tf.random.normal

TensorFlow 1 version View source on GitHub

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
)

Used in the notebooks

Used in the guide Used in the tutorials

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.

Args:

  • 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 type of the output.
  • 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).

Returns:

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