def random_uniform(shape,
minval=0,
maxval=None,
dtype=dtypes.float32,
seed=None,
name=None):
return ops.RandomUniform(shape, minval, maxval)
def random_uniform(shape,
minval=0,
maxval=None,
dtype=dtypes.float32,
name=None):
"""
Outputs random values from a uniform distribution.
The generated values follow a uniform distribution in the range
`[minval, maxval)`. The lower bound `minval` is included in the range, while
the upper bound `maxval` is excluded.
For floats, the default range is `[0, 1)`. For ints, at least `maxval` must
be specified explicitly.
In the integer case, the random integers are slightly biased unless
`maxval - minval` is an exact power of two. The bias is small for values of
`maxval - minval` significantly smaller than the range of the output (either
`2**32` or `2**64`).
Args:
shape: A 1-D integer Python array. The shape of the output tensor.
minval: A 0-D Python value of type `dtype`. The lower bound on the
range of random values to generate. Defaults to 0.
maxval: A 0-D Python value of type `dtype`. The upper bound on
the range of random values to generate. Defaults to 1 if `dtype` is floating point.
dtype: The type of the output: `float32`, `float64`, `int32`, or `int64`.
name: A name for the operation (optional).
Returns:
A tensor of the specified shape filled with random uniform values.
"""
return ops.RandomUniform(shape, minval, maxval)
def __call__(self, shape, dtype=None, **kwargs):
if dtype is None: dtype = self.dtype
return _ops.RandomUniform(
shape=shape,
low=self.minval,
high=self.maxval,
dtype=dtype.name,
)
def __call__(self, shape, dtype=None):
if dtype is None: dtype = self.dtype
return ops.RandomUniform(shape, self.minval, self.maxval)