tf.keras.backend.random_normal_variable(
shape,
mean,
scale,
dtype=None,
name=None,
seed=None
)
Defined in tensorflow/python/keras/backend.py
.
Instantiates a variable with values drawn from a normal distribution.
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:
python
# 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)