



"""simple docstring"""







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

class       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     ["""image_processor""", """tokenizer"""]
			__magic_name__     					=     """AutoImageProcessor"""
			__magic_name__     					=     """AutoTokenizer"""



			def __init__(			self							:				Dict   ,	_lowercase							:				Dict   ,	_lowercase							:				List[Any]		)							->					Dict:
									super().__init__(_lowercase   ,	_lowercase		)
									snake_case   :			Dict						    = self.image_processor



			def __call__(			self							:				Tuple   ,	_lowercase							:				Optional[Any]=None   ,	_lowercase							:				Union[str, Any]=None   ,	_lowercase							:				Union[str, Any]=None   ,	**_lowercase							:				Optional[int]		)							->					Optional[int]:

									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:
															snake_case   :			Any						    = self.tokenizer(_lowercase   ,	return_tensors=_lowercase   ,	**_lowercase		)

									if images is not None:
															snake_case   :			List[Any]						    = self.image_processor(_lowercase   ,	return_tensors=_lowercase   ,	**_lowercase		)

									if text is not None and images is not None:
															snake_case   :			Optional[Any]						    = image_features.pixel_values
															return encoding
									elif text is not None:
															return encoding
									else:
															return BatchEncoding(data=dict(**_lowercase		)   ,	tensor_type=_lowercase		)



			def 				__lowercase					(			self							:				int   ,	*_lowercase							:				int   ,	**_lowercase							:				Optional[Any]		)							->					List[str]:
									return self.tokenizer.batch_decode(*_lowercase   ,	**_lowercase		)



			def 				__lowercase					(			self							:				Optional[Any]   ,	*_lowercase							:				Union[str, Any]   ,	**_lowercase							:				Optional[Any]		)							->					Optional[Any]:
									return self.tokenizer.decode(*_lowercase   ,	**_lowercase		)



			@property
			def 				__lowercase					(			self							:				Any		)							->					Any:
									return ["input_ids", "attention_mask", "pixel_values"]








"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A		=						{}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			A		=						['GPTSw3Tokenizer']


if TYPE_CHECKING:
			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_gpt_swa import GPTSwaTokenizer

else:
			import sys

			A		=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



