|  View source on GitHub | 
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, the output of get_config. | 
| Returns | |
|---|---|
| A tf.keras.initializers.Initializerinstance. | 
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 tofloat32unless you configured it otherwise
(viatf.keras.backend.set_floatx(float_dtype)) | 
| **kwargs | Additional keyword arguments. |