Instantiates a variable with values drawn from a normal distribution.
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)