





'''simple docstring'''

import argparse
import json
import re
import string
import sys
from collections import Counter







def       a__       (       lowercase      :  Any   )	->	List[Any]:





     """simple docstring"""

     def remove_articles(lowercase      :  Any   ):
          return re.sub(r'''\b(a|an|the)\b''',      ''' ''',      lowercase   )

     def white_space_fix(lowercase      :  int   ):
          return " ".join(text.split()   )

     def remove_punc(lowercase      :  Tuple   ):
          _UpperCamelCase       					= set(string.punctuation   )
          return "".join(ch for ch in text if ch not in exclude   )

     def lower(lowercase      :  Optional[int]   ):
          return text.lower()

     return white_space_fix(remove_articles(remove_punc(lower(lowercase   )   )   )   )







def       a__       (       lowercase      :  Tuple,      lowercase      :  List[str]   )	->	Optional[Any]:





     """simple docstring"""

     _UpperCamelCase       					= normalize_answer(lowercase   ).split()
     _UpperCamelCase       					= normalize_answer(lowercase   ).split()
     _UpperCamelCase       					= Counter(lowercase   ) & Counter(lowercase   )
     _UpperCamelCase       					= sum(common.values()   )
     if num_same == 0:
          return 0
     _UpperCamelCase       					= 1.0 * num_same / len(lowercase   )
     _UpperCamelCase       					= 1.0 * num_same / len(lowercase   )
     _UpperCamelCase       					= (2 * precision * recall) / (precision + recall)
     return fa







def       a__       (       lowercase      :  Union[str, Any],      lowercase      :  int   )	->	Tuple:





     """simple docstring"""

     return normalize_answer(lowercase   ) == normalize_answer(lowercase   )







def       a__       (       lowercase      :  Any,      lowercase      :  Optional[int],      lowercase      :  Any   )	->	Optional[int]:





     """simple docstring"""

     _UpperCamelCase       					= []
     for ground_truth in ground_truths:
          _UpperCamelCase       					= metric_fn(lowercase,      lowercase   )
          scores_for_ground_truths.append(lowercase   )
     return max(lowercase   )







def       a__       (       lowercase      :  List[str],      lowercase      :  Any   )	->	str:





     """simple docstring"""

     _UpperCamelCase       					= _UpperCamelCase       					= _UpperCamelCase       					= 0
     for article in dataset:
          for paragraph in article["paragraphs"]:
               for qa in paragraph["qas"]:
                    total += 1
                    if qa["id"] not in predictions:
                         _UpperCamelCase       					= '''Unanswered question ''' + qa['''id'''] + ''' will receive score 0.'''
                         print(lowercase,      file=sys.stderr   )
                         continue
                    _UpperCamelCase       					= [x['''text'''] for x in qa['''answers''']]
                    _UpperCamelCase       					= predictions[qa['''id''']]
                    exact_match += metric_max_over_ground_truths(lowercase,      lowercase,      lowercase   )
                    fa += metric_max_over_ground_truths(lowercase,      lowercase,      lowercase   )

     _UpperCamelCase       					= 1_0_0.0 * exact_match / total
     _UpperCamelCase       					= 1_0_0.0 * fa / total

     return {"exact_match": exact_match, "f1": fa}


if __name__ == "__main__":
   lowercase__		:    Dict =       '1.1'
   lowercase__		:    Any =       argparse.ArgumentParser(description='Evaluation for SQuAD ' + expected_version)
   parser.add_argument('dataset_file', help='Dataset file')
   parser.add_argument('prediction_file', help='Prediction File')
   lowercase__		:    Any =       parser.parse_args()
   with open(args.dataset_file) as dataset_file:
      lowercase__		:    List[str] =       json.load(dataset_file)
      if dataset_json["version"] != expected_version:
         print(
             'Evaluation expects v-' + expected_version + ', but got dataset with v-' + dataset_json['version'],
             file=sys.stderr,
         )
      lowercase__		:    Optional[int] =       dataset_json['data']
   with open(args.prediction_file) as prediction_file:
      lowercase__		:    Optional[int] =       json.load(prediction_file)
   print(json.dumps(evaluate(dataset, predictions)))










'''simple docstring'''

import inspect

from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax


if is_flax_available():
   import jax
@require_flax
class        __lowerCAmelCase  :






       """simple docstring"""





       def snake_case__		(							self     :	str  )					->  Any:

            '''simple docstring'''




            _UpperCamelCase					,       _UpperCamelCase       					= self.prepare_init_args_and_inputs_for_common()

            _UpperCamelCase       					= self.model_class(**lowerCAmelCase__  )
            _UpperCamelCase       					= model.init(inputs_dict['''prng_key'''] ,				inputs_dict['''sample''']  )
            jax.lax.stop_gradient(lowerCAmelCase__  )

            _UpperCamelCase       					= model.apply(lowerCAmelCase__ ,				inputs_dict['''sample''']  )

            if isinstance(lowerCAmelCase__ ,				lowerCAmelCase__  ):
                 _UpperCamelCase       					= output.sample

            self.assertIsNotNone(lowerCAmelCase__  )
            _UpperCamelCase       					= inputs_dict['''sample'''].shape
            self.assertEqual(output.shape ,				lowerCAmelCase__ ,				'''Input and output shapes do not match'''  )





       def snake_case__		(							self     :	Any  )					->  int:

            '''simple docstring'''




            _UpperCamelCase					,       _UpperCamelCase       					= self.prepare_init_args_and_inputs_for_common()

            _UpperCamelCase       					= 16
            _UpperCamelCase       					= (16, 32)

            _UpperCamelCase       					= self.model_class(**lowerCAmelCase__  )
            _UpperCamelCase       					= model.init(inputs_dict['''prng_key'''] ,				inputs_dict['''sample''']  )
            jax.lax.stop_gradient(lowerCAmelCase__  )

            _UpperCamelCase       					= model.apply(lowerCAmelCase__ ,				inputs_dict['''sample''']  )

            if isinstance(lowerCAmelCase__ ,				lowerCAmelCase__  ):
                 _UpperCamelCase       					= output.sample

            self.assertIsNotNone(lowerCAmelCase__  )
            _UpperCamelCase       					= inputs_dict['''sample'''].shape
            self.assertEqual(output.shape ,				lowerCAmelCase__ ,				'''Input and output shapes do not match'''  )







       def snake_case__		(							self     :	int  )					->  int:

            '''simple docstring'''




            _UpperCamelCase       					= '''kwargs''' in inspect.signature(self.model_class.__init__  ).parameters
            _UpperCamelCase       					= len(self.model_class._deprecated_kwargs  ) > 0

            if has_kwarg_in_model_class and not has_deprecated_kwarg:
                 raise ValueError(
                     f"""{self.model_class} has `**kwargs` in its __init__ method but has not defined any deprecated kwargs"""
                     ''' under the `_deprecated_kwargs` class attribute. Make sure to either remove `**kwargs` if there are'''
                     ''' no deprecated arguments or add the deprecated argument with `_deprecated_kwargs ='''
                     ''' [<deprecated_argument>]`'''  )

            if not has_kwarg_in_model_class and has_deprecated_kwarg:
                 raise ValueError(
                     f"""{self.model_class} doesn't have `**kwargs` in its __init__ method but has defined deprecated kwargs"""
                     ''' under the `_deprecated_kwargs` class attribute. Make sure to either add the `**kwargs` argument to'''
                     f""" {self.model_class}.__init__ if there are deprecated arguments or remove the deprecated argument"""
                     ''' from `_deprecated_kwargs = [<deprecated_argument>]`'''  )



