tf.keras.backend.random_normal_variable

TensorFlow 1 version View source on GitHub

Instantiates a variable with values drawn from a normal distribution.

Aliases: tf.compat.v1.keras.backend.random_normal_variable, tf.compat.v2.keras.backend.random_normal_variable

tf.keras.backend.random_normal_variable(
    shape,
    mean,
    scale,
    dtype=None,
    name=None,
    seed=None
)

Arguments:

  • shape: Tuple of integers, shape of returned Keras variable.
  • mean: Float, mean of the normal distribution.
  • scale: Float, standard deviation of the normal distribution.
  • dtype: String, dtype of returned Keras variable.
  • name: String, name of returned Keras variable.
  • seed: Integer, random seed.

Returns:

A Keras variable, filled with drawn samples.

Example:

    # TensorFlow example
    >>> kvar = K.random_normal_variable((2,3), 0, 1)
    >>> kvar
    <tensorflow.python.ops.variables.Variable object at 0x10ab12dd0>
    >>> K.eval(kvar)
    array([[ 1.19591331,  0.68685907, -0.63814116],
           [ 0.92629528,  0.28055015,  1.70484698]], dtype=float32)