tf.keras.initializers.Identity
Stay organized with collections
Save and categorize content based on your preferences.
Initializer that generates the identity matrix.
Inherits From: Initializer
tf.keras.initializers.Identity(
gain=1.0
)
Only usable for generating 2D matrices.
Examples:
# Standalone usage:
initializer = Identity()
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = Identity()
layer = Dense(3, kernel_initializer=initializer)
Args |
gain
|
Multiplicative factor to apply to the identity matrix.
|
Methods
clone
View source
clone()
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
)
Returns a tensor object initialized as specified by the initializer.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-06-07 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.initializers.Identity\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/initializers/constant_initializers.py#L108-L153) |\n\nInitializer that generates the identity matrix.\n\nInherits From: [`Initializer`](../../../tf/keras/Initializer)\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.initializers.IdentityInitializer`](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/Identity), [`tf.keras.initializers.identity`](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/Identity)\n\n\u003cbr /\u003e\n\n tf.keras.initializers.Identity(\n gain=1.0\n )\n\nOnly usable for generating 2D matrices.\n\n#### Examples:\n\n # Standalone usage:\n initializer = Identity()\n values = initializer(shape=(2, 2))\n\n # Usage in a Keras layer:\n initializer = Identity()\n layer = Dense(3, kernel_initializer=initializer)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|--------------------------------------------------------|\n| `gain` | Multiplicative factor to apply to the identity matrix. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `clone`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/initializers/initializer.py#L83-L84) \n\n clone()\n\n### `from_config`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/initializers/initializer.py#L63-L81) \n\n @classmethod\n from_config(\n config\n )\n\nInstantiates an initializer from a configuration dictionary.\n\n#### Example:\n\n initializer = RandomUniform(-1, 1)\n config = initializer.get_config()\n initializer = RandomUniform.from_config(config)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|----------------------------------------------------|\n| `config` | A Python dictionary, the output of `get_config()`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| An `Initializer` instance. ||\n\n\u003cbr /\u003e\n\n### `get_config`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/initializers/initializer.py#L55-L61) \n\n get_config()\n\nReturns the initializer's configuration as a JSON-serializable dict.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A JSON-serializable Python dict. ||\n\n\u003cbr /\u003e\n\n### `__call__`\n\n[View source](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/initializers/constant_initializers.py#L137-L153) \n\n __call__(\n shape, dtype=None\n )\n\nReturns a tensor object initialized as specified by the initializer.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|---------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `shape` | Shape of the tensor. |\n| `dtype` | Optional dtype of the tensor. Only numeric or boolean dtypes are supported. If not specified, [`keras.backend.floatx()`](../../../tf/keras/backend/floatx) is used, which default to `float32` unless you configured it otherwise (via [`keras.backend.set_floatx(float_dtype)`](../../../tf/keras/backend/set_floatx)). |\n\n\u003cbr /\u003e"]]