tf.keras.initializers.Zeros
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Initializer that generates tensors initialized to 0.
Inherits From: Initializer
Also available via the shortcut function tf.keras.initializers.zeros
.
Examples:
# Standalone usage:
initializer = tf.keras.initializers.Zeros()
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = tf.keras.initializers.Zeros()
layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)
Methods
from_config
View source
@classmethod
from_config(
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, the output of get_config() .
|
Returns |
An Initializer instance.
|
get_config
View source
get_config()
Returns the initializer's configuration as a JSON-serializable dict.
Returns |
A JSON-serializable Python dict.
|
__call__
View source
__call__(
shape, dtype=None, **kwargs
)
Returns a tensor object initialized as specified by the initializer.
Args |
shape
|
Shape of the tensor.
|
dtype
|
Optional dtype of the tensor. Only numeric or boolean dtypes
are supported. If not specified, keras.backend.floatx() is
used, which defaults to float32 unless you configured it
otherwise (via keras.backend.set_floatx(float_dtype) ).
|
**kwargs
|
Additional keyword arguments.
|
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Last updated 2024-01-23 UTC.
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