





from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available





@dataclass
class A_      (    _lowerCamelCase     ):
   lowerCAmelCase__       =				42


if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
       from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
       from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline












from unittest.mock import patch

import datasets
from datasets import Dataset



def _a       (			)			->		Optional[Any]:







      '''simple docstring'''






      __A      =       Dataset.from_dict({'''col_1''': [3, 2, 0, 1]}				)

      with patch('''tqdm.auto.tqdm'''				) as mock_tqdm:
            datasets.disable_progress_bar()
            dset.map(lambda lowerCamelCase				: {"col_2": x["col_1"] + 1}				)
            mock_tqdm.assert_not_called()

            mock_tqdm.reset_mock()

            datasets.enable_progress_bar()
            dset.map(lambda lowerCamelCase				: {"col_2": x["col_1"] + 1}				)
            mock_tqdm.assert_called()





