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tf.compat.v2.keras.initializers.RandomUniform

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Class RandomUniform

Initializer that generates tensors with a uniform distribution.

Inherits From: Initializer

Aliases:

  • Class tf.compat.v2.initializers.RandomUniform
  • Class tf.compat.v2.random_uniform_initializer

Args:

  • minval: A python scalar or a scalar tensor. Lower bound of the range of random values to generate.
  • maxval: A python scalar or a scalar tensor. Upper bound of the range of random values to generate. Defaults to 1 for float types.
  • seed: A Python integer. Used to create random seeds. See tf.compat.v1.set_random_seed for behavior.

__init__

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__init__(
    minval=-0.05,
    maxval=0.05,
    seed=None
)

Methods

__call__

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__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 and integer types are supported.

Raises:

  • ValueError: If the dtype is not numeric.

from_config

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from_config(
    cls,
    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

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get_config()