View source on GitHub
|
Outputs deterministic pseudorandom values from a uniform distribution.
tf.random.stateless_uniform(
shape,
seed,
minval=0,
maxval=None,
dtype=tf.dtypes.float32,
name=None,
alg='auto_select'
)
| Used in the tutorials |
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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
seed
int32 or int64. (When using XLA, only int32 is allowed.)
minval
dtype, broadcastable with shape
(for integer types, broadcasting is not supported, so it needs to be a
scalar). The lower bound on the range of random values to generate. Pass
None for full-range integers. Defaults to 0.
maxval
dtype, broadcastable with shape
(for integer types, broadcasting is not supported, so it needs to be a
scalar). The upper bound on the range of random values to generate.
Defaults to 1 if dtype is floating point. Pass None for full-range
integers.
dtype
float16, bfloat16, float32, float64,
int32, or int64. For unbounded uniform ints (minval, maxval both
None), uint32 and uint64 may be used. Defaults to float32.
name
alg
"philox" for the Philox
algorithm,
"threefry" for the ThreeFry
algorithm,
and "auto_select" (default) for the system to automatically select an
algorithm based the device type. Values of tf.random.Algorithm can also
be used. Note that with "auto_select", the outputs of this function may
change when it is running on a different device.
ValueError
dtype is integral and only one of minval or maxval is
specified.
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Last updated 2024-04-26 UTC.