diff --git a/mindspore/nn/layer/lstm.py b/mindspore/nn/layer/lstm.py
index 06ad5154ab..86d0e8e44a 100755
--- a/mindspore/nn/layer/lstm.py
+++ b/mindspore/nn/layer/lstm.py
@@ -63,7 +63,7 @@ class LSTM(Cell):
         num_layers (int): Number of layers of stacked LSTM . Default: 1.
         has_bias (bool): Specifies whether has bias `b_ih` and `b_hh`. Default: True.
         batch_first (bool): Specifies whether the first dimension of input is batch_size. Default: False.
-        dropout (float): If not 0, append `Dropout` layer on the outputs of each
+        dropout (float, int): If not 0, append `Dropout` layer on the outputs of each
             LSTM layer except the last layer. Default 0. The range of dropout is [0.0, 1.0].
         bidirectional (bool): Specifies whether this is a bidirectional LSTM. If set True,
             number of directions will be 2 otherwise number of directions is 1. Default: False.
diff --git a/mindspore/ops/operations/control_ops.py b/mindspore/ops/operations/control_ops.py
index 3f8d50857a..736855a046 100644
--- a/mindspore/ops/operations/control_ops.py
+++ b/mindspore/ops/operations/control_ops.py
@@ -154,14 +154,6 @@ class Merge(PrimitiveWithInfer):
         raise NotImplementedError
 
     def infer_shape(self, inputs):
-        validator.check_integer('inputs len', len(inputs), 0, Rel.GT, self.name)
-        input_0 = inputs[0]
-
-        for i in range(1, len(inputs)):
-            if inputs[i] != input_0:
-                raise ValueError(f"For \'{self.name}\', the shape of {i}th input should be same as "
-                                 f"first input {input_0}, but got {inputs[i]}.")
-
         return (inputs[0], [1])
 
     def infer_dtype(self, inputs):