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tf.compat.v2.keras.initializers.RandomUniform

Initializer that generates tensors with a uniform distribution.

Inherits From: 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.

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. Only floating point and integer types are supported.
Raises
ValueError If the dtype is not numeric.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/compat/v2/keras/initializers/RandomUniform