add print comment and fix some example

mindspore/ops/operations/comm_ops.py

@@ -65,7 +65,7 @@ class AllReduce(PrimitiveWithInfer):
         The contents depend on the specified operation.
 
     Examples:
-        >>> from mindspore.communication.management import init
+        >>> from mindspore.communication import init
         >>> import mindspore.ops.operations as P
         >>> init('nccl')
         >>> class Net(nn.Cell):
@@ -130,7 +130,7 @@ class AllGather(PrimitiveWithInfer):
         then the shape of output is :math:`(N, x_1, x_2, ..., x_R)`.
 
     Examples:
-        >>> from mindspore.communication.management import init
+        >>> from mindspore.communication import init
         >>> import mindspore.ops.operations as P
         >>> init('nccl')
         >>> class Net(nn.Cell):
@@ -187,7 +187,7 @@ class ReduceScatter(PrimitiveWithInfer):
         ValueError: If the first dimension of input can not be divided by rank size.
 
     Examples:
-        >>> from mindspore.communication.management import init
+        >>> from mindspore.communication import init
         >>> import mindspore.ops.operations as P
         >>> init('nccl')
         >>> class Net(nn.Cell):
@@ -252,7 +252,7 @@ class Broadcast(PrimitiveWithInfer):
         TypeError: If root_rank is not a integer or group is not a string.
 
     Examples:
-        >>> from mindspore.communication.management import init
+        >>> from mindspore.communication import init
         >>> import mindspore.ops.operations as P
         >>> init('nccl')
         >>> class Net(nn.Cell):

mindspore/ops/operations/debug_ops.py

@@ -161,6 +161,9 @@ class Print(PrimitiveWithInfer):
     """
     Output tensor or string to stdout.
 
+    Note:
+        The print operation cannot support float64 and bool types currently.
+
     Inputs:
         - **input_x** (Union[Tensor, str]) - The graph node to attach to. The input supports
           multiple strings and tensors which are separated by ','.

mindspore/ops/operations/other_ops.py

@@ -120,7 +120,7 @@ class BoundingBoxDecode(PrimitiveWithInfer):
 
     Examples:
         >>> boundingbox_decode = P.BoundingBoxDecode(means=(0.0, 0.0, 0.0, 0.0), stds=(1.0, 1.0, 1.0, 1.0),
-                                                   max_shape=(768, 1280), wh_ratio_clip=0.016)
+        >>>                                          max_shape=(768, 1280), wh_ratio_clip=0.016)
         >>> bbox = boundingbox_decode(anchor_box, deltas)
     """