From 6c7957f0dd2ae8abb366e56001d426c6e75d4cca Mon Sep 17 00:00:00 2001
From: lianliguang <lianliguang@huawei.com>
Date: Mon, 21 Feb 2022 18:06:28 +0800
Subject: [PATCH] change api of DynamicShape ops

---
 .../ops/mindspore.ops.DynamicShape.rst        |  6 ++++
 .../ops/mindspore.ops.TensorShape.rst         | 18 ++++++++++
 .../mindspore/ops/operations/array_ops.py     | 36 ++-----------------
 3 files changed, 27 insertions(+), 33 deletions(-)
 create mode 100644 docs/api/api_python/ops/mindspore.ops.DynamicShape.rst
 create mode 100644 docs/api/api_python/ops/mindspore.ops.TensorShape.rst

diff --git a/docs/api/api_python/ops/mindspore.ops.DynamicShape.rst b/docs/api/api_python/ops/mindspore.ops.DynamicShape.rst
new file mode 100644
index 00000000000..841c303bb92
--- /dev/null
+++ b/docs/api/api_python/ops/mindspore.ops.DynamicShape.rst
@@ -0,0 +1,6 @@
+mindspore.ops.DynamicShape
+=================
+
+.. py:class:: mindspore.ops.DynamicShape()
+
+与`TensorShape`相同，`DynamicShape`将会被`TensorShape`替换，请使用`TensorShape`。
diff --git a/docs/api/api_python/ops/mindspore.ops.TensorShape.rst b/docs/api/api_python/ops/mindspore.ops.TensorShape.rst
new file mode 100644
index 00000000000..1095335935f
--- /dev/null
+++ b/docs/api/api_python/ops/mindspore.ops.TensorShape.rst
@@ -0,0 +1,18 @@
+mindspore.ops.TensorShape
+=================
+
+.. py:class:: mindspore.ops.TensorShape()
+
+    返回输入Tensor的Shape。
+
+    **输入：**
+
+    - **input_x** (Tensor) - 第一个输入，是一个Tensor类型数据
+
+    **输出：**
+
+    Tensor，输入`input_x`的shape
+
+    **异常：**
+
+    - **TypeError** - `input_x` 都不是Tensor。
diff --git a/mindspore/python/mindspore/ops/operations/array_ops.py b/mindspore/python/mindspore/ops/operations/array_ops.py
index 2b5c139af06..4f018db05e0 100755
--- a/mindspore/python/mindspore/ops/operations/array_ops.py
+++ b/mindspore/python/mindspore/ops/operations/array_ops.py
@@ -637,13 +637,7 @@ class Shape(Primitive):
 
 class TensorShape(Primitive):
     """
-    Returns the shape of the input tensor. And it used to be dynamic shape.
-
-    Note:
-        Dynamic shape: After the graph is running, as the tensor flows in the graph, the specific shape of the tensor
-        on each node on the graph can be inferred according to the structure of the graph.
-        This shape is called a dynamic shape. As the input shape of the graph is different,
-        the dynamic shape of the tensor in the graph will change.
+    Returns the shape of the input tensor.
 
     Inputs:
         - **input_x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
@@ -671,32 +665,8 @@ class TensorShape(Primitive):
 
 class DynamicShape(Primitive):
     """
-    Returns the shape of the input tensor. And it used to be dynamic shape.
-
-    Note:
-        Dynamic shape: After the graph is running, as the tensor flows in the graph, the specific shape of the tensor
-        on each node on the graph can be inferred according to the structure of the graph.
-        This shape is called a dynamic shape. As the input shape of the graph is different,
-        the dynamic shape of the tensor in the graph will change.
-
-    Inputs:
-        - **input_x** (Tensor) - The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
-
-    Outputs:
-        Tensor[int], 1-dim Tensor of type int32
-
-    Raises:
-        TypeError: If `input_x` is not a Tensor.
-
-    Supported Platforms:
-        ``Ascend`` ``GPU`` ``CPU``
-
-    Examples:
-        >>> input_x = Tensor(np.ones(shape=[3, 2, 1]), mindspore.float32)
-        >>> shape = ops.DynamicShape()
-        >>> output = shape(input_x)
-        >>> print(output)
-        [3 2 1]
+    Same as operator TensorShape. DynamicShape will be deprecated in the future.
+    Please use TensorShape instead.
     """
 
     @deprecated("1.7", "TensorShape", True)