add cn doc of Tensor, test=develop (#1444)

doc/fluid/api_cn/fluid_cn/Tensor_cn.rst

@@ -5,13 +5,101 @@ Tensor
 
 .. py:function:: paddle.fluid.Tensor
 
-    ``LoDTensor`` 的别名
+Tensor用于表示多维张量，可以通过 ``np.array(tensor)`` 方法转换为numpy.ndarray。
 
+**示例代码**
 
+.. code-block:: python
 
+      import paddle.fluid as fluid
 
+      t = fluid.Tensor()
 
+.. py:method::  set(*args, **kwargs)
 
+该接口根据输入的numpy array和设备place，设置Tensor的数据。
 
+重载函数：
 
+1. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[float32], place: paddle::platform::CPUPlace) -> None
 
+2. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int32], place: paddle::platform::CPUPlace) -> None
+
+3. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[float64], place: paddle::platform::CPUPlace) -> None
+
+4. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int64], place: paddle::platform::CPUPlace) -> None
+
+5. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[bool], place: paddle::platform::CPUPlace) -> None
+
+6. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[uint16], place: paddle::platform::CPUPlace) -> None
+
+7. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[uint8], place: paddle::platform::CPUPlace) -> None
+
+8. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int8], place: paddle::platform::CPUPlace) -> None
+
+9. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[float32], place: paddle::platform::CUDAPlace) -> None
+
+10. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int32], place: paddle::platform::CUDAPlace) -> None
+
+11. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[float64], place: paddle::platform::CUDAPlace) -> None
+
+12. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int64], place: paddle::platform::CUDAPlace) -> None
+
+13. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[bool], place: paddle::platform::CUDAPlace) -> None
+
+14. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[uint16], place: paddle::platform::CUDAPlace) -> None
+
+15. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[uint8], place: paddle::platform::CUDAPlace) -> None
+
+16. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int8], place: paddle::platform::CUDAPlace) -> None
+
+17. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[float32], place: paddle::platform::CUDAPinnedPlace) -> None
+
+18. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int32], place: paddle::platform::CUDAPinnedPlace) -> None
+
+19. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[float64], place: paddle::platform::CUDAPinnedPlace) -> None
+
+20. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int64], place: paddle::platform::CUDAPinnedPlace) -> None
+
+21. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[bool], place: paddle::platform::CUDAPinnedPlace) -> None
+
+22. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[uint16], place: paddle::platform::CUDAPinnedPlace) -> None
+
+23. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[uint8], place: paddle::platform::CUDAPinnedPlace) -> None
+
+24. set(self: paddle.fluid.core_avx.Tensor, array: numpy.ndarray[int8], place: paddle::platform::CUDAPinnedPlace) -> None
+
+参数：
+    - **array** (numpy.ndarray) - 要设置的numpy array，支持的数据类型为bool, float32, float64, int8, int32, int64, uint8, uint16。
+    - **place** (CPUPlace|CUDAPlace|CUDAPinnedPlace) - 要设置的Tensor所在的设备。
+
+返回：无。
+
+**示例代码**
+
+.. code-block:: python
+
+            import paddle.fluid as fluid
+            import numpy as np
+
+            t = fluid.Tensor()
+            t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+
+.. py:method::  shape(self: paddle.fluid.core_avx.Tensor) → List[int]
+
+该接口返回Tensor的shape。
+
+返回：Tensor的shape。
+
+返回类型：List[int] 。
+
+**示例代码**
+
+.. code-block:: python
+
+            import paddle.fluid as fluid
+            import numpy as np
+
+            t = fluid.Tensor()
+            t.set(np.ndarray([5, 30]), fluid.CPUPlace())
+            print(t.shape())  # [5, 30]
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