

from typing import Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
 from PIL import Image

 from ..image_utils import load_image

if is_torch_available():
 from ..models.auto.modeling_auto import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING

_UpperCamelCase     			=     logging.get_logger(__name__)



@add_end_docstrings(snake_case__   )
class        lowercase		(			snake_case__   ):



 '''simple docstring'''


 def __init__(self			,			*__a			,			**__a					)					->   List[str]:






  """simple docstring"""





  super().__init__(*_UpperCamelCase			,			**_UpperCamelCase					)
  self.check_model_type(_UpperCamelCase					)




 def     UpperCamelCase__				(self			,			__a=None			,			__a=None			,			__a=None			,			**__a					)					->   Dict:






  """simple docstring"""





  UpperCAmelCase__							,       UpperCAmelCase__     							=							{}, {}
  if padding is not None:
   UpperCAmelCase__     							=							padding
  if truncation is not None:
   UpperCAmelCase__     							=							truncation
  if top_k is not None:
   UpperCAmelCase__     							=							top_k
  return preprocess_params, {}, postprocess_params




 def __call__(self			,			__a			,			__a = None			,			**__a					)					->   str:






  """simple docstring"""





  if isinstance(_UpperCamelCase			,			(Image.Image, str)					) and isinstance(_UpperCamelCase			,			_UpperCamelCase					):
   UpperCAmelCase__     							=							{'image': image, 'question': question}
  else:
   UpperCAmelCase__     							=							image
  UpperCAmelCase__     							=							super().__call__(_UpperCamelCase			,			**_UpperCamelCase					)
  return results




 def     UpperCamelCase__				(self			,			__a			,			__a=False			,			__a=False					)					->   Any:






  """simple docstring"""





  UpperCAmelCase__     							=							load_image(inputs['image']					)
  UpperCAmelCase__     							=							self.tokenizer(
      inputs['question']			,			return_tensors=self.framework			,			padding=_UpperCamelCase			,			truncation=_UpperCamelCase					)
  UpperCAmelCase__     							=							self.image_processor(images=_UpperCamelCase			,			return_tensors=self.framework					)
  model_inputs.update(_UpperCamelCase					)
  return model_inputs




 def     UpperCamelCase__				(self			,			__a					)					->   Any:






  """simple docstring"""





  UpperCAmelCase__     							=							self.model(**_UpperCamelCase					)
  return model_outputs




 def     UpperCamelCase__				(self			,			__a			,			__a=5					)					->   Optional[int]:






  """simple docstring"""





  if top_k > self.model.config.num_labels:
   UpperCAmelCase__     							=							self.model.config.num_labels

  if self.framework == "pt":
   UpperCAmelCase__     							=							model_outputs.logits.sigmoid()[0]
   UpperCAmelCase__							,       UpperCAmelCase__     							=							probs.topk(_UpperCamelCase					)
  else:
   raise ValueError(F"Unsupported framework: {self.framework}"					)

  UpperCAmelCase__     							=							scores.tolist()
  UpperCAmelCase__     							=							ids.tolist()
  return [{"score": score, "answer": self.model.config.idalabel[_id]} for score, _id in zip(_UpperCamelCase			,			_UpperCamelCase					)]






import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


UpperCamelCase__		 =     get_logger(__name__)

class     __snake_case    (				enum.Enum  ):
       """simple docstring"""







       __SCREAMING_SNAKE_CASE				    =							"all_checks"
       __SCREAMING_SNAKE_CASE				    =							"basic_checks"
       __SCREAMING_SNAKE_CASE				    =							"no_checks"






class     __snake_case    (				snake_case__  ):
       """simple docstring"""













class     __snake_case    (				snake_case__  ):
       """simple docstring"""













class     __snake_case    (				snake_case__  ):
       """simple docstring"""













class     __snake_case    (				snake_case__  ):
       """simple docstring"""














def 						lowerCamelCase__      ( __A    :Optional[dict]	,__A    :dict	,__A    :Any=None		):


       """simple docstring"""




       if expected_checksums is None:
              logger.info("""Unable to verify checksums."""		)
              return
       if len(set(__A		) - set(__A		)		) > 0:
              raise ExpectedMoreDownloadedFiles(str(set(__A		) - set(__A		)		)		)
       if len(set(__A		) - set(__A		)		) > 0:
              raise UnexpectedDownloadedFile(str(set(__A		) - set(__A		)		)		)
       __snake_case       	=							[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
       __snake_case       	=							""" for """ + verification_name if verification_name is not None else """"""
       if len(__A		) > 0:
              raise NonMatchingChecksumError(
                  F'Checksums didn\'t match{for_verification_name}:\n'
                  F'{bad_urls}\n'
                  """Set `verification_mode='no_checks'` to skip checksums verification and ignore this error"""		)
       logger.info("""All the checksums matched successfully""" + for_verification_name		)

class     __snake_case    (				snake_case__  ):
       """simple docstring"""













class     __snake_case    (				snake_case__  ):
       """simple docstring"""













class     __snake_case    (				snake_case__  ):
       """simple docstring"""













class     __snake_case    (				snake_case__  ):
       """simple docstring"""














def 						lowerCamelCase__      ( __A    :Optional[dict]	,__A    :dict		):


       """simple docstring"""




       if expected_splits is None:
              logger.info("""Unable to verify splits sizes."""		)
              return
       if len(set(__A		) - set(__A		)		) > 0:
              raise ExpectedMoreSplits(str(set(__A		) - set(__A		)		)		)
       if len(set(__A		) - set(__A		)		) > 0:
              raise UnexpectedSplits(str(set(__A		) - set(__A		)		)		)
       __snake_case       	=							[
           {"""expected""": expected_splits[name], """recorded""": recorded_splits[name]}
           for name in expected_splits
           if expected_splits[name].num_examples != recorded_splits[name].num_examples
       ]
       if len(__A		) > 0:
              raise NonMatchingSplitsSizesError(str(__A		)		)
       logger.info("""All the splits matched successfully."""		)







def 						lowerCamelCase__      ( __A    :str	,__A    :bool = True		):


       """simple docstring"""




       if record_checksum:
              __snake_case       	=							shaaaa()
              with open(__A	,"""rb"""		) as f:
                     for chunk in iter(lambda: f.read(1 << 2_0		)	,b""""""		):
                            m.update(__A		)
                     __snake_case       	=							m.hexdigest()
       else:
              __snake_case       	=							None
       return {"num_bytes": os.path.getsize(__A		), "checksum": checksum}







def 						lowerCamelCase__      ( __A    :Optional[int]		):


       """simple docstring"""




       if dataset_size and config.IN_MEMORY_MAX_SIZE:
              return dataset_size < config.IN_MEMORY_MAX_SIZE
       else:
              return False

