





"""simple docstring"""



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
a_			=      {
    """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,
}
a_			=      """ETAOINSHRDLCUMWFGYPBVKJXQZ"""
a_			=      """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""







def 		__lowercase					(       snake_case_  :  str						)       ->dict[str, int]:



    '''simple docstring'''







    __A   :						Any									=					{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					(       snake_case_  :  tuple						)       ->str:



    '''simple docstring'''







    return x[0]







def 		__lowercase					(       snake_case_  :  str						)       ->str:



    '''simple docstring'''







    __A   :						Union[str, Any]									=					get_letter_count(snake_case_						)
    __A   :						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(snake_case_						)

    __A   :						dict[int, str]									=					{}

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

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

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

    return "".join(snake_case_						)







def 		__lowercase					(       snake_case_  :  str						)       ->int:



    '''simple docstring'''







    __A   :						Any									=					get_frequency_order(snake_case_						)
    __A   :						str									=					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()











"""simple docstring"""



import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch

import numpy as np
import pytest
from absl.testing import parameterized

import datasets
from datasets import load_metric

from .utils import for_all_test_methods, local, slow


# mark all tests as integration
a_			=      pytest.mark.integration


a_			=      {"""comet"""}
a_			=      importlib.util.find_spec("""fairseq""") is not None

a_			=      {"""code_eval"""}
a_			=      os.name == """nt"""

a_			=      {"""bertscore""", """frugalscore""", """perplexity"""}
a_			=      importlib.util.find_spec("""transformers""") is not None







def 		__lowercase					(       snake_case_  :  str						)       ->Any:



    '''simple docstring'''







    @wraps(snake_case_						)
    def wrapper(self  :  List[Any]    ,snake_case_  :  int						):
        if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
            self.skipTest('''"test requires Fairseq"'''						)
        else:
            test_case(self    ,snake_case_						)

    return wrapper







def 		__lowercase					(       snake_case_  :  int						)       ->str:



    '''simple docstring'''







    @wraps(snake_case_						)
    def wrapper(self  :  List[Any]    ,snake_case_  :  List[str]						):
        if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
            self.skipTest('''"test requires transformers"'''						)
        else:
            test_case(self    ,snake_case_						)

    return wrapper







def 		__lowercase					(       snake_case_  :  Union[str, Any]						)       ->Tuple:



    '''simple docstring'''







    @wraps(snake_case_						)
    def wrapper(self  :  int    ,snake_case_  :  Dict						):
        if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
            self.skipTest('''"test not supported on Windows"'''						)
        else:
            test_case(self    ,snake_case_						)

    return wrapper







def 		__lowercase					(       )       ->Tuple:



    '''simple docstring'''







    __A   :						int									=					[metric_dir.split(os.sep						)[-2] for metric_dir in glob.glob('''./metrics/*/'''						)]
    return [{"testcase_name": x, "metric_name": x} for x in metrics if x != "gleu"]  # gleu is unfinished






@parameterized.named_parameters(get_local_metric_names()					)
@for_all_test_methods(
    SCREAMING_SNAKE_CASE__							,							SCREAMING_SNAKE_CASE__							,							SCREAMING_SNAKE_CASE__					)
@local
class 		__snake_case (		parameterized.TestCase					):





 """simple docstring"""


 _lowerCamelCase				=					{}
 _lowerCamelCase				=					None

 @pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''  )
 @pytest.mark.filterwarnings('''ignore:load_metric is deprecated:FutureWarning'''  )
 def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



     '''simple docstring'''




     __A   :						int									=					'''[...]'''
     __A   :						Any									=					importlib.import_module(
         datasets.load.metric_module_factory(os.path.join('''metrics''' ,						__lowerCamelCase  )  ).module_path  )
     __A   :						str									=					datasets.load.import_main_class(metric_module.__name__ ,						dataset=__lowerCamelCase  )
     # check parameters
     __A   :						Optional[int]									=					inspect.signature(metric._compute  ).parameters
     self.assertTrue(all(p.kind != p.VAR_KEYWORD for p in parameters.values()  )  )  # no **kwargs
     # run doctest
     with self.patch_intensive_calls(__lowerCamelCase ,						metric_module.__name__  ):
         with self.use_local_metrics():
             try:
                 __A   :						Tuple									=					doctest.testmod(__lowerCamelCase ,						verbose=__lowerCamelCase ,						raise_on_error=__lowerCamelCase  )
             except doctest.UnexpectedException as e:
                 raise e.exc_info[1]  # raise the exception that doctest caught
     self.assertEqual(results.failed ,						0  )
     self.assertGreater(results.attempted ,						1  )

 @slow
 def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



     '''simple docstring'''




     __A   :						Any									=					'''[...]'''
     __A   :						Union[str, Any]									=					importlib.import_module(
         datasets.load.metric_module_factory(os.path.join('''metrics''' ,						__lowerCamelCase  )  ).module_path  )
     # run doctest
     with self.use_local_metrics():
         __A   :						Union[str, Any]									=					doctest.testmod(__lowerCamelCase ,						verbose=__lowerCamelCase ,						raise_on_error=__lowerCamelCase  )
     self.assertEqual(results.failed ,						0  )
     self.assertGreater(results.attempted ,						1  )

 @contextmanager
 def  UpperCamelCase__(   self ,						__lowerCamelCase ,						__lowerCamelCase  ):



     '''simple docstring'''




     if metric_name in self.INTENSIVE_CALLS_PATCHER:
         with self.INTENSIVE_CALLS_PATCHER[metric_name](__lowerCamelCase  ):
             yield
     else:
         yield

 @contextmanager
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     def load_local_metric(__lowerCamelCase ,						*__lowerCamelCase ,						**__lowerCamelCase  ):
         return load_metric(os.path.join('''metrics''' ,						__lowerCamelCase  ) ,						*__lowerCamelCase ,						**__lowerCamelCase  )

     with patch('''datasets.load_metric'''  ) as mock_load_metric:
         __A   :						List[Any]									=					load_local_metric
         yield







 @classmethod
 def  UpperCamelCase__(   cls ,						__lowerCamelCase  ):



     '''simple docstring'''




     def wrapper(__lowerCamelCase  ):
         __A   :						Any									=					contextmanager(__lowerCamelCase  )
         __A   :						Optional[Any]									=					patcher
         return patcher

     return wrapper







@LocalMetricTest.register_intensive_calls_patcher('''bleurt'''						)
def 		__lowercase					(       snake_case_  :  Tuple						)       ->int:



    '''simple docstring'''







    import tensorflow.compat.va as tf
    from bleurt.score import Predictor

    tf.flags.DEFINE_string('''sv'''    ,''''''    ,''''''						)  # handle pytest cli flags






    class 		__snake_case (		SCREAMING_SNAKE_CASE__					):





     """simple docstring"""


     def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



         '''simple docstring'''




         assert len(input_dict['''input_ids''']  ) == 2
         return np.array([1.0_3, 1.0_4]  )

    # mock predict_fn which is supposed to do a forward pass with a bleurt model
    with patch('''bleurt.score._create_predictor'''						) as mock_create_predictor:
        __A   :						List[str]									=					MockedPredictor()
        yield







@LocalMetricTest.register_intensive_calls_patcher('''bertscore'''						)
def 		__lowercase					(       snake_case_  :  List[str]						)       ->Dict:



    '''simple docstring'''







    import torch

    def bert_cos_score_idf(snake_case_  :  Union[str, Any]    ,snake_case_  :  List[str]    ,*snake_case_  :  List[str]    ,**snake_case_  :  Dict						):
        return torch.tensor([[1.0, 1.0, 1.0]] * len(snake_case_						)						)

    # mock get_model which is supposed to do download a bert model
    # mock bert_cos_score_idf which is supposed to do a forward pass with a bert model
    with patch('''bert_score.scorer.get_model'''						), patch(
        '''bert_score.scorer.bert_cos_score_idf'''						) as mock_bert_cos_score_idf:
        __A   :						str									=					bert_cos_score_idf
        yield







@LocalMetricTest.register_intensive_calls_patcher('''comet'''						)
def 		__lowercase					(       snake_case_  :  Optional[int]						)       ->List[Any]:



    '''simple docstring'''







    def load_from_checkpoint(snake_case_  :  str						):






        class 		__snake_case :





         """simple docstring"""


         def  UpperCamelCase__(   self ,						__lowerCamelCase ,						*__lowerCamelCase ,						**__lowerCamelCase  ):



             '''simple docstring'''




             assert len(__lowerCamelCase  ) == 2
             __A   :						str									=					[0.1_9, 0.9_2]
             return scores, sum(__lowerCamelCase  ) / len(__lowerCamelCase  )






        return Model()

    # mock load_from_checkpoint which is supposed to do download a bert model
    # mock load_from_checkpoint which is supposed to do download a bert model
    with patch('''comet.download_model'''						) as mock_download_model:
        __A   :						int									=					None
        with patch('''comet.load_from_checkpoint'''						) as mock_load_from_checkpoint:
            __A   :						Dict									=					load_from_checkpoint
            yield







def 		__lowercase					(       )       ->str:



    '''simple docstring'''







    __A   :						Optional[Any]									=					load_metric(os.path.join('''metrics'''    ,'''seqeval'''						)						)
    __A   :						Optional[int]									=					'''ERROR'''
    __A   :						str									=					F"""Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}"""
    with pytest.raises(snake_case_    ,match=re.escape(snake_case_						)						):
        metric.compute(predictions=[]    ,references=[]    ,scheme=snake_case_						)




