tf.compat.v2.keras.initializers.RandomNormal

Initializer that generates tensors with a normal distribution.

Inherits From: Initializer

View aliases

Compat aliases for migration

See Migration guide for more details.

`tf.compat.v2.initializers.RandomNormal`, `tf.compat.v2.random_normal_initializer`

tf.compat.v2.keras.initializers.RandomNormal(
    mean=0.0, stddev=0.05, seed=None
)

Args
mean	a python scalar or a scalar tensor. Mean of the random values to generate.
stddev	a python scalar or a scalar tensor. Standard deviation of the random values to generate.
seed	A Python integer. Used to create random seeds. See tf.compat.v1.set_random_seed for behavior.

Methods

from_config

View source

@classmethod
from_config(
    config
)

Instantiates an initializer from a configuration dictionary.

Example:

initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)

Args
config	A Python dictionary. It will typically be the output of get_config.

Returns
An Initializer instance.

get_config

View source

get_config()

Returns the configuration of the initializer as a JSON-serializable dict.

Returns
A JSON-serializable Python dict.

__call__

View source

__call__(
    shape, dtype=tf.dtypes.float32
)

Returns a tensor object initialized as specified by the initializer.

Args
shape	Shape of the tensor.
dtype	Optional dtype of the tensor. Only floating point types are supported.

Raises
ValueError	If the dtype is not floating point