From 77b783d46995181199ff477c61d506b3d9b01eb6 Mon Sep 17 00:00:00 2001
From: suytingwan <suytingwan@163.com>
Date: Sat, 9 May 2020 12:32:12 +0800
Subject: [PATCH] test=develop add meshgrid cn rst (#2042)

---
 doc/fluid/api_cn/tensor_cn/meshgrid_cn.rst | 55 +++++++++++++++++++++-
 1 file changed, 54 insertions(+), 1 deletion(-)

diff --git a/doc/fluid/api_cn/tensor_cn/meshgrid_cn.rst b/doc/fluid/api_cn/tensor_cn/meshgrid_cn.rst
index 995d0d957..2e5a23cb8 100644
--- a/doc/fluid/api_cn/tensor_cn/meshgrid_cn.rst
+++ b/doc/fluid/api_cn/tensor_cn/meshgrid_cn.rst
@@ -1,3 +1,56 @@
+
+.. _cn_api_paddle_tensor_meshgrid:
+
 meshgrid
 -------------------------------
-**版本升级，文档正在开发中**
+
+.. py:function:: paddle.tensor.meshgrid(input, name=None)
+
+该OP的输入是tensor list, 包含 k 个一维Tensor，对每个Tensor做扩充操作，输出 k 个 k 维tensor。
+
+参数：
+         - **input** （Variable）- 输入变量为 k 个一维Tensor，形状分别为(N1,), (N2,), ..., (Nk, )。支持数据类型为float32，float64，int32，int64。
+         - **name** （str， 可选）- 具体用法请参见 :ref:`api_guide_Name` ，一般无需设置，默认值为None。
+
+返回： 
+k 个 k 维Tensor，每个Tensor的形状均为(N1, N2, ..., Nk)。
+
+返回类型：  变量（Variable）
+
+**代码示例**
+
+..  code-block:: python
+
+    #静态图示例
+    import paddle
+    import paddle.fluid as fluid
+    import numpy as np
+    x = fluid.data(name='x', shape=[100], dtype='int32')
+    y = fluid.data(name='y', shape=[200], dtype='int32')
+    input_1 = np.random.randint(0, 100, [100, ]).astype('int32')
+    input_2 = np.random.randint(0, 100, [200, ]).astype('int32')
+    exe = fluid.Executor(place=fluid.CPUPlace())
+    grid_x, grid_y = paddle.tensor.meshgrid([x, y])
+    res_1, res_2 = exe.run(fluid.default_main_program(),
+                            feed={'x': input_1,
+                                  'y': input_2},
+                            fetch_list=[grid_x, grid_y])
+     
+    #the shape of res_1 is (100, 200)
+    #the shape of res_2 is (100, 200)
+
+
+..  code-block:: python
+
+    #动态图示例
+    import paddle
+    import paddle.fluid as fluid
+    import numpy as np
+    input_3 = np.random.randint(0, 100, [100, ]).astype('int32')
+    input_4 = np.random.randint(0, 100, [200, ]).astype('int32')
+    with fluid.dygraph.guard():
+        tensor_3 = fluid.dygraph.to_variable(input_3)
+        tensor_4 = fluid.dygraph.to_variable(input_4)
+        grid_x, grid_y = paddle.tensor.meshgrid([tensor_3, tensor_4])
+    #the shape of grid_x is (100, 200)
+    #the shape of grid_y is (100, 200)    
-- 
GitLab