





'''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
lowercase__       : Any         =       pytest.mark.integration


lowercase__       : List[str]         =       {'''comet'''}
lowercase__       : Optional[int]         =       importlib.util.find_spec('''fairseq''') is not None

lowercase__       : int         =       {'''code_eval'''}
lowercase__       : int         =       os.name == '''nt'''

lowercase__       : Any         =       {'''bertscore''', '''frugalscore''', '''perplexity'''}
lowercase__       : Union[str, Any]         =       importlib.util.find_spec('''transformers''') is not None






def 			_lowerCAmelCase     (    __snake_case    :					Any     )	->	List[str]:
     @wraps(_snake_case     )
     def wrapper(self    :					Optional[Any]					,				__snake_case    :					Dict     ):
          if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
               self.skipTest('"test requires Fairseq"'     )
          else:
               test_case(self					,				_snake_case     )

     return wrapper






def 			_lowerCAmelCase     (    __snake_case    :					Tuple     )	->	str:
     @wraps(_snake_case     )
     def wrapper(self    :					Optional[int]					,				__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 			_lowerCAmelCase     (    __snake_case    :					Optional[Any]     )	->	Union[str, Any]:
     @wraps(_snake_case     )
     def wrapper(self    :					List[Any]					,				__snake_case    :					str     ):
          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 			_lowerCAmelCase     (    )	->	str:
     __A		:					Optional[Any]						=			[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(
    _A   ,						_A   ,						_A				)
@local
class 					SCREAMING_SNAKE_CASE       (parameterized.TestCase				):
     lowerCAmelCase						     =			{}
     lowerCAmelCase						     =			None


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

          '''simple docstring'''






          __A		:					Optional[int]						=			'[...]'
          __A		:					int						=			importlib.import_module(
              datasets.load.metric_module_factory(os.path.join('metrics'		,      __lowerCAmelCase)).module_path)
          __A		:					int						=			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		:					Optional[int]						=			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 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






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


     @contextmanager
     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase):

          '''simple docstring'''






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


     @contextmanager
     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






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

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


     @classmethod
     def 				SCREAMING_SNAKE_CASE    (		cls		,      _UpperCAmelCase):

          '''simple docstring'''






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

          return wrapper






@LocalMetricTest.register_intensive_calls_patcher('bleurt'     )
def 			_lowerCAmelCase     (    __snake_case    :					List[str]     )	->	Any:
     import tensorflow.compat.va as tf
     from bleurt.score import Predictor

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


     class 					SCREAMING_SNAKE_CASE       (_A				):


          def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

               '''simple docstring'''






               assert len(input_dict['input_ids']) == 2
               return np.array([1.03, 1.04])

          # 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[Any]						=			MockedPredictor()
          yield






@LocalMetricTest.register_intensive_calls_patcher('bertscore'     )
def 			_lowerCAmelCase     (    __snake_case    :					int     )	->	Any:
     import torch

     def bert_cos_score_idf(__snake_case    :					List[Any]					,				__snake_case    :					Optional[int]					,				*__snake_case    :					Union[str, Any]					,				**__snake_case    :					Optional[int]     ):
          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		:					Optional[Any]						=			bert_cos_score_idf
          yield






@LocalMetricTest.register_intensive_calls_patcher('comet'     )
def 			_lowerCAmelCase     (    __snake_case    :					Optional[Any]     )	->	Union[str, Any]:
     def load_from_checkpoint(__snake_case    :					Dict     ):


          class 					SCREAMING_SNAKE_CASE       :


               def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      *_UpperCAmelCase		,      **_UpperCAmelCase):

                    '''simple docstring'''






                    assert len(__lowerCAmelCase) == 2
                    __A		:					Optional[int]						=			[0.19, 0.92]
                    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		:					Tuple						=			None
          with patch('comet.load_from_checkpoint'     ) as mock_load_from_checkpoint:
               __A		:					Optional[int]						=			load_from_checkpoint
               yield







def 			_lowerCAmelCase     (    )	->	List[Any]:
     __A		:					Optional[int]						=			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     )




UpperCAmelCase_		 =					2_5_6
# Modulus to hash a string
UpperCAmelCase_		 =					1_0_0_0_0_0_3

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:str	,   _snake_case	:str				)  ->     bool:
   _A      =       len(_snake_case				)
   _A      =       len(_snake_case				)
   if p_len > t_len:
      return False

   _A      =       0
   _A      =       0
   _A      =       1

   # Calculating the hash of pattern and substring of text
   for i in range(_snake_case				):
      _A      =       (ord(pattern[i]				) + p_hash * alphabet_size) % modulus
      _A      =       (ord(text[i]				) + text_hash * alphabet_size) % modulus
      if i == p_len - 1:
         continue
      _A      =       (modulus_power * alphabet_size) % modulus

   for i in range(0	,   t_len - p_len + 1				):
      if text_hash == p_hash and text[i : i + p_len] == pattern:
         return True
      if i == t_len - p_len:
         continue
      # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
      _A      =       (
          (text_hash - ord(text[i]				) * modulus_power) * alphabet_size
          + ord(text[i + p_len]				)
      ) % modulus
   return False

def 	SCREAMING_SNAKE_CASE_							(	)  ->     None:
   _A      =       '''abc1abc12'''
   _A      =       '''alskfjaldsabc1abc1abc12k23adsfabcabc'''
   _A      =       '''alskfjaldsk23adsfabcabc'''
   assert rabin_karp(_snake_case	,   _snake_case				) and not rabin_karp(_snake_case	,   _snake_case				)

   # Test 2)
   _A      =       '''ABABX'''
   _A      =       '''ABABZABABYABABX'''
   assert rabin_karp(_snake_case	,   _snake_case				)

   # Test 3)
   _A      =       '''AAAB'''
   _A      =       '''ABAAAAAB'''
   assert rabin_karp(_snake_case	,   _snake_case				)

   # Test 4)
   _A      =       '''abcdabcy'''
   _A      =       '''abcxabcdabxabcdabcdabcy'''
   assert rabin_karp(_snake_case	,   _snake_case				)

   # Test 5)
   _A      =       '''Lü'''
   _A      =       '''Lüsai'''
   assert rabin_karp(_snake_case	,   _snake_case				)
   _A      =       '''Lue'''
   assert not rabin_karp(_snake_case	,   _snake_case				)
   print('''Success.'''				)


if __name__ == "__main__":
   test_rabin_karp()



