tf.random.truncated_normal

Outputs random values from a truncated normal distribution.

tf.random.truncated_normal(
    shape,
    mean=0.0,
    stddev=1.0,
    dtype=tf.dtypes.float32,
    seed=None,
    name=None
)

The values are drawn from a normal distribution with specified mean and standard deviation, discarding and re-drawing any samples that are more than two standard deviations from the mean.

Examples:

tf.random.truncated_normal(shape=[2])
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([..., ...], dtype=float32)>
 
tf.random.truncated_normal(shape=[2], mean=3, stddev=1, dtype=tf.float32)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([..., ...], dtype=float32)>

shape A 1-D integer Tensor or Python array. The shape of the output tensor.
mean A 0-D Tensor or Python value of type dtype. The mean of the truncated normal distribution.
stddev A 0-D Tensor or Python value of type dtype. The standard deviation of the normal distribution, before truncation.
dtype The type of the output. Restricted to floating-point types: tf.half, tf.float, tf.double, etc.
seed A Python integer. Used to create a random seed for the distribution. See tf.random.set_seed for more information.
name A name for the operation (optional).

A tensor of the specified shape filled with random truncated normal values.