data-augmentation

Hi there, nice project!

We have recently got Catalyst pipeline with DALI augmentations example. Could you please add it to the docs?

Thanks in advance!

Both the GoalFunctionResult and AttackResult abstract classes should provide a meaningful __str__ method so that they can be printed in a readable way.

Some amount of work for this was done here. Checkout this comment to see what it lacked.

Hi, guys!
I am trying to reuse the OCR transformation module in TextFlint, but I somehow find it rather trivial...
I quote the code about the OCR rules in the source code as below:

mapping = {
            '0': ['8', '9', 'o', 'O', 'D'],
            '1': ['4', '7', 'l', 'I'],
            '2': ['z', 'Z'],
            '5': ['8'],
            '6': ['b'],
            '8': ['s', 'S',

The offset can be randomized, as long as the output has the specified length

Like https://github.com/Spijkervet/torchaudio-augmentations/blob/d044f9d020e12032ab9280acf5f34a337e72d212/torchaudio_augmentations/augmentations/random_resized_crop.py#L5

The idea is that one can have a chain of transforms, and some of them change the input length, but the final length should be fixed. That is where