!2832 check types for optional boolean parameters

Merge pull request !2832 from Peilin/invalid-type-bucket-check

mindspore/dataset/engine/validators.py

@@ -606,8 +606,15 @@ def check_bucket_batch_by_length(method):
         nreq_param_list = ['column_names', 'bucket_boundaries', 'bucket_batch_sizes']
         check_param_type(nreq_param_list, param_dict, list)
 
+        nbool_param_list = ['pad_to_bucket_boundary', 'drop_remainder']
+        check_param_type(nbool_param_list, param_dict, bool)
+
         # check column_names: must be list of string.
         column_names = param_dict.get("column_names")
+
+        if not column_names:
+            raise ValueError("column_names cannot be empty")
+
         all_string = all(isinstance(item, str) for item in column_names)
         if not all_string:
             raise TypeError("column_names should be a list of str.")

tests/ut/python/dataset/test_bucket_batch_by_length.py

@@ -53,6 +53,9 @@ def test_bucket_batch_invalid_input():
     negative_bucket_batch_sizes = [1, 2, 3, -4]
     zero_bucket_batch_sizes = [0, 1, 2, 3]
 
+    invalid_type_pad_to_bucket_boundary = ""
+    invalid_type_drop_remainder = ""
+
     with pytest.raises(TypeError) as info:
         _ = dataset.bucket_batch_by_length(invalid_column_names, bucket_boundaries, bucket_batch_sizes)
     assert "column_names should be a list of str" in str(info.value)
@@ -93,6 +96,16 @@ def test_bucket_batch_invalid_input():
         _ = dataset.bucket_batch_by_length(column_names, bucket_boundaries, bucket_boundaries)
     assert "bucket_batch_sizes must contain one element more than bucket_boundaries" in str(info.value)
 
+    with pytest.raises(TypeError) as info:
+        _ = dataset.bucket_batch_by_length(column_names, bucket_boundaries, bucket_batch_sizes,
+                                           None, None, invalid_type_pad_to_bucket_boundary)
+    assert "Wrong input type for pad_to_bucket_boundary, should be <class 'bool'>" in str(info.value)
+
+    with pytest.raises(TypeError) as info:
+        _ = dataset.bucket_batch_by_length(column_names, bucket_boundaries, bucket_batch_sizes,
+                                           None, None, False, invalid_type_drop_remainder)
+    assert "Wrong input type for drop_remainder, should be <class 'bool'>" in str(info.value)
+
 
 def test_bucket_batch_multi_bucket_no_padding():
     dataset = ds.GeneratorDataset((lambda: generate_sequential_same_shape(10)), ["col1"])