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|
Initializer that generates the identity matrix.
Inherits From: Initializer
tf.keras.initializers.Identity(
gain=1.0
)
Also available via the shortcut function tf.keras.initializers.identity.
Only usable for generating 2D matrices.
Examples:
# Standalone usage:initializer = tf.keras.initializers.Identity()values = initializer(shape=(2, 2))
# Usage in a Keras layer:initializer = tf.keras.initializers.Identity()layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)
Args | |
|---|---|
gain
|
Multiplicative factor to apply to the identity matrix. |
Methods
from_config
@classmethodfrom_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.
It will typically be the output of get_config.
|
| Returns | |
|---|---|
| An Initializer instance. |
get_config
get_config()
Returns the configuration of the initializer as a JSON-serializable dict.
| Returns | |
|---|---|
| A JSON-serializable Python dict. |
__call__
__call__(
shape, dtype=None, **kwargs
)
Returns a tensor object initialized to a 2D identity matrix.
| Args | |
|---|---|
shape
|
Shape of the tensor. It should have exactly rank 2. |
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))
|
**kwargs
|
Additional keyword arguments. |