tf.random.stateless_parameterized_truncated_normal

Outputs random values from a truncated normal distribution.

The generated values follow a normal distribution with specified mean and standard deviation, except that values whose magnitude is more than 2 standard deviations from the mean are dropped and re-picked.

Examples:

Sample from a Truncated normal, with deferring shape parameters that broadcast.

means = 0.
stddevs = tf.math.exp(tf.random.uniform(shape=[2, 3]))
minvals = [-1., -2., -1000.]
maxvals = [[10000.], [1.]]
y = tf.random.stateless_parameterized_truncated_normal(
  shape=[10, 2, 3], seed=[7, 17],
  means=means, stddevs=stddevs, minvals=minvals, maxvals=maxvals)
y.shape
TensorShape([10, 2, 3])

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