tf.keras.backend.random_normal_variable

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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)