






from PIL import Image






def 						a    (		lowerCamelCase_	,     lowerCamelCase_       ):






				'''simple docstring'''

				def brightness(lowerCamelCase_       ) -> float:
								return 128 + level + (c - 128)

				if not -255.0 <= level <= 255.0:
								raise ValueError('''level must be between -255.0 (black) and 255.0 (white)'''       )
				return img.point(_SCREAMING_SNAKE_CASE       )


if __name__ == "__main__":
					# Load image
					with Image.open('image_data/lena.jpg') as img:
										# Change brightness to 100
										A__			:    Any         =				change_brightness(img, 1_00)
										brigt_img.save('image_data/lena_brightness.png', format='png')












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


A__			:    Any         =				{'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__			:    Union[str, Any]         =				[
							    'UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'UniSpeechForCTC',
							    'UniSpeechForPreTraining',
							    'UniSpeechForSequenceClassification',
							    'UniSpeechModel',
							    'UniSpeechPreTrainedModel',
							]

if TYPE_CHECKING:
							from .configuration_unispeech import UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_unispeech import (
														    UNISPEECH_PRETRAINED_MODEL_ARCHIVE_LIST,
														    UniSpeechForCTC,
														    UniSpeechForPreTraining,
														    UniSpeechForSequenceClassification,
														    UniSpeechModel,
														    UniSpeechPreTrainedModel,
														)

else:
							import sys

							A__			:    List[Any]         =				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




