




'''simple docstring'''







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





def 						snake_case_							(_a     :							List[str]					):

    def remove_articles(_a     :							Tuple					):
        return re.sub(R'''\b(a|an|the)\b'''   ,       ''' '''   ,       _a					)

    def white_space_fix(_a     :							Any					):
        return " ".join(text.split()					)

    def remove_punc(_a     :							Dict					):
        UpperCAmelCase      	=		set(string.punctuation					)
        return "".join(ch for ch in text if ch not in exclude					)

    def lower(_a     :							List[Any]					):
        return text.lower()

    return white_space_fix(remove_articles(remove_punc(lower(_a					)					)					)					)





def 						snake_case_							(_a     :							Tuple   ,       _a     :							Dict					):
    UpperCAmelCase      	=		normalize_answer(_a					).split()
    UpperCAmelCase      	=		normalize_answer(_a					).split()
    UpperCAmelCase      	=		Counter(_a					) & Counter(_a					)
    UpperCAmelCase      	=		sum(common.values()					)
    if num_same == 0:
        return 0
    UpperCAmelCase      	=		1.0 * num_same / len(_a					)
    UpperCAmelCase      	=		1.0 * num_same / len(_a					)
    UpperCAmelCase      	=		(2 * precision * recall) / (precision + recall)
    return fa





def 						snake_case_							(_a     :							int   ,       _a     :							Optional[int]					):
    return normalize_answer(_a					) == normalize_answer(_a					)





def 						snake_case_							(_a     :							Union[str, Any]   ,       _a     :							List[str]   ,       _a     :							List[str]					):
    UpperCAmelCase      	=		[]
    for ground_truth in ground_truths:
        UpperCAmelCase      	=		metric_fn(_a   ,       _a					)
        scores_for_ground_truths.append(_a					)
    return max(_a					)





def 						snake_case_							(_a     :							int   ,       _a     :							List[str]					):
    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(_a   ,       file=sys.stderr					)
                    continue
                UpperCAmelCase      	=		[x['''text'''] for x in qa['''answers''']]
                UpperCAmelCase      	=		predictions[qa['''id''']]
                exact_match += metric_max_over_ground_truths(_a   ,       _a   ,       _a					)
                fa += metric_max_over_ground_truths(_a   ,       _a   ,       _a					)

    UpperCAmelCase      	=		100.0 * exact_match / total
    UpperCAmelCase      	=		100.0 * fa / total

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


if __name__ == "__main__":
   A			   ='1.1'
   A			   =argparse.ArgumentParser(description='Evaluation for SQuAD ' + expected_version)
   parser.add_argument('dataset_file', help='Dataset file')
   parser.add_argument('prediction_file', help='Prediction File')
   A			   =parser.parse_args()
   with open(args.dataset_file) as dataset_file:
      A			   =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,
         )
      A			   =dataset_json['data']
   with open(args.prediction_file) as prediction_file:
      A			   =json.load(prediction_file)
   print(json.dumps(evaluate(dataset, predictions)))










'''simple docstring'''







import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase


@require_tokenizers
class       _a  (     unittest.TestCase			):
       __a    :					Optional[int]           = EsmTokenizer
       def    A				(     self						:     Tuple    ):



           '''simple docstring'''

           super().setUp()
           UpperCAmelCase      	=		tempfile.mkdtemp()
           # fmt: off
           UpperCAmelCase      	=		["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
           # fmt: on
           UpperCAmelCase      	=		os.path.join(self.tmpdirname       ,    VOCAB_FILES_NAMES['''vocab_file''']    )
           with open(self.vocab_file       ,    '''w'''       ,    encoding='''utf-8'''    ) as vocab_writer:
               vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]    )    )
       def    A				(     self						:     Union[str, Any]       ,    **lowercase						:     Tuple    ):



           '''simple docstring'''

           return [self.get_tokenizer(**lowercase    )]
       def    A				(     self						:     Optional[Any]       ,    **lowercase						:     str    ):



           '''simple docstring'''

           return self.tokenizer_class.from_pretrained(self.tmpdirname       ,    **lowercase    )
       def    A				(     self						:     Optional[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		tokenizer.tokenize('''LAGVS'''    )
           self.assertListEqual(lowercase       ,    ['''L''', '''A''', '''G''', '''V''', '''S''']    )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase    )       ,    [4, 5, 6, 7, 8]    )
       def    A				(     self						:     str    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		'''LAGVS'''
           self.assertListEqual(tokenizer.encode(lowercase    )       ,    [0, 4, 5, 6, 7, 8, 2]    )
       def    A				(     self						:     Optional[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		['''LAGVS''', '''WCB''']
           UpperCAmelCase      	=		tokenizer(lowercase       ,    padding=lowercase    )['''input_ids''']

           self.assertListEqual(lowercase       ,    [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]    )
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		['''LAGVS''', '''WCB''']
           UpperCAmelCase      	=		tokenizer(lowercase       ,    padding=lowercase    )['''input_ids''']

           self.assertListEqual(lowercase       ,    [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]    )







       def    A				(     self						:     Any    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.get_tokenizers(fast=lowercase    )
           for tokenizer in tokenizers:
               with self.subTest(f"{tokenizer.__class__.__name__}"    ):
                   UpperCAmelCase      	=		'''<unk>'''
                   UpperCAmelCase      	=		'''<mask>'''

                   UpperCAmelCase      	=		tokenizer.tokenize(lowercase    )
                   UpperCAmelCase      	=		tokenizer.tokenize(lowercase    )

                   self.assertEqual(len(lowercase    )       ,    1    )
                   self.assertEqual(len(lowercase    )       ,    1    )
                   self.assertEqual(token_a[0]       ,    lowercase    )
                   self.assertEqual(token_a[0]       ,    lowercase    )




