This creates an n-D kernel suitable for SignalConv* with the requested
support that produces an output identical to its input (except possibly at the
signal boundaries).
Methods
from_config
@classmethodfrom_config(config)
Instantiates an initializer from a configuration dictionary.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tfc.layers.IdentityInitializer\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/compression/blob/v2.14.1/tensorflow_compression/python/layers/initializers.py#L25-L55) |\n\nInitialize to the identity kernel with the given shape.\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tfc.IdentityInitializer`](https://www.tensorflow.org/api_docs/python/tfc/layers/IdentityInitializer)\n\n\u003cbr /\u003e\n\n tfc.layers.IdentityInitializer(\n gain=1\n )\n\nThis creates an n-D kernel suitable for `SignalConv*` with the requested\nsupport that produces an output identical to its input (except possibly at the\nsignal boundaries).\n| **Note:** The identity initializer in [`tf.keras.initializers`](https://www.tensorflow.org/api_docs/python/tf/keras/initializers) is only suitable for matrices, not for n-D convolution kernels (i.e., no spatial support).\n\nMethods\n-------\n\n### `from_config`\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/tensorflow/compression/blob/v2.14.1/tensorflow_compression/python/layers/initializers.py#L52-L55) \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/tensorflow/compression/blob/v2.14.1/tensorflow_compression/python/layers/initializers.py#L40-L50) \n\n __call__(\n shape, dtype=None, **kwargs\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. |\n| `**kwargs` | Additional keyword arguments. |\n\n\u003cbr /\u003e"]]