tf.keras.initializers.VarianceScaling

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Initializer capable of adapting its scale to the shape of weights tensors.

Inherits From: Initializer

Used in the notebooks

Used in the tutorials

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

With distribution="truncated_normal" or "untruncated_normal", samples are drawn from a truncated/untruncated normal distribution with a mean of zero and a standard deviation (after truncation, if used) stddev = sqrt(scale / n), where n is:

  • number of input units in the weight tensor, if mode="fan_in"
  • number of output units, if mode="fan_out"
  • average of the numbers of input and output units, if mode="fan_avg"

With distribution="uniform", samples are drawn from a uniform distribution within [-limit, limit], where limit = sqrt(3 * scale / n).

Examples:

# Standalone usage:
initializer = tf.keras.initializers.VarianceScaling(
scale=0.1, mode='fan_in', distribution='uniform')
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = tf.keras.initializers.VarianceScaling(
scale=0.1, mode='fan_in', distribution='uniform')
layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)

scale Scaling factor (positive float).
mode One of "fan_in", "fan_out", "fan_avg".
distribution Random distribution to use. One of "truncated_normal", "untruncated_normal" and "uniform".
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

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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 types are supported. If not specified, tf.keras.backend.floatx() is used, which default to float32 unless you configured it otherwise (via tf.keras.backend.set_floatx(float_dtype))