tf.random_uniform(shape, minval=0, maxval=None, dtype=tf.float32, seed=None, 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 Tensor or Python array. The shape of the output tensor. -
minval
: A 0-D Tensor or Python value of typedtype
. The lower bound on the range of random values to generate. Defaults to 0. -
maxval
: A 0-D Tensor or Python value of typedtype
. The upper bound on the range of random values to generate. Defaults to 1 ifdtype
is floating point. -
dtype
: The type of the output:float32
,float64
,int32
, orint64
. -
seed
: A Python integer. Used to create a random seed for the distribution. Seeset_random_seed
for behavior. -
name
: A name for the operation (optional).
Returns:
A tensor of the specified shape filled with random uniform values.
Raises:
-
ValueError
: Ifdtype
is integral andmaxval
is not specified.
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