torchsig.transforms.base_transforms.Lambda¶

class torchsig.transforms.base_transforms.Lambda(func: Callable, **kwargs)[source]¶

Apply a user-defined lambda as a transform.: Warning: does not automatically update metadata

func¶

Lambda/function to be used for transform.

Example

>>> from torchsig.transforms.base_transforms import Lambda
>>> transform = Lambda(lambda x: x**2)  # A transform that squares all inputs.

Methods

`add_parent`	Add parent Seedable object and set up RNGs accordingly
`get_distribution`
`get_second_seed`	Gets second seed, usually used to seed both torch and numpy generators with slightly different seeds
`seed`	Seed number generators with given seed.
`setup_rngs`	Initialize torch and numpy number generators, and update its children.
`update`	Update bookeeping for signals
`update_from_parent`	Update numpy and torch number generators with parent seed

__init__(func: Callable, **kwargs) → None[source]¶: Transform initialization as Seedable.

Performs transforms

Parameters:: signal (Any) – Signal to be transformed.
Raises:: NotImplementedError – Inherited classes must override this method.
Returns:: Transformed Signal.
Return type:: Any

__repr__() → str¶

Transform string representation. Should be able to recreate class from this string.

add_parent(parent) → None¶: Add parent Seedable object and set up RNGs accordingly

get_second_seed(seed: int) → int¶

Gets second seed, usually used to seed both torch and numpy generators with slightly different seeds

seed(seed: int) → None¶

Seed number generators with given seed.

setup_rngs() → None¶: Initialize torch and numpy number generators, and update its children.

update(signal: Signal | DatasetSignal) → None¶

Update bookeeping for signals

Parameters:: signal (Signal | DatasetSignal) – signal to update metadata.
Raises:: NotImplementedError – Inherited classes must override this method.

update_from_parent() → None¶: Update numpy and torch number generators with parent seed