


'''simple docstring'''

def lowerCamelCase			(			lowerCAmelCase				:	Optional[int]		,		lowerCAmelCase				:	Optional[int] = False		):





	"""simple docstring"""







	if not isinstance(_a		,		_a		):
		__magic_name__       :    int     	=     f'Expected string as input, found {type(_a		)}'
		raise ValueError(_a		)
	if not isinstance(_a		,		_a		):
		__magic_name__       :    Any     	=     f'Expected boolean as use_pascal parameter, found {type(_a		)}'
		raise ValueError(_a		)

	__magic_name__       :    List[Any]     	=     input_str.split('_'		)

	__magic_name__       :    List[str]     	=     0 if use_pascal else 1

	__magic_name__       :    str     	=     words[start_index:]

	__magic_name__       :    str     	=     [word[0].upper() + word[1:] for word in words_to_capitalize]

	__magic_name__       :    Optional[Any]     	=     '''''' if use_pascal else words[0]

	return "".join([initial_word, *capitalized_words]		)


if __name__ == "__main__":
							from doctest import testmod

							testmod()




"""simple docstring"""

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__    :  str							    =	{
    '''configuration_x_clip''': [
        '''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XCLIPConfig''',
        '''XCLIPTextConfig''',
        '''XCLIPVisionConfig''',
    ],
    '''processing_x_clip''': ['''XCLIPProcessor'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__    :  Tuple							    =	[
         '''XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''XCLIPModel''',
         '''XCLIPPreTrainedModel''',
         '''XCLIPTextModel''',
         '''XCLIPVisionModel''',
     ]

if TYPE_CHECKING:
     from .configuration_x_clip import (
         XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
         XCLIPConfig,
         XCLIPTextConfig,
         XCLIPVisionConfig,
     )
     from .processing_x_clip import XCLIPProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_x_clip import (
              XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
              XCLIPModel,
              XCLIPPreTrainedModel,
              XCLIPTextModel,
              XCLIPVisionModel,
          )

else:
     import sys

     lowercase__    :  Tuple							    =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





