tf.random.normal

Outputs random values from a normal distribution.

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

Example that generates a new set of random values every time:

tf.random.set_seed(5);
tf.random.normal([4], 0, 1, tf.float32)
<tf.Tensor: shape=(4,), dtype=float32, numpy=..., dtype=float32)>

Example that outputs a reproducible result:

tf.random.set_seed(5);
tf.random.normal([2,2], 0, 1, tf.float32, seed=1)
<tf.Tensor: shape=(2, 2), dtype=float32, numpy=
array([[-1.3768897 , -0.01258316],
      [-0.169515   ,  1.0824056 ]], dtype=float32)>

In this case, we are setting both the global and operation-level seed to ensure this result is reproducible. See tf.random.set_seed for more information.

shape A 1-D integer Tensor or Python array. The shape of the output tensor.
mean A Tensor or Python value of type dtype, broadcastable with stddev. The mean of the normal distribution.
stddev A Tensor or Python value of type dtype, broadcastable with mean. The standard deviation of the normal distribution.
dtype The float type of the output: float16, bfloat16, float32, float64. Defaults to float32.
seed A Python integer. Used to create a random seed for the distribution. See tf.random.set_seed for behavior.
name A name for the operation (optional).

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