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add uniform op doc (#2439)
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* add uniform op doc

* fix uniform en format

* delete useless code
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pangyoki authored Aug 22, 2020
1 parent 08e429c commit 83d775f
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1 change: 1 addition & 0 deletions doc/fluid/api/tensor/random.rst
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random/randint.rst
random/randn.rst
random/randperm.rst
random/uniform.rst
10 changes: 10 additions & 0 deletions doc/fluid/api/tensor/random/uniform.rst
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.. THIS FILE IS GENERATED BY `gen_doc.{py|sh}`
!DO NOT EDIT THIS FILE MANUALLY!
.. _api_tensor_random_uniform:

uniform
-------

.. autofunction:: paddle.tensor.random.uniform
:noindex:
1 change: 1 addition & 0 deletions doc/fluid/api_cn/tensor_cn.rst
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tensor_cn/tril_cn.rst
tensor_cn/triu_cn.rst
tensor_cn/unbind_cn.rst
tensor_cn/uniform_cn.rst
tensor_cn/unique_cn.rst
tensor_cn/unique_with_counts_cn.rst
tensor_cn/unsqueeze_cn.rst
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77 changes: 77 additions & 0 deletions doc/fluid/api_cn/tensor_cn/uniform_cn.rst
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.. _cn_api_tensor_uniform:

uniform
-------------------------------

.. py:function:: paddle.uniform(shape, dtype='float32', min=-1.0, max=1.0, seed=0, name=None)
该OP返回数值服从范围[``min``, ``max``)内均匀分布的随机Tensor,形状为 ``shape``,数据类型为 ``dtype``。

::

示例1:
给定:
shape=[1,2]
则输出为:
result=[[0.8505902, 0.8397286]]

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, 可选) - 输出Tensor的数据类型,支持float32、float64。默认值为float32。
- **min** (float|int,可选) - 要生成的随机值范围的下限,min包含在范围中。支持的数据类型:float、int。默认值为-1.0。
- **max** (float|int,可选) - 要生成的随机值范围的上限,max不包含在范围中。支持的数据类型:float、int。默认值为1.0。
- **seed** (int,可选) - 随机种子,用于生成样本。0表示使用系统生成的种子。注意如果种子不为0,该操作符每次都生成同样的随机数。支持的数据类型:int。默认为 0。
- **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:数值服从范围[``min``, ``max``)内均匀分布的随机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。

**代码示例**:

.. code-block:: python
import numpy as np
import paddle
paddle.disable_static()
# example 1:
# attr shape is a list which doesn't contain Tensor.
result_1 = paddle.uniform(shape=[3, 4])
# [[ 0.84524226, 0.6921872, 0.56528175, 0.71690357],
# [-0.34646994, -0.45116323, -0.09902662, -0.11397249],
# [ 0.433519, 0.39483607, -0.8660099, 0.83664286]]
# 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.uniform(shape=[dim_1, dim_2])
# [[-0.9951253, 0.30757582, 0.9899647 ],
# [ 0.5864527, 0.6607096, -0.8886161 ]]
# example 3:
# attr shape is a Tensor, the data type must be int64 or int32.
shape = np.array([2, 3])
shape_tensor = paddle.to_tensor(shape)
result_3 = paddle.uniform(shape_tensor)
# if shape_tensor's value is [2, 3]
# result_3 is:
# [[-0.8517412, -0.4006908, 0.2551912 ],
# [ 0.3364414, 0.36278176, -0.16085452]]

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