






'''simple docstring'''



from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    is_torch_available,
    is_vision_available,
    logging,
    requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline


if is_vision_available():
      from PIL import Image

      from ..image_utils import load_image

if is_tf_available():
      import tensorflow as tf

      from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
      from ..tf_utils import stable_softmax

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

SCREAMING_SNAKE_CASE							=						logging.get_logger(__name__)
@add_end_docstrings(__A					)
class UpperCAmelCase_       (     __A					):




      """simple docstring"""




      def __init__(			self      :		Tuple  ,   *UpperCAmelCase      :		int  ,   **UpperCAmelCase      :		Optional[Any]		)	->	Dict:


       '''simple docstring'''

       super().__init__(*UpperCAmelCase  ,   **UpperCAmelCase		)
       requires_backends(self  ,   '''vision'''		)
       self.check_model_type(
           TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
           if self.framework == '''tf'''
           else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING		)






      def 					A__   (			self      :		str  ,   UpperCAmelCase      :		str=None		)	->	Union[str, Any]:


       '''simple docstring'''

       lowercase       : Dict						={}
       if top_k is not None:
        lowercase       : Union[str, Any]						=top_k
       return {}, {}, postprocess_params






      def __call__(			self      :		str  ,   UpperCAmelCase      :		Union[str, List[str], "Image.Image", List["Image.Image"]]  ,   **UpperCAmelCase      :		str		)	->	Optional[Any]:


       '''simple docstring'''

       return super().__call__(UpperCAmelCase  ,   **UpperCAmelCase		)






      def 					A__   (			self      :		str  ,   UpperCAmelCase      :		Optional[int]		)	->	int:


       '''simple docstring'''

       lowercase       : List[Any]						=load_image(UpperCAmelCase		)
       lowercase       : Optional[Any]						=self.image_processor(images=UpperCAmelCase  ,   return_tensors=self.framework		)
       return model_inputs






      def 					A__   (			self      :		Union[str, Any]  ,   UpperCAmelCase      :		Optional[Any]		)	->	Any:


       '''simple docstring'''

       lowercase       : str						=self.model(**UpperCAmelCase		)
       return model_outputs






      def 					A__   (			self      :		int  ,   UpperCAmelCase      :		Optional[Any]  ,   UpperCAmelCase      :		Any=5		)	->	str:


       '''simple docstring'''

       if top_k > self.model.config.num_labels:
        lowercase       : Any						=self.model.config.num_labels

       if self.framework == "pt":
        lowercase       : Dict						=model_outputs.logits.softmax(-1		)[0]
        lowercase	,		lowercase       : Dict						=probs.topk(UpperCAmelCase		)
       elif self.framework == "tf":
        lowercase       : Tuple						=stable_softmax(model_outputs.logits  ,   axis=-1		)[0]
        lowercase       : Dict						=tf.math.top_k(UpperCAmelCase  ,   k=UpperCAmelCase		)
        lowercase	,		lowercase       : Any						=topk.values.numpy(), topk.indices.numpy()
       else:
        raise ValueError(f'Unsupported framework: {self.framework}'		)

       lowercase       : str						=scores.tolist()
       lowercase       : Dict						=ids.tolist()
       return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(UpperCAmelCase  ,   UpperCAmelCase		)]











'''simple docstring'''



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
SCREAMING_SNAKE_CASE							=						{
    'E': 12.70,
    'T': 9.06,
    'A': 8.17,
    'O': 7.51,
    'I': 6.97,
    'N': 6.75,
    'S': 6.33,
    'H': 6.09,
    'R': 5.99,
    'D': 4.25,
    'L': 4.03,
    'C': 2.78,
    'U': 2.76,
    'M': 2.41,
    'W': 2.36,
    'F': 2.23,
    'G': 2.02,
    'Y': 1.97,
    'P': 1.93,
    'B': 1.29,
    'V': 0.98,
    'K': 0.77,
    'J': 0.15,
    'X': 0.15,
    'Q': 0.10,
    'Z': 0.07,
}
SCREAMING_SNAKE_CASE							=						'ETAOINSHRDLCUMWFGYPBVKJXQZ'
SCREAMING_SNAKE_CASE							=						'ABCDEFGHIJKLMNOPQRSTUVWXYZ'


def 				lowercase_					(     __A			:							str      )							->   dict[str, int]:



 """simple docstring"""




 lowercase       : List[str]						={letter: 0 for letter in string.ascii_uppercase}
 for letter in message.upper():
  if letter in LETTERS:
   letter_count[letter] += 1

 return letter_count


def 				lowercase_					(     __A			:							tuple      )							->   str:



 """simple docstring"""




 return x[0]


def 				lowercase_					(     __A			:							str      )							->   str:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_letter_count(__A      )
 lowercase       : dict[int, list[str]]						={
     freq: [] for letter, freq in letter_to_freq.items()
 }
 for letter in LETTERS:
  freq_to_letter[letter_to_freq[letter]].append(__A      )

 lowercase       : dict[int, str]						={}

 for freq in freq_to_letter:
  freq_to_letter[freq].sort(key=ETAOIN.find       ,   reverse=__A      )
  lowercase       : Optional[int]						=''''''.join(freq_to_letter[freq]      )

 lowercase       : str						=list(freq_to_letter_str.items()      )
 freq_pairs.sort(key=__A       ,   reverse=__A      )

 lowercase       : list[str]						=[freq_pair[1] for freq_pair in freq_pairs]

 return "".join(__A      )


def 				lowercase_					(     __A			:							str      )							->   int:



 """simple docstring"""




 lowercase       : Optional[Any]						=get_frequency_order(__A      )
 lowercase       : Union[str, Any]						=0
 for common_letter in ETAOIN[:6]:
  if common_letter in freq_order[:6]:
   match_score += 1

 for uncommon_letter in ETAOIN[-6:]:
  if uncommon_letter in freq_order[-6:]:
   match_score += 1

 return match_score


if __name__ == "__main__":
      import doctest

      doctest.testmod()



