ValueError: high is out of bounds for int64 (word_swap_change_number._alter_number)

[fabriceyhc]

Describe the bug When using textattack.augmentation.recipes.CheckListAugmenter on the yahoo_answers_topics dataset in Huggingface, I get an error:

...
  File "~\textattack\transformations\word_swaps\word_swap_change_number.py", line 108, in _alter_number
    num_list = np.random.randint(max(num - change, 1), num + change, self.n, dtype=np.int64)
  File "mtrand.pyx", line 765, in numpy.random.mtrand.RandomState.randint
  File "_bounded_integers.pyx", line 1245, in numpy.random._bounded_integers._rand_int64
ValueError: high is out of bounds for int64

Whatever number is being found in the text is too large for np.int32. A partial workaround that solved the problem in ag_news was to change change the dtype=np.int64, but its still happening now for yahoo_answers_topics.

To Reproduce

class AugMapper:
    def __init__(self, augmenter):
        self.augmenter = augmenter # textattack augmenter recipe

    def apply_to_batch(self, batch):
        new_texts, new_labels = [], []
        for text, label in zip(batch['text'], batch['label']):
            augmented_text = self.augmenter.augment(text)
            new_texts.extend(augmented_text)
            new_labels.extend([label] * len(augmented_text))

        return {
            "text": new_texts,
            "label": new_labels,
            "idx": list(range(len(new_labels))),
        }

if __name__ == "__main__":
    import os
    import glob
    from datasets import load_dataset, load_from_disk
    from textattack.augmentation.recipes import (
        EasyDataAugmenter,
        CheckListAugmenter,
    )

    # checklist
    checklist_augmenter = CheckListAugmenter(
        transformations_per_example=3
    )
    checklist_aug_mapper = AugMapper(checklist_augmenter)

    dataset_paths = ["yahoo_answers_topics"]

    for dataset_path in dataset_paths:
        print(dataset_path)
        dataset = load_dataset(dataset_path, split="train")
        # augment + save checklist
        checklist_dataset = dataset.map(checklist_aug_mapper.apply_to_batch, batched=True, batch_size=10)
            

Expected behavior The augmentation should not error out

Screenshots or Traceback If applicable, add screenshots to help explain your problem. Also, copy and paste tracebacks produced by the bug.

System Information (please complete the following information):

• OS: Windows
• Textattack version: 0.3.8

Additional context Potential fix that is working so far --> cap the values to the max that numpy can handle for int64

    def _alter_number(self, num):
        """helper function of _get_new_number, replace a number with another
        random number within the range of self.max_change."""
        if num not in [0, 2, 4]:
            change = int(num * self.max_change) + 1
            if num >= 0:
                num_list = np.random.randint(
                    low=max(num - change, 1), 
                    high=min(num + change, np.iinfo(np.int64).max - 1), 
                    size=self.n,
                    dtype=np.int64)
            else:
                num_list = np.random.randint(
                    low=max(num - change, np.iinfo(np.int64).min + 1), 
                    high=min(0, num + change), 
                    size=self.n,
                    dtype=np.int64)
            return num_list
        return []