From d8128930efdf74873d518da132d2d82cb78ea185 Mon Sep 17 00:00:00 2001
From: qingqing01 <dangqingqing@baidu.com>
Date: Mon, 25 Feb 2019 15:21:02 +0800
Subject: [PATCH] Refine doc of uniform_random and fix dtype (#15873)

* Refine doc of uniform_random and fix dtype
* Update defaule value in the arguments
---
 paddle/fluid/API.spec             |  2 +-
 python/paddle/fluid/layers/ops.py | 29 ++++++++++++++++++++++-------
 2 files changed, 23 insertions(+), 8 deletions(-)

diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec
index 62c96f8f5..2544b7308 100644
--- a/paddle/fluid/API.spec
+++ b/paddle/fluid/API.spec
@@ -304,7 +304,7 @@ paddle.fluid.layers.reciprocal ArgSpec(args=['x', 'name'], varargs=None, keyword
 paddle.fluid.layers.square ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.softplus ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.softsign ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,))
-paddle.fluid.layers.uniform_random ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=(None, None, None, None))
+paddle.fluid.layers.uniform_random ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', -1.0, 1.0, 0))
 paddle.fluid.layers.hard_shrink ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.layers.cumsum ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None))
 paddle.fluid.layers.thresholded_relu ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,))
diff --git a/python/paddle/fluid/layers/ops.py b/python/paddle/fluid/layers/ops.py
index 6b4dc4ac8..4381727a0 100644
--- a/python/paddle/fluid/layers/ops.py
+++ b/python/paddle/fluid/layers/ops.py
@@ -60,7 +60,28 @@ __all__ += ["uniform_random"]
 _uniform_random_ = generate_layer_fn('uniform_random')
 
 
-def uniform_random(shape, dtype=None, min=None, max=None, seed=None):
+def uniform_random(shape, dtype='float32', min=-1.0, max=1.0, seed=0):
+    """
+    This operator initializes a variable with random values sampled from a
+    uniform distribution. The random result is in set [min, max].
+
+    Args:
+        shape (list): The shape of output variable.
+        dtype(np.dtype|core.VarDesc.VarType|str): The type of data, such as
+            float32, float64 etc. Default: float32.
+        min (float): Minimum value of uniform random. Default -1.0.
+        max (float): Maximun value of uniform random. Default 1.0.
+        seed (int): Random seed used for generating samples. 0 means use a
+            seed generated by the system. Note that if seed is not 0, this
+            operator will always generate the same random numbers every time.
+            Default 0.
+
+    Examples:
+        .. code-block:: python
+
+        result = fluid.layers.uniform_random(shape=[32, 784])
+    """
+
     locals_var = locals().keys()
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
@@ -72,12 +93,6 @@ def uniform_random(shape, dtype=None, min=None, max=None, seed=None):
     return _uniform_random_(**kwargs)
 
 
-uniform_random.__doc__ = _uniform_random_.__doc__ + """
-Examples:
-
-    >>> result = fluid.layers.uniform_random(shape=[32, 784])
-"""
-
 __all__ += ['hard_shrink']
 
 _hard_shrink_ = generate_layer_fn('hard_shrink')
-- 
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