refind rand, randn, standard_normal, normal, randint, randperm docs (#2528)

* refind rand, randn, standard_normal, normal, randint, randperm docs

test=develop

* test=develop

doc/paddle/api/paddle/tensor/random/normal_cn.rst

+.. _cn_api_tensor_random_normal:
+
+normal
+-------------------------------
+
+.. py:function:: paddle.normal(mean=0.0, std=1.0, shape=None, name=None)
+
+
+该OP返回符合正态分布（均值为 ``mean`` ，标准差为 ``std`` 的正态随机分布）的随机Tensor。
+
+如果 ``mean`` 是Tensor，则输出Tensor和 ``mean`` 具有相同的形状和数据类型。
+如果 ``mean`` 不是Tensor，且 ``std`` 是Tensor，则输出Tensor和 ``std`` 具有相同的形状和数据类型。
+如果 ``mean`` 和 ``std`` 都不是Tensor，则输出Tensor的形状为 ``shape``，数据类型为float32。
+
+如果 ``mean`` 和 ``std`` 都是Tensor，则 ``mean`` 和 ``std`` 的元素个数应该相同。
+
+参数
+::::::::::
+    - mean (float|Tensor, 可选) - 输出Tensor的正态分布的平均值。如果 ``mean`` 是float，则表示输出Tensor中所有元素的正态分布的平均值。如果 ``mean`` 是Tensor(支持的数据类型为float32、float64)，则表示输出Tensor中每个元素的正态分布的平均值。默认值为0.0
+    - std (float|Tensor, 可选) - 输出Tensor的正态分布的标准差。如果 ``std`` 是float，则表示输出Tensor中所有元素的正态分布的标准差。如果 ``std`` 是Tensor(支持的数据类型为float32、float64)，则表示输出Tensor中每个元素的正态分布的标准差。默认值为0.0
+    - shape (list|tuple|Tensor, 可选) - 生成的随机Tensor的形状。如果 ``shape`` 是list、tuple，则其中的元素可以是int，或者是形状为[1]且数据类型为int32、int64的Tensor。如果 ``shape`` 是Tensor，则是数据类型为int32、int64的1-D Tensor。如果 ``mean`` 或者 ``std`` 是Tensor，输出Tensor的形状和 ``mean`` 或者 ``std`` 相同(此时 ``shape`` 无效)。默认值为None。
+    - name (str, 可选) - 操作的名称(可选，默认值为None）。更多信息请参见 :ref:`api_guide_Name`。
+
+返回
+::::::::::
+  Tensor：符合正态分布（均值为 ``mean`` ，标准差为 ``std`` 的正态随机分布）的随机Tensor。
+
+示例代码
+::::::::::
+
+.. code-block:: python
+
+    import paddle
+    import numpy as np
+
+    paddle.disable_static()
+
+    out1 = paddle.normal(shape=[2, 3])
+    # [[ 0.17501129  0.32364586  1.561118  ]  # random
+    #  [-1.7232178   1.1545963  -0.76156676]]  # random
+
+    mean_tensor = paddle.to_tensor(np.array([1.0, 2.0, 3.0]))
+    out2 = paddle.normal(mean=mean_tensor)
+    # [ 0.18644847 -1.19434458  3.93694787]  # random
+
+    std_tensor = paddle.to_tensor(np.array([1.0, 2.0, 3.0]))
+    out3 = paddle.normal(mean=mean_tensor, std=std_tensor)
+    # [1.00780561 3.78457445 5.81058198]  # random

doc/paddle/api/paddle/tensor/random/rand_cn.rst

@@ -5,11 +5,6 @@ rand
 
 .. py:function:: paddle.rand(shape, dtype=None, name=None)
 
-:alias_main: paddle.rand
-:alias: paddle.tensor.rand, paddle.tensor.random.rand
-
-
-
 该OP返回符合均匀分布的，范围在[0, 1)的Tensor，形状为 ``shape``，数据类型为 ``dtype``。
 
 参数
@@ -22,11 +17,6 @@ rand
 ::::::::::
     Tensor: 符合均匀分布的范围为[0, 1)的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。
 
-抛出异常
-::::::::::
-    - ``TypeError`` - 如果 ``shape`` 的类型不是list、tuple、Tensor。
-    - ``TypeError`` - 如果 ``dtype`` 不是float32、float64。
-
 示例代码
 ::::::::::
 
@@ -35,25 +25,25 @@ rand
     import paddle
     import numpy as np
 
-    paddle.enable_imperative()
+    paddle.disable_static()
     # example 1: attr shape is a list which doesn't contain Tensor.
-    result_1 = paddle.rand(shape=[2, 3])
-    # [[0.451152  , 0.55825245, 0.403311  ],
-    #  [0.22550228, 0.22106001, 0.7877319 ]]
+    out1 = paddle.rand(shape=[2, 3])
+    # [[0.451152  , 0.55825245, 0.403311  ],  # random
+    #  [0.22550228, 0.22106001, 0.7877319 ]]  # random
 
     # example 2: attr shape is a list which contains Tensor.
-    dim_1 = paddle.fill_constant([1], "int64", 2)
-    dim_2 = paddle.fill_constant([1], "int32", 3)
-    result_2 = paddle.rand(shape=[dim_1, dim_2, 2])
-    # [[[0.8879919  0.25788337]
-    #   [0.28826773 0.9712097 ]
-    #   [0.26438272 0.01796806]]
-    #  [[0.33633623 0.28654453]
-    #   [0.79109055 0.7305809 ]
-    #   [0.870881   0.2984597 ]]]
+    dim1 = paddle.full([1], 2, "int64")
+    dim2 = paddle.full([1], 3, "int32")
+    out2 = paddle.rand(shape=[dim1, dim2, 2])
+    # [[[0.8879919 , 0.25788337],  # random
+    #   [0.28826773, 0.9712097 ],  # random
+    #   [0.26438272, 0.01796806]],  # random
+    #  [[0.33633623, 0.28654453],  # random
+    #   [0.79109055, 0.7305809 ],  # random
+    #   [0.870881  , 0.2984597 ]]]  # random
 
     # example 3: attr shape is a Tensor, the data type must be int64 or int32.
-    var_shape = paddle.imperative.to_variable(np.array([2, 3]))
-    result_3 = paddle.rand(var_shape)
-    # [[0.22920267 0.841956   0.05981819]
-    #  [0.4836288  0.24573246 0.7516129 ]]
+    shape_tensor = paddle.to_tensor(np.array([2, 3]))
+    out2 = paddle.rand(shape_tensor)
+    # [[0.22920267, 0.841956  , 0.05981819],  # random
+    #  [0.4836288 , 0.24573246, 0.7516129 ]]  # random

doc/paddle/api/paddle/tensor/random/randint_cn.rst

-.. _cn_api_tensor_randint:
+.. _cn_api_tensor_random_randint:
 
 randint
 -------------------------------
 
 .. py:function:: paddle.randint(low=0, high=None, shape=[1], dtype=None, name=None)
 
-:alias_main: paddle.randint
-:alias: paddle.tensor.randint, paddle.tensor.random.randint
-
-
-
 该OP返回服从均匀分布的、范围在[``low``, ``high``)的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。当 ``high`` 为None时（默认），均匀采样的区间为[0, ``low``)。
 
 参数
@@ -24,12 +19,6 @@ randint
 ::::::::::
     Tensor：从区间[``low``，``high``)内均匀分布采样的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。
 
-抛出异常
-::::::::::
-    - ``TypeError`` - 如果 ``shape`` 的类型不是list、tuple、Tensor。
-    - ``TypeError`` - 如果 ``dtype`` 不是int32、int64。
-    - ``ValueError`` - 如果 ``high`` 不大于 ``low``；或者 ``high`` 为None，且 ``low`` 不大于0。
-
 代码示例
 :::::::::::
 
@@ -38,35 +27,34 @@ randint
     import paddle
     import numpy as np
 
-    paddle.enable_imperative()
+    paddle.disable_static()
 
     # example 1:
     # attr shape is a list which doesn't contain Tensor.
-    result_1 = paddle.randint(low=-5, high=5, shape=[3])
-    # [0, -3, 2]
+    out1 = paddle.randint(low=-5, high=5, shape=[3])
+    # [0, -3, 2]  # random
 
     # example 2:
     # attr shape is a list which contains Tensor.
-    dim_1 = paddle.fill_constant([1], "int64", 2)
-    dim_2 = paddle.fill_constant([1], "int32", 3)
-    result_2 = paddle.randint(low=-5, high=5, shape=[dim_1, dim_2], dtype="int32")
-    print(result_2.numpy())
-    # [[ 0, -1, -3],
-    #  [ 4, -2,  0]]
+    dim1 = paddle.full([1], 2, "int64")
+    dim2 = paddle.full([1], 3, "int32")
+    out2 = paddle.randint(low=-5, high=5, shape=[dim1, dim2], dtype="int32")
+    # [[0, -1, -3],  # random
+    #  [4, -2,  0]]  # random
 
     # example 3:
     # attr shape is a Tensor
-    var_shape = paddle.imperative.to_variable(np.array([3]))
-    result_3 = paddle.randint(low=-5, high=5, shape=var_shape)
-    # [-2, 2, 3]
+    shape_tensor = paddle.to_tensor(np.array([3]))
+    out3 = paddle.randint(low=-5, high=5, shape=shape_tensor)
+    # [-2, 2, 3]  # random
 
     # example 4:
-    # date type is int32
-    result_4 = paddle.randint(low=-5, high=5, shape=[3], dtype='int32')
-    # [-5, 4, -4]
+    # data type is int32
+    out4 = paddle.randint(low=-5, high=5, shape=[3], dtype='int32')
+    # [-5, 4, -4]  # random
 
     # example 5:
     # Input only one parameter
     # low=0, high=10, shape=[1], dtype='int64'
-    result_5 = paddle.randint(10)
-    # [7]
+    out5 = paddle.randint(10)
+    # [7]  # random

doc/paddle/api/paddle/tensor/random/randn_cn.rst

@@ -5,11 +5,6 @@ randn
 
 .. py:function:: paddle.randn(shape, dtype=None, name=None)
 
-:alias_main: paddle.randn
-:alias: paddle.tensor.randn, paddle.tensor.random.randn
-
-
-
 该OP返回符合标准正态分布（均值为0，标准差为1的正态随机分布）的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。
 
 参数
@@ -22,11 +17,6 @@ randn
 ::::::::::
   Tensor：符合标准正态分布的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。
 
-抛出异常
-::::::::::
-  - ``TypeError`` - 如果 ``shape`` 的类型不是list、tuple、Tensor。
-  - ``TypeError`` - 如果 ``dtype`` 不是float32、float64。
-
 示例代码
 ::::::::::
 
@@ -35,26 +25,26 @@ randn
     import paddle
     import numpy as np
 
-    paddle.enable_imperative()
+    paddle.disable_static()
 
     # example 1: attr shape is a list which doesn't contain Tensor.
-    result_1 = paddle.randn(shape=[2, 3])
-    # [[-2.923464    0.11934398 -0.51249987]
-    #  [ 0.39632758  0.08177969  0.2692008 ]]
+    out1 = paddle.randn(shape=[2, 3])
+    # [[-2.923464  ,  0.11934398, -0.51249987],  # random
+    #  [ 0.39632758,  0.08177969,  0.2692008 ]]  # random
 
     # example 2: attr shape is a list which contains Tensor.
-    dim_1 = paddle.fill_constant([1], "int64", 2)
-    dim_2 = paddle.fill_constant([1], "int32", 3)
-    result_2 = paddle.randn(shape=[dim_1, dim_2, 2])
-    # [[[-2.8852394  -0.25898588]
-    #   [-0.47420555  0.17683524]
-    #   [-0.7989969   0.00754541]]
-    #  [[ 0.85201347  0.32320443]
-    #   [ 1.1399018   0.48336947]
-    #   [ 0.8086993   0.6868893 ]]]
+    dim1 = paddle.full([1], 2, "int64")
+    dim2 = paddle.full([1], 3, "int32")
+    out2 = paddle.randn(shape=[dim1, dim2, 2])
+    # [[[-2.8852394 , -0.25898588],  # random
+    #   [-0.47420555,  0.17683524],  # random
+    #   [-0.7989969 ,  0.00754541]],  # random
+    #  [[ 0.85201347,  0.32320443],  # random
+    #   [ 1.1399018 ,  0.48336947],  # random
+    #   [ 0.8086993 ,  0.6868893 ]]]  # random
 
     # example 3: attr shape is a Tensor, the data type must be int64 or int32.
-    var_shape = paddle.imperative.to_variable(np.array([2, 3]))
-    result_3 = paddle.randn(var_shape)
-    # [[-2.878077    0.17099959  0.05111201]
-    #  [-0.3761474  -1.044801    1.1870178 ]]
+    shape_tensor = paddle.to_tensor(np.array([2, 3]))
+    out3 = paddle.randn(shape_tensor)
+    # [[-2.878077 ,  0.17099959,  0.05111201]  # random
+    #  [-0.3761474, -1.044801  ,  1.1870178 ]]  # random

doc/paddle/api/paddle/tensor/random/randperm_cn.rst

@@ -5,9 +5,6 @@ randperm
 
 .. py:function:: paddle.randperm(n, dtype="int64", name=None)
 
-:alias_main: paddle.randperm
-:alias: paddle.tensor.randperm, paddle.tensor.random.randperm
-
 该OP返回一个数值在0到n-1、随机排列的1-D Tensor，数据类型为 ``dtype``。
 
 参数:
@@ -20,22 +17,17 @@ randperm
 ::::::::::
   Tensor：一个数值在0到n-1、随机排列的1-D Tensor，数据类型为 ``dtype`` 。
 
-抛出异常
-::::::::::
-  - ValueError - 如果 ``n`` 不大于0.
-  - TypeError - 如果 ``dtype`` 不是int32、int64、float32、float64.
-
 代码示例
 ::::::::::
 
-..  code-block:: python
+.. code-block:: python
 
     import paddle
 
-    paddle.enable_imperative()
+    paddle.disable_static()
 
-    result_1 = paddle.randperm(5)
-    # [4 1 2 3 0]
+    out1 = paddle.randperm(5)
+    # [4, 1, 2, 3, 0]  # random
 
-    result_2 = paddle.randperm(7, 'int32')
-    # [1 6 2 0 4 3 5]   
+    out2 = paddle.randperm(7, 'int32')
+    # [1, 6, 2, 0, 4, 3, 5]  # random

doc/paddle/api/paddle/tensor/random/standard_normal_cn.rst

+.. _cn_api_tensor_random_standard_normal:
+
+standard_normal
+-------------------------------
+
+.. py:function:: paddle.standard_normal(shape, dtype=None, name=None)
+
+该OP返回符合标准正态分布（均值为0，标准差为1的正态随机分布）的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。
+
+参数
+::::::::::
+  - **shape** (list|tuple|Tensor) - 生成的随机Tensor的形状。如果 ``shape`` 是list、tuple，则其中的元素可以是int，或者是形状为[1]且数据类型为int32、int64的Tensor。如果 ``shape`` 是Tensor，则是数据类型为int32、int64的1-D Tensor。
+  - **dtype** (str|np.dtype|core.VarDesc.VarType, 可选) - 输出Tensor的数据类型，支持float32、float64。当该参数值为None时， 输出Tensor的数据类型为float32。默认值为None.
+  - **name** (str, 可选) - 输出的名字。一般无需设置，默认值为None。该参数供开发人员打印调试信息时使用，具体用法请参见 :ref:`api_guide_Name` 。
+
+返回
+::::::::::
+  Tensor：符合标准正态分布的随机Tensor，形状为 ``shape``，数据类型为 ``dtype``。
+
+示例代码
+::::::::::
+
+.. code-block:: python
+
+    import paddle
+    import numpy as np
+
+    paddle.disable_static()
+
+    # example 1: attr shape is a list which doesn't contain Tensor.
+    out1 = paddle.standard_normal(shape=[2, 3])
+    # [[-2.923464  ,  0.11934398, -0.51249987],  # random
+    #  [ 0.39632758,  0.08177969,  0.2692008 ]]  # random
+
+    # example 2: attr shape is a list which contains Tensor.
+    dim1 = paddle.full([1], 2, "int64")
+    dim2 = paddle.full([1], 3, "int32")
+    out2 = paddle.standard_normal(shape=[dim1, dim2, 2])
+    # [[[-2.8852394 , -0.25898588],  # random
+    #   [-0.47420555,  0.17683524],  # random
+    #   [-0.7989969 ,  0.00754541]],  # random
+    #  [[ 0.85201347,  0.32320443],  # random
+    #   [ 1.1399018 ,  0.48336947],  # random
+    #   [ 0.8086993 ,  0.6868893 ]]]  # random
+
+    # example 3: attr shape is a Tensor, the data type must be int64 or int32.
+    shape_tensor = paddle.to_tensor(np.array([2, 3]))
+    out3 = paddle.standard_normal(shape_tensor)
+    # [[-2.878077 ,  0.17099959,  0.05111201]  # random
+    #  [-0.3761474, -1.044801  ,  1.1870178 ]]  # random