diff --git a/mindspore/_checkparam.py b/mindspore/_checkparam.py
index 40a402bb49..e1edc32ce3 100644
--- a/mindspore/_checkparam.py
+++ b/mindspore/_checkparam.py
@@ -139,7 +139,7 @@ class Validator:
     def check_int_range(arg_name, arg_value, lower_limit, upper_limit, rel, prim_name):
         """Method for checking whether an int value is in some range."""
         rel_fn = Rel.get_fns(rel)
-        type_mismatch = not isinstance(arg_value, int)
+        type_mismatch = not isinstance(arg_value, int) or isinstance(arg_value, bool)
         excp_cls = TypeError if type_mismatch else ValueError
         if type_mismatch or not rel_fn(arg_value, lower_limit, upper_limit):
             rel_str = Rel.get_strs(rel).format(lower_limit, upper_limit)
diff --git a/mindspore/nn/layer/conv.py b/mindspore/nn/layer/conv.py
index 13f3ee4c23..b0bcba8522 100644
--- a/mindspore/nn/layer/conv.py
+++ b/mindspore/nn/layer/conv.py
@@ -461,7 +461,8 @@ class Conv2dTranspose(_Conv):
             width of the kernel.
         stride (Union[int, tuple[int]]): The distance of kernel moving, an int number that represents
             the height and width of movement are both strides, or a tuple of two int numbers that
-            represent height and width of movement respectively. Default: 1.
+            represent height and width of movement respectively. Its value should be equal to or greater than 1.
+            Default: 1.
         pad_mode (str): Select the mode of the pad. The optional values are
             "pad", "same", "valid". Default: "same".
 
diff --git a/mindspore/ops/operations/array_ops.py b/mindspore/ops/operations/array_ops.py
index 0a9116b63e..bfc2f31627 100644
--- a/mindspore/ops/operations/array_ops.py
+++ b/mindspore/ops/operations/array_ops.py
@@ -115,6 +115,8 @@ class ExpandDims(PrimitiveWithInfer):
         >>> input_tensor = Tensor(np.array([[2, 2], [2, 2]]), mindspore.float32)
         >>> expand_dims = P.ExpandDims()
         >>> output = expand_dims(input_tensor, 0)
+        [[[2.0, 2.0],
+          [2.0, 2.0]]]
     """
 
     @prim_attr_register
@@ -887,6 +889,8 @@ class Fill(PrimitiveWithInfer):
     Examples:
         >>> fill = P.Fill()
         >>> fill(mindspore.float32, (2, 2), 1)
+        [[1.0, 1.0],
+         [1.0, 1.0]]
     """
 
     @prim_attr_register
@@ -2364,6 +2368,8 @@ class Eye(PrimitiveWithInfer):
     Examples:
         >>> eye = P.Eye()
         >>> out_tensor = eye(2, 2, mindspore.int32)
+        [[1, 0],
+         [0, 1]]
     """
 
     @prim_attr_register
diff --git a/mindspore/ops/operations/math_ops.py b/mindspore/ops/operations/math_ops.py
index b4fd9bf28a..8355e4aa29 100644
--- a/mindspore/ops/operations/math_ops.py
+++ b/mindspore/ops/operations/math_ops.py
@@ -2244,10 +2244,10 @@ class Equal(_LogicBinaryOp):
     When the inputs are one tensor and one scalar, the scalar only could be a constant.
 
     Inputs:
-        - **input_x** (Union[Tensor, Number, bool]) - The first input is a number or
-          a bool or a tensor whose data type is number or bool.
-        - **input_y** (Union[Tensor, Number, bool]) - The second input is a number or
-          a bool when the first input is a tensor or a tensor whose data type is number or bool.
+        - **input_x** (Union[Tensor, Number]) - The first input is a number or
+          a tensor whose data type is number.
+        - **input_y** (Union[Tensor, Number]) - The second input is a number
+          when the first input is a tensor or a tensor whose data type is number.
 
     Outputs:
         Tensor, the shape is the same as the one after broadcasting,and the data type is bool.