


# Lint as: python3
import itertools
import os
import re


a : List[str]		=				re.compile(R'''([A-Z]+)([A-Z][a-z])''')
a : Dict		=				re.compile(R'''([a-z\d])([A-Z])''')

a : Any		=				re.compile(R'''(?<!_)_(?!_)''')
a : Any		=				re.compile(R'''(_{2,})''')

a : Any		=				R'''^\w+(\.\w+)*$'''

a : Optional[int]		=				R'''<>:/\|?*'''


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







			__lowercase 					=   _uppercase_uppercase_re.sub(r'''\1_\2'''       ,			_UpperCamelCase  )
			__lowercase 					=   _lowercase_uppercase_re.sub(r'''\1_\2'''       ,			_UpperCamelCase  )
			return name.lower()


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







			__lowercase 					=   _single_underscore_re.split(_UpperCamelCase  )
			__lowercase 					=   [_multiple_underscores_re.split(_UpperCamelCase  ) for n in name]
			return "".join(n.capitalize() for n in itertools.chain.from_iterable(_UpperCamelCase  ) if n != ''''''  )


def 		lowercase_  (     _UpperCamelCase  ):


			'''simple docstring'''







			if os.path.basename(_UpperCamelCase  ) != name:
						raise ValueError(F'Should be a dataset name, not a path: {name}'  )
			return camelcase_to_snakecase(_UpperCamelCase  )


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase  ):


			'''simple docstring'''







			if os.path.basename(_UpperCamelCase  ) != name:
						raise ValueError(F'Should be a dataset name, not a path: {name}'  )
			if not re.match(_split_re       ,			_UpperCamelCase  ):
						raise ValueError(F'Split name should match \'{_split_re}\'\' but got \'{split}\'.'  )
			return F'{filename_prefix_for_name(_UpperCamelCase  )}-{split}'


def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase=None  ):


			'''simple docstring'''







			__lowercase 					=   filename_prefix_for_split(_UpperCamelCase       ,			_UpperCamelCase  )
			if filetype_suffix:
						prefix += F'.{filetype_suffix}'
			__lowercase 					=   os.path.join(_UpperCamelCase       ,			_UpperCamelCase  )
			return F'{filepath}*'





def 		lowercase_  (     _UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase       ,			_UpperCamelCase=None       ,			_UpperCamelCase=None  ):


			'''simple docstring'''







			__lowercase 					=   filename_prefix_for_split(_UpperCamelCase       ,			_UpperCamelCase  )
			__lowercase 					=   os.path.join(_UpperCamelCase       ,			_UpperCamelCase  )

			if shard_lengths:
						__lowercase 					=   len(_UpperCamelCase  )
						__lowercase 					=   [F'{prefix}-{shard_id:05d}-of-{num_shards:05d}' for shard_id in range(_UpperCamelCase  )]
						if filetype_suffix:
									__lowercase 					=   [filename + F'.{filetype_suffix}' for filename in filenames]
						return filenames
			else:
						__lowercase 					=   prefix
						if filetype_suffix:
									filename += F'.{filetype_suffix}'
						return [filename]






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a : List[str]		=				{
    '''configuration_table_transformer''': [
        '''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TableTransformerConfig''',
        '''TableTransformerOnnxConfig''',
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a : Union[str, Any]		=				[
	    '''TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TableTransformerForObjectDetection''',
	    '''TableTransformerModel''',
	    '''TableTransformerPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_table_transformer import (
	    TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    TableTransformerConfig,
	    TableTransformerOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_table_transformer import (
		    TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TableTransformerForObjectDetection,
		    TableTransformerModel,
		    TableTransformerPreTrainedModel,
		)

else:
	import sys

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


