ML Community Day is November 9! Join us for updates from TensorFlow, JAX, and more Learn more

tf.keras.initializers.RandomUniform

Initializer that generates tensors with a uniform distribution.

Inherits From: Initializer

Used in the notebooks

Used in the tutorials

Also available via the shortcut function tf.keras.initializers.random_uniform.

Examples:

# Standalone usage:
initializer = tf.keras.initializers.RandomUniform(minval=0., maxval=1.)
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = tf.keras.initializers.RandomUniform(minval=0., maxval=1.)
layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)

minval A python scalar or a scalar tensor. Lower bound of the range of random values to generate (inclusive).
maxval A python scalar or a scalar tensor. Upper bound of the range of random values to generate (exclusive).
seed A Python integer. An initializer created with a given seed will always produce the same random tensor for a given shape and dtype.

Methods

from_config

View source

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, the output of get_config.

Returns
A tf.keras.initializers.Initializer instance.

get_config

View source

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

Returns
A JSON-serializable Python dict.

__call__

View source

Returns a tensor object initialized as specified by the initializer.

Args
shape Shape of the tensor.