pylint clean

tests/mindspore_test_framework/apps/bert_attention_submodules.py

@@ -167,7 +167,7 @@ class BertAttentionMask(nn.Cell):
 
         super(BertAttentionMask, self).__init__()
         self.has_attention_mask = has_attention_mask
-        self.multiply_data = Tensor([-1000.0, ], dtype=dtype)
+        self.multiply_data = Tensor([-1000.0,], dtype=dtype)
         self.multiply = P.Mul()
 
         if self.has_attention_mask:
@@ -198,7 +198,7 @@ class BertAttentionMaskBackward(nn.Cell):
                  dtype=mstype.float32):
         super(BertAttentionMaskBackward, self).__init__()
         self.has_attention_mask = has_attention_mask
-        self.multiply_data = Tensor([-1000.0, ], dtype=dtype)
+        self.multiply_data = Tensor([-1000.0,], dtype=dtype)
         self.multiply = P.Mul()
         self.attention_mask = Tensor(np.ones(shape=attention_mask_shape).astype(np.float32))
         if self.has_attention_mask:

tests/st/networks/test_gpu_lstm.py

@@ -136,7 +136,7 @@ def test_LSTM():
     train_network.set_train()
 
     train_features = Tensor(np.ones([64, max_len]).astype(np.int32))
-    train_labels = Tensor(np.ones([64, ]).astype(np.int32)[0:64])
+    train_labels = Tensor(np.ones([64,]).astype(np.int32)[0:64])
     losses = []
     for epoch in range(num_epochs):
         loss = train_network(train_features, train_labels)

tests/ut/python/ir/test_tensor.py

@@ -34,7 +34,7 @@ ndarr = np.ones((2, 3))
 
 def test_tensor_flatten():
     with pytest.raises(AttributeError):
-        lst = [1, 2, 3, 4, ]
+        lst = [1, 2, 3, 4,]
         tensor_list = ms.Tensor(lst, ms.float32)
         tensor_list = tensor_list.Flatten()
         print(tensor_list)