




import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


__a      :       Tuple				  =   {
    "<": operator.lt,
    "<=": operator.le,
    "==": operator.eq,
    "!=": operator.ne,
    ">=": operator.ge,
    ">": operator.gt,
}



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			str			,				__lowercase   :			Tuple			,				__lowercase   :			List[Any]			,				__lowercase   :			List[Any]			,				__lowercase   :			int			,				__lowercase   :			Optional[Any]    )						->      Optional[int]:





    """simple docstring"""

    if got_ver is None or want_ver is None:
        raise ValueError(
            f"Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider"
            f" reinstalling {pkg}."    )
    if not ops[op](version.parse(__a    )			,				version.parse(__a    )    ):
        raise ImportError(
            f"{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}"    )



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			str			,				__lowercase   :			Optional[str] = None    )						->      Optional[Any]:





    """simple docstring"""

    __A         =	f"\n{hint}" if hint is not None else """"""

    # non-versioned check
    if re.match(R"""^[\w_\-\d]+$"""			,				__a    ):
        __A    ,	__A    ,	__A         =	requirement, None, None
    else:
        __A         =	re.findall(R"""^([^!=<>\s]+)([\s!=<>]{1,2}.+)"""			,				__a    )
        if not match:
            raise ValueError(
                """requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but"""
                f" got {requirement}"    )
        __A    ,	__A         =	match[0]
        __A         =	want_full.split(""","""    )  # there could be multiple requirements
        __A         =	{}
        for w in want_range:
            __A         =	re.findall(R"""^([\s!=<>]{1,2})(.+)"""			,				__a    )
            if not match:
                raise ValueError(
                    """requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,"""
                    f" but got {requirement}"    )
            __A    ,	__A         =	match[0]
            __A         =	want_ver
            if op not in ops:
                raise ValueError(f"{requirement}: need one of {list(ops.keys()    )}, but got {op}"    )

    # special case
    if pkg == "python":
        __A         =	""".""".join([str(__a    ) for x in sys.version_info[:3]]    )
        for op, want_ver in wanted.items():
            _compare_versions(__a			,				__a			,				__a			,				__a			,				__a			,				__a    )
        return

    # check if any version is installed
    try:
        __A         =	importlib.metadata.version(__a    )
    except importlib.metadata.PackageNotFoundError:
        raise importlib.metadata.PackageNotFoundError(
            f"The '{requirement}' distribution was not found and is required by this application. {hint}"    )

    # check that the right version is installed if version number or a range was provided
    if want_ver is not None:
        for op, want_ver in wanted.items():
            _compare_versions(__a			,				__a			,				__a			,				__a			,				__a			,				__a    )






def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Tuple    )						->      List[Any]:





    """simple docstring"""

    __A         =	"""Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main"""
    return require_version(__a			,				__a    )












from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding


class       __lowercase      (	lowercase_  ):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE   						=				["image_processor", "tokenizer"]
     SCREAMING_SNAKE_CASE   						=				"AutoImageProcessor"
     SCREAMING_SNAKE_CASE   						=				"AutoTokenizer"




     def __init__(				self       :			str ,	UpperCamelCase_       :			Any ,	UpperCamelCase_       :			str				):


         """simple docstring"""



         super().__init__(UpperCamelCase_ ,	UpperCamelCase_				)
         __A         =	self.image_processor




     def __call__(				self       :			Optional[Any] ,	UpperCamelCase_       :			Optional[Any]=None ,	UpperCamelCase_       :			Any=None ,	UpperCamelCase_       :			List[Any]=None ,	**UpperCamelCase_       :			int				):


         """simple docstring"""



         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:
             __A         =	self.tokenizer(UpperCamelCase_ ,	return_tensors=UpperCamelCase_ ,	**UpperCamelCase_				)

         if images is not None:
             __A         =	self.image_processor(UpperCamelCase_ ,	return_tensors=UpperCamelCase_ ,	**UpperCamelCase_				)

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




     def 		lowerCAmelCase_     (				self       :			List[str] ,	*UpperCamelCase_       :			Tuple ,	**UpperCamelCase_       :			List[str]				):


         """simple docstring"""



         return self.tokenizer.batch_decode(*UpperCamelCase_ ,	**UpperCamelCase_				)




     def 		lowerCAmelCase_     (				self       :			Any ,	*UpperCamelCase_       :			int ,	**UpperCamelCase_       :			Tuple				):


         """simple docstring"""



         return self.tokenizer.decode(*UpperCamelCase_ ,	**UpperCamelCase_				)





     @property
     def 		lowerCAmelCase_     (				self       :			Optional[Any]				):


         """simple docstring"""



         return ["input_ids", "attention_mask", "pixel_values"]




