tf.random_uniform_initializer

TensorFlow 2 version View source on GitHub

Initializer that generates tensors with a uniform distribution.

Inherits From: Initializer

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.
dtype Default data type, used if no dtype argument is provided when calling the initializer.

Methods

from_config

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

Returns
A JSON-serializable Python dict.

__call__

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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.