[MD] Revert changes to weighted_random_sampler in PR7866

mindspore/dataset/engine/samplers.py

@@ -19,6 +19,7 @@ SequentialSampler, SubsetRandomSampler, and WeightedRandomSampler.
 Users can also define a custom sampler by extending from the Sampler class.
 """
 
+import numbers
 import numpy as np
 import mindspore._c_dataengine as cde
 import mindspore.dataset as ds
@@ -591,6 +592,20 @@ class WeightedRandomSampler(BuiltinSampler):
         if not isinstance(weights, list):
             weights = [weights]
 
+        for ind, w in enumerate(weights):
+            if not isinstance(w, numbers.Number):
+                raise TypeError("type of weights element should be number, "
+                                "but got w[{}]={}, type={}".format(ind, w, type(w)))
+
+        if weights == []:
+            raise ValueError("weights size should not be 0")
+
+        if list(filter(lambda x: x < 0, weights)) != []:
+            raise ValueError("weights should not contain negative numbers")
+
+        if list(filter(lambda x: x == 0, weights)) == weights:
+            raise ValueError("elements of weights should not be all zero")
+
         if num_samples is not None:
             if num_samples <= 0:
                 raise ValueError("num_samples should be a positive integer "

tests/ut/python/dataset/test_datasets_imagefolder.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ==============================================================================
+import pytest
 import mindspore.dataset as ds
 from mindspore import log as logger
 
@@ -382,6 +383,35 @@ def test_weighted_random_sampler():
     logger.info("Number of data in data1: {}".format(num_iter))
     assert num_iter == 11
 
+def test_weighted_random_sampler_exception():
+    """
+    Test error cases for WeightedRandomSampler
+    """
+    logger.info("Test error cases for WeightedRandomSampler")
+    error_msg_1 = "type of weights element should be number"
+    with pytest.raises(TypeError, match=error_msg_1):
+        weights = ""
+        ds.WeightedRandomSampler(weights)
+
+    error_msg_2 = "type of weights element should be number"
+    with pytest.raises(TypeError, match=error_msg_2):
+        weights = (0.9, 0.8, 1.1)
+        ds.WeightedRandomSampler(weights)
+
+    error_msg_3 = "weights size should not be 0"
+    with pytest.raises(ValueError, match=error_msg_3):
+        weights = []
+        ds.WeightedRandomSampler(weights)
+
+    error_msg_4 = "weights should not contain negative numbers"
+    with pytest.raises(ValueError, match=error_msg_4):
+        weights = [1.0, 0.1, 0.02, 0.3, -0.4]
+        ds.WeightedRandomSampler(weights)
+
+    error_msg_5 = "elements of weights should not be all zero"
+    with pytest.raises(ValueError, match=error_msg_5):
+        weights = [0, 0, 0, 0, 0]
+        ds.WeightedRandomSampler(weights)
 
 def test_imagefolder_rename():
     logger.info("Test Case rename")
@@ -465,6 +495,9 @@ if __name__ == '__main__':
     test_weighted_random_sampler()
     logger.info('test_weighted_random_sampler Ended.\n')
 
+    test_weighted_random_sampler_exception()
+    logger.info('test_weighted_random_sampler_exception Ended.\n')
+
     test_imagefolder_numshards()
     logger.info('test_imagefolder_numshards Ended.\n')