tf.keras.initializers.Zeros | TensorFlow v2.16.1 (original) (raw)
tf.keras.initializers.Zeros
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Initializer that generates tensors initialized to 0.
Inherits From: Initializer
View aliases
Main aliases
Used in the notebooks
| Used in the tutorials |
|---|
| Scalable model compression |
Examples:
# Standalone usage:
initializer = Zeros()
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = Zeros()
layer = Dense(units=3, kernel_initializer=initializer)
Methods
clone
clone()
from_config
@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
get_config()
Returns the initializer's configuration as a JSON-serializable dict.
| Returns |
|---|
| A JSON-serializable Python dict. |
__call__
__call__(
shape, dtype=None
)
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 default to float32 unless you configured it otherwise (via keras.backend.set_floatx(float_dtype)). |
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Last updated 2024-06-07 UTC.