Outputs deterministic pseudorandom values from a uniform distribution.

Used in the notebooks

Used in the tutorials

This is a stateless version of tf.random.uniform: if run twice with the same seeds and shapes, it will produce the same pseudorandom numbers. The output is consistent across multiple runs on the same hardware (and between CPU and GPU), but may change between versions of TensorFlow or on non-CPU/GPU hardware.

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).

For full-range (i.e. inclusive of both max and min) random integers, pass minval=None and maxval=None with an integer dtype. For an integer dtype either both minval and maxval must be None or neither may be None. For example:

ints = tf.random.stateless_uniform(
    [10], seed=(2, 3), minval=None, maxval=None, dtype=tf.int32)

shape A 1-D integer Tensor or Python array. The shape of