tfl.lattice_layer.RandomMonotonicInitializer
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Initializes a tfl.layers.Lattice as uniform random monotonic function.
tfl.lattice_layer.RandomMonotonicInitializer(
lattice_sizes, output_min, output_max, unimodalities=None
)
- The uniform random monotonic function will initilaize the lattice parameters
uniformly at random and make it such that the parameters are monotonically
increasing for each input.
- The random parameters will be sampled from
[output_min, output_max]
Args |
|---|
lattice_sizes
|
Lattice sizes of tfl.layers.Lattice to initialize.
|
output_min
|
Minimum layer output after initialization.
|
output_max
|
Maximum layer output after initialization.
|
unimodalities
|
None or unimodal dimensions after initialization. Does not
need to match unimodalities of tfl.layers.Lattice.
|
Raises |
|---|
ValueError
|
If there are invalid hyperparameters.
|
Methods
from_config
@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()
Standard Keras config for serialization.
__call__
View source
__call__(
shape, dtype=None, partition_info=None
)
Returns weights of tfl.layers.Lattice layer.
| Args |
|---|
shape
|
Must be: (prod(lattice_sizes), units).
|
dtype
|
Standard Keras initializer param.
|
partition_info
|
Standard Keras initializer param. Not used.
|
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Last updated 2024-08-02 UTC.
[null,null,["Last updated 2024-08-02 UTC."],[],[],null,["# tfl.lattice_layer.RandomMonotonicInitializer\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/lattice/blob/v2.1.1/tensorflow_lattice/python/lattice_layer.py#L740-L802) |\n\nInitializes a [`tfl.layers.Lattice`](../../tfl/layers/Lattice) as uniform random monotonic function. \n\n tfl.lattice_layer.RandomMonotonicInitializer(\n lattice_sizes, output_min, output_max, unimodalities=None\n )\n\n- The uniform random monotonic function will initilaize the lattice parameters uniformly at random and make it such that the parameters are monotonically increasing for each input.\n- The random parameters will be sampled from `[output_min, output_max]`\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------|\n| `lattice_sizes` | Lattice sizes of [`tfl.layers.Lattice`](../../tfl/layers/Lattice) to initialize. |\n| `output_min` | Minimum layer output after initialization. |\n| `output_max` | Maximum layer output after initialization. |\n| `unimodalities` | None or unimodal dimensions after initialization. Does not need to match `unimodalities` of [`tfl.layers.Lattice`](../../tfl/layers/Lattice). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|---------------------------------------|\n| `ValueError` | If there are invalid hyperparameters. |\n\n\u003cbr /\u003e\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/lattice/blob/v2.1.1/tensorflow_lattice/python/lattice_layer.py#L794-L802) \n\n get_config()\n\nStandard Keras config for serialization.\n\n### `__call__`\n\n[View source](https://github.com/tensorflow/lattice/blob/v2.1.1/tensorflow_lattice/python/lattice_layer.py#L778-L792) \n\n __call__(\n shape, dtype=None, partition_info=None\n )\n\nReturns weights of [`tfl.layers.Lattice`](../../tfl/layers/Lattice) layer.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|------------------|---------------------------------------------|\n| `shape` | Must be: `(prod(lattice_sizes), units)`. |\n| `dtype` | Standard Keras initializer param. |\n| `partition_info` | Standard Keras initializer param. Not used. |\n\n\u003cbr /\u003e"]]
View source on GitHub