torchsig.image_datasets.transforms.impairments.RandomGaussianNoiseTransform¶

class torchsig.image_datasets.transforms.impairments.RandomGaussianNoiseTransform(mean: float = 0, range=(0.01, 0.5), **kwargs)[source]¶

Bases: Seedable

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_from_parent`	Update numpy and torch number generators with parent seed

__init__(mean: float = 0, range=(0.01, 0.5), **kwargs)[source]¶

Initializes seedable object with self.seed = seed; if a parent Seedable object is passed in, they will share random number generators, and the seed argument will not be used

Parameters:

seed (int, optional) – Seed for use for number genrators. Defaults to None.
parent (Seedable, optional) – Parent Seedable responsible for seeding this object. Defaults to None.

__call__(image)[source]¶: Call self as a function.

__repr__() → str¶: Return repr(self).

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

Parameters:: seed (int) – Seed to use.
Returns:: New seed.
Return type:: int

seed(seed: int) → None¶

Seed number generators with given seed.

Parameters:: seed (int) – Seed to use.

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

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