changed discription

Added validator checks

Added builtin sampler check

Added proper input check for samplers

mindspore/dataset/core/validator_helpers.py

@@ -16,12 +16,13 @@
 General Validators.
 """
 import inspect
+import numbers
 from multiprocessing import cpu_count
 import os
 import numpy as np
 
 import mindspore._c_dataengine as cde
-
+from ..engine import samplers
 # POS_INT_MIN is used to limit values from starting from 0
 POS_INT_MIN = 1
 UINT8_MAX = 255
@@ -288,6 +289,7 @@ def check_sampler_shuffle_shard_options(param_dict):
     shuffle, sampler = param_dict.get('shuffle'), param_dict.get('sampler')
     num_shards, shard_id = param_dict.get('num_shards'), param_dict.get('shard_id')
     num_samples = param_dict.get('num_samples')
+    check_sampler(sampler)
 
     if sampler is not None:
         if shuffle is not None:
@@ -384,6 +386,37 @@ def check_tensor_op(param, param_name):
     if not isinstance(param, cde.TensorOp) and not callable(param) and not getattr(param, 'parse', None):
         raise TypeError("{0} is neither a c_transform op (TensorOperation) nor a callable pyfunc.".format(param_name))
 
+def check_sampler(sampler):
+    """
+    Check if the sampler is of valid input.
+
+    Args:
+        param(Union[list, samplers.Sampler, samplers.BuiltinSampler, None]): sampler
+
+    Returns:
+        Exception: TypeError if error
+    """
+    builtin = False
+    base_sampler = False
+    list_num = False
+    if sampler is not None:
+        if isinstance(sampler, samplers.BuiltinSampler):
+            builtin = True
+        elif isinstance(sampler, samplers.Sampler):
+            base_sampler = True
+        else:
+            # check for list of numbers
+            list_num = True
+            # subset sampler check
+            subset_sampler = sampler
+            if not isinstance(sampler, list):
+                subset_sampler = [sampler]
+
+            for _, item in enumerate(subset_sampler):
+                if not isinstance(item, numbers.Number):
+                    list_num = False
+        if not (builtin or base_sampler or list_num):
+            raise TypeError("Argument sampler is not of type Sampler, BuiltinSamplers, or list of numbers")
 
 def replace_none(value, default):
     return value if value is not None else default

mindspore/dataset/engine/datasets.py

@@ -3535,7 +3535,8 @@ class TFRecordDataset(SourceDataset):
         shard_id (int, optional): The shard ID within num_shards (default=None). This
             argument can only be specified when num_shards is also specified.
         shard_equal_rows (bool, optional): Get equal rows for all shards(default=False). If shard_equal_rows
-            is false, number of rows of each shard may be not equal.
+            is false, number of rows of each shard may be not equal. This
+            argument should only be specified when num_shards is also specified.
         cache (DatasetCache, optional): Use tensor caching service to speed up dataset processing.
             (default=None, which means no cache is used).
 

tests/ut/python/dataset/test_datasets_celeba.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd.
+# Copyright 2020-2021 Huawei Technologies Co., Ltd.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -20,6 +20,10 @@ DATA_DIR = "../data/dataset/testCelebAData/"
 
 
 def test_celeba_dataset_label():
+    """
+    Test CelebA dataset with labels
+    """
+    logger.info("Test CelebA labels")
     data = ds.CelebADataset(DATA_DIR, shuffle=False, decode=True)
     expect_labels = [
         [0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1,
@@ -43,6 +47,10 @@ def test_celeba_dataset_label():
 
 
 def test_celeba_dataset_op():
+    """
+    Test CelebA dataset with decode
+    """
+    logger.info("Test CelebA with decode")
     data = ds.CelebADataset(DATA_DIR, decode=True, num_shards=1, shard_id=0)
     crop_size = (80, 80)
     resize_size = (24, 24)
@@ -62,6 +70,10 @@ def test_celeba_dataset_op():
 
 
 def test_celeba_dataset_ext():
+    """
+    Test CelebA dataset with extension
+    """
+    logger.info("Test CelebA extension option")
     ext = [".JPEG"]
     data = ds.CelebADataset(DATA_DIR, decode=True, extensions=ext)
     expect_labels = [
@@ -82,6 +94,10 @@ def test_celeba_dataset_ext():
 
 
 def test_celeba_dataset_distribute():
+    """
+    Test CelebA dataset with distributed options
+    """
+    logger.info("Test CelebA with sharding")
     data = ds.CelebADataset(DATA_DIR, decode=True, num_shards=2, shard_id=0)
     count = 0
     for item in data.create_dict_iterator(num_epochs=1):
@@ -94,6 +110,10 @@ def test_celeba_dataset_distribute():
 
 
 def test_celeba_get_dataset_size():
+    """
+    Test CelebA dataset get dataset size
+    """
+    logger.info("Test CelebA get dataset size")
     data = ds.CelebADataset(DATA_DIR, shuffle=False, decode=True)
     size = data.get_dataset_size()
     assert size == 4
@@ -112,6 +132,10 @@ def test_celeba_get_dataset_size():
 
 
 def test_celeba_dataset_exception_file_path():
+    """
+    Test CelebA dataset with bad file path
+    """
+    logger.info("Test CelebA with bad file path")
     def exception_func(item):
         raise Exception("Error occur!")
 
@@ -144,6 +168,20 @@ def test_celeba_dataset_exception_file_path():
         assert "map operation: [PyFunc] failed. The corresponding data files" in str(e)
 
 
+def test_celeba_sampler_exception():
+    """
+    Test CelebA with bad sampler input
+    """
+    logger.info("Test CelebA with bad sampler input")
+    try:
+        data = ds.CelebADataset(DATA_DIR, sampler="")
+        for _ in data.create_dict_iterator():
+            pass
+        assert False
+    except TypeError as e:
+        assert "Argument" in str(e)
+
+
 if __name__ == '__main__':
     test_celeba_dataset_label()
     test_celeba_dataset_op()
@@ -151,3 +189,4 @@ if __name__ == '__main__':
     test_celeba_dataset_distribute()
     test_celeba_get_dataset_size()
     test_celeba_dataset_exception_file_path()
+    test_celeba_sampler_exception()