


"""simple docstring"""


# Lint as: python3
import itertools
import os
import re


A     :   Dict			    =			re.compile(R"([A-Z]+)([A-Z][a-z])")
A     :   Union[str, Any]			    =			re.compile(R"([a-z\d])([A-Z])")

A     :   Any			    =			re.compile(R"(?<!_)_(?!_)")
A     :   List[Any]			    =			re.compile(R"(_{2,})")

A     :   Union[str, Any]			    =			R"^\w+(\.\w+)*$"

A     :   Union[str, Any]			    =			R"<>:/\|?*"


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			_uppercase_uppercase_re.sub(R"\1_\2"    , _UpperCamelCase      )
			__lowerCAmelCase				    =			_lowercase_uppercase_re.sub(R"\1_\2"    , _UpperCamelCase      )
			return name.lower()


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




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


def _lowerCamelCase	(		_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 _lowerCamelCase	(		_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 _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase=None      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			filename_prefix_for_split(_UpperCamelCase    , _UpperCamelCase      )
			if filetype_suffix:
						prefix += f".{filetype_suffix}"
			__lowerCAmelCase				    =			os.path.join(_UpperCamelCase    , _UpperCamelCase      )
			return f"{filepath}*"


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

			'''simple docstring'''




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

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








"""simple docstring"""


import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class   _UpperCamelCase  (   lowerCAmelCase__		):
							'''simple docstring'''







							__UpperCAmelCase						:    Union[str, Any]				      =["""image_processor""", """tokenizer"""]
							__UpperCAmelCase						:    Optional[Any]				      ="""CLIPImageProcessor"""
							__UpperCAmelCase						:    Union[str, Any]				      =("""XLMRobertaTokenizer""", """XLMRobertaTokenizerFast""")

							def __init__(     self    ,   __a=None    ,   __a=None    ,   **__a	):
										__lowerCAmelCase				    =			None
										if "feature_extractor" in kwargs:
													warnings.warn(
													    "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
													    " instead."    ,   __a    ,   )
													__lowerCAmelCase				    =			kwargs.pop("feature_extractor"	)

										__lowerCAmelCase				    =			image_processor if image_processor is not None else feature_extractor
										if image_processor is None:
													raise ValueError("You need to specify an `image_processor`."	)
										if tokenizer is None:
													raise ValueError("You need to specify a `tokenizer`."	)

										super().__init__(__a    ,   __a	)

							def __call__(     self    ,   __a=None    ,   __a=None    ,   __a=None    ,   **__a	):

										if text is None and images is None:
													raise ValueError("You have to specify either text or images. Both cannot be none."	)

										if text is not None:
													__lowerCAmelCase				    =			self.tokenizer(__a    ,   return_tensors=__a    ,   **__a	)

										if images is not None:
													__lowerCAmelCase				    =			self.image_processor(__a    ,   return_tensors=__a    ,   **__a	)

										if text is not None and images is not None:
													__lowerCAmelCase				    =			image_features.pixel_values
													return encoding
										elif text is not None:
													return encoding
										else:
													return BatchEncoding(data=dict(**__a	)    ,   tensor_type=__a	)

							def 			snake_case				(     self    ,   *__a    ,   **__a	):
										return self.tokenizer.batch_decode(*__a    ,   **__a	)

							def 			snake_case				(     self    ,   *__a    ,   **__a	):
										return self.tokenizer.decode(*__a    ,   **__a	)



							@property
							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.tokenizer.model_input_names
										__lowerCAmelCase				    =			self.image_processor.model_input_names
										return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names	)	)




