tf.keras.initializers.Ones
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Initializer that generates tensors initialized to 1.
Inherits From: Initializer
Also available via the shortcut function ones
.
Examples:
# Standalone usage:
initializer = Ones()
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = Ones()
layer = Dense(3, kernel_initializer=initializer)
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.
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Last updated 2024-06-07 UTC.
[null,null,["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.initializers.Ones\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#L77-L105) |\n\nInitializer that generates tensors initialized to 1.\n\nInherits From: [`Initializer`](../../../tf/keras/Initializer)\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.initializers.ones`](https://www.tensorflow.org/api_docs/python/tf/keras/initializers/Ones)\n\n\u003cbr /\u003e\n\nAlso available via the shortcut function `ones`.\n\n#### Examples:\n\n # Standalone usage:\n initializer = Ones()\n values = initializer(shape=(2, 2))\n\n # Usage in a Keras layer:\n initializer = Ones()\n layer = Dense(3, kernel_initializer=initializer)\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#L94-L105) \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"]]