Outputs deterministic pseudorandom values from a normal distribution.
tf.random.stateless_normal(
shape,
seed,
mean=0.0,
stddev=1.0,
dtype=tf.dtypes.float32
,
name=None,
alg='auto_select'
)
This is a stateless version of tf.random.normal
: 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.
Args |
shape
|
A 1-D integer Tensor or Python array. The shape of the output tensor.
|
seed
|
A shape [2] Tensor, the seed to the random number generator. Must have
dtype int32 or int64 . (When using XLA, only int32 is allowed.)
|
mean
|
A 0-D Tensor or Python value of type dtype . The mean of the normal
distribution.
|
stddev
|
A 0-D Tensor or Python value of type dtype . The standard deviation
of the normal distribution.
|
dtype
|
The type of the output.
|
name
|
A name for the operation (optional).
|
alg
|
The RNG algorithm used to generate the random numbers. See
tf.random.stateless_uniform for a detailed explanation.
|
Returns |
A tensor of the specified shape filled with random normal values.
|