num_samples' is "None". Random accessible input is required.
+            When this argument is specified, 'num_samples' will not effect. Random accessible input is required.
         shard_id (int, optional): The shard ID within num_shards (default=None). This argument should be specified only
             when num_shards is also specified. Random accessible input is required.
 
@@ -4878,6 +4878,11 @@ class _NumpySlicesDataset:
         else:
             self.data = (np.array(data),)
 
+        # check whether the data length in each column is equal
+        data_len = [len(data_item) for data_item in self.data]
+        if data_len[1:] != data_len[:-1]:
+            raise ValueError("Data length in each column is not equal.")
+
         # Init column_name
         if column_list is not None:
             self.column_list = column_list
@@ -4966,7 +4971,7 @@ class NumpySlicesDataset(GeneratorDataset):
         sampler (Sampler/Iterable, optional): Object used to choose samples from the dataset. Random accessible input is
             required (default=None, expected order behavior shown in the table).
         num_shards (int, optional): Number of shards that the dataset should be divided into (default=None).
-            This argument should be specified only when 'num_samples' is "None". Random accessible input is required.
+            When this argument is specified, 'num_samples' will not effect. Random accessible input is required.
         shard_id (int, optional): The shard ID within num_shards (default=None). This argument should be specified only
             when num_shards is also specified. Random accessible input is required.
 

mindspore/dataset/engine/validators.py

@@ -153,6 +153,7 @@ def check_sampler_shuffle_shard_options(param_dict):
             raise RuntimeError("sampler and sharding cannot be specified at the same time.")
 
     if num_shards is not None:
+        check_positive_int32(num_shards, "num_shards")
         if shard_id is None:
             raise RuntimeError("num_shards is specified and currently requires shard_id as well.")
         if shard_id < 0 or shard_id >= num_shards:
@@ -529,6 +530,7 @@ def check_generatordataset(method):
             # These two parameters appear together.
             raise ValueError("num_shards and shard_id need to be passed in together")
         if num_shards is not None:
+            check_positive_int32(num_shards, "num_shards")
             if shard_id >= num_shards:
                 raise ValueError("shard_id should be less than num_shards")
 

tests/ut/python/dataset/test_minddataset_exception.py

@@ -185,7 +185,7 @@ def test_minddataset_invalidate_num_shards():
     columns_list = ["data", "label"]
     num_readers = 4
     with pytest.raises(Exception, match="shard_id is invalid, "):
-        data_set = ds.MindDataset(CV_FILE_NAME, columns_list, num_readers, True, 0, 1)
+        data_set = ds.MindDataset(CV_FILE_NAME, columns_list, num_readers, True, 1, 2)
         num_iter = 0
         for _ in data_set.create_dict_iterator():
             num_iter += 1