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 ifdtypeis 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_seedfor behavior. -
name: A name for the operation (optional).
Returns:
A tensor of the specified shape filled with random uniform values.
Raises:
-
ValueError: Ifdtypeis integral andmaxvalis not specified.
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