tf.keras.initializers.RandomUniform
Initializer that generates tensors with a uniform distribution.
Inherits From: random_uniform_initializer
tf.keras.initializers.RandomUniform(
minval=-0.05, maxval=0.05, seed=None, dtype=tf.dtypes.float32
)
Args |
minval | A python scalar or a scalar tensor. Lower bound of the range of random values to generate. Defaults to -0.05. |
maxval | A python scalar or a scalar tensor. Upper bound of the range of random values to generate. Defaults to 0.05. |
seed | A Python integer. Used to create random seeds. See tf.compat.v1.set_random_seed for behavior. |
dtype | The data type. |
Returns |
A RandomUniform instance. |
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=None, partition_info=None
)
Returns a tensor object initialized as specified by the initializer.
Args |
shape | Shape of the tensor. |
dtype | Optional dtype of the tensor. If not provided use the initializer dtype. |
partition_info | Optional information about the possible partitioning of a tensor. |