
"""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
_snake_case          =						pytest.mark.integration


_snake_case          =						{'''comet'''}
_snake_case          =						importlib.util.find_spec('''fairseq''') is not None

_snake_case          =						{'''code_eval'''}
_snake_case          =						os.name == '''nt'''

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






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					List[str]						):






							"""simple docstring"""



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

							return wrapper






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					List[str]						):






							"""simple docstring"""



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

							return wrapper






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



							@wraps(SCREAMING_SNAKE_CASE						)
							def wrapper(self:					List[str]     ,  SCREAMING_SNAKE_CASE:					Tuple						):
														if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
																					self.skipTest('"test not supported on Windows"'						)
														else:
																					test_case(self     ,  SCREAMING_SNAKE_CASE						)

							return wrapper






def 	__snake_case  (    ):






							"""simple docstring"""



							_lowerCAmelCase  	=			[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(
    UpperCAmelCase      ,				UpperCAmelCase      ,				UpperCAmelCase							)
@local
class        _SCREAMING_SNAKE_CASE  (  parameterized.TestCase							):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE_:							List[str]							=					{}
				SCREAMING_SNAKE_CASE_:							List[Any]							=					None


				@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'  )
				@pytest.mark.filterwarnings('ignore:load_metric is deprecated:FutureWarning'  )
				def 				__lowerCamelCase	(					self	:			Optional[int]				,     UpperCAmelCase_	:			Optional[Any]  )		->  Union[str, Any]:







											"""simple docstring"""




											_lowerCAmelCase  	=			'[...]'
											_lowerCAmelCase  	=			importlib.import_module(
											    datasets.load.metric_module_factory(os.path.join('metrics'				,     UpperCAmelCase_  )  ).module_path  )
											_lowerCAmelCase  	=			datasets.load.import_main_class(metric_module.__name__				,     dataset=UpperCAmelCase_  )
											# check parameters
											_lowerCAmelCase  	=			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(UpperCAmelCase_				,     metric_module.__name__  ):
																		with self.use_local_metrics():
																									try:
																																_lowerCAmelCase  	=			doctest.testmod(UpperCAmelCase_				,     verbose=UpperCAmelCase_				,     raise_on_error=UpperCAmelCase_  )
																									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 				__lowerCamelCase	(					self	:			Any				,     UpperCAmelCase_	:			str  )		->  Tuple:







											"""simple docstring"""




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


				@contextmanager
				def 				__lowerCamelCase	(					self	:			Union[str, Any]				,     UpperCAmelCase_	:			List[Any]				,     UpperCAmelCase_	:			str  )		->  int:







											"""simple docstring"""




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


				@contextmanager
				def 				__lowerCamelCase	(					self	:			Tuple  )		->  Optional[Any]:







											"""simple docstring"""




											def load_local_metric(UpperCAmelCase_	:			Any				,     *UpperCAmelCase_	:			List[str]				,     **UpperCAmelCase_	:			int  ):
																		return load_metric(os.path.join('metrics'				,     UpperCAmelCase_  )				,     *UpperCAmelCase_				,     **UpperCAmelCase_  )

											with patch('datasets.load_metric'  ) as mock_load_metric:
																		_lowerCAmelCase  	=			load_local_metric
																		yield







				@classmethod
				def 				__lowerCamelCase	(					cls	:			List[str]				,     UpperCAmelCase_	:			int  )		->  int:







											"""simple docstring"""




											def wrapper(UpperCAmelCase_	:			str  ):
																		_lowerCAmelCase  	=			contextmanager(UpperCAmelCase_  )
																		_lowerCAmelCase  	=			patcher
																		return patcher

											return wrapper






@LocalMetricTest.register_intensive_calls_patcher('bleurt'						)
def 	__snake_case  (    SCREAMING_SNAKE_CASE:					int						):






							"""simple docstring"""



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

							tf.flags.DEFINE_string('sv'     ,  ''     ,  ''						)  # handle pytest cli flags
							class        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase							):






											'''simple docstring'''



											def 				__lowerCamelCase	(					self	:			Optional[Any]				,     UpperCAmelCase_	:			str  )		->  Optional[int]:







																		"""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:
														_lowerCAmelCase  	=			MockedPredictor()
														yield






@LocalMetricTest.register_intensive_calls_patcher('bertscore'						)
def 	__snake_case  (    SCREAMING_SNAKE_CASE:					List[Any]						):






							"""simple docstring"""



							import torch

							def bert_cos_score_idf(SCREAMING_SNAKE_CASE:					str     ,  SCREAMING_SNAKE_CASE:					Optional[int]     ,  *SCREAMING_SNAKE_CASE:					Union[str, Any]     ,  **SCREAMING_SNAKE_CASE:					Union[str, Any]						):
														return torch.tensor([[1.0, 1.0, 1.0]] * len(SCREAMING_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:
														_lowerCAmelCase  	=			bert_cos_score_idf
														yield






@LocalMetricTest.register_intensive_calls_patcher('comet'						)
def 	__snake_case  (    SCREAMING_SNAKE_CASE:					Optional[Any]						):






							"""simple docstring"""



							def load_from_checkpoint(SCREAMING_SNAKE_CASE:					Any						):
														class        _SCREAMING_SNAKE_CASE  :






																		'''simple docstring'''



																		def 				__lowerCamelCase	(					self	:			str				,     UpperCAmelCase_	:			Any				,     *UpperCAmelCase_	:			Optional[Any]				,     **UpperCAmelCase_	:			Dict  )		->  Dict:







																									"""simple docstring"""




																									assert len(UpperCAmelCase_  ) == 2
																									_lowerCAmelCase  	=			[0.19, 0.92]
																									return scores, sum(UpperCAmelCase_  ) / len(UpperCAmelCase_  )






														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:
														_lowerCAmelCase  	=			None
														with patch('comet.load_from_checkpoint'						) as mock_load_from_checkpoint:
																					_lowerCAmelCase  	=			load_from_checkpoint
																					yield






def 	__snake_case  (    ):






							"""simple docstring"""



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








"""simple docstring"""



def 	__snake_case  (    SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



							_lowerCAmelCase  	=			[0 for i in range(len(SCREAMING_SNAKE_CASE						)						)]

							# initialize interval's left pointer and right pointer
							_lowerCAmelCase	,		_lowerCAmelCase  	=			0, 0

							for i in range(1     ,  len(SCREAMING_SNAKE_CASE						)						):
														# case when current index is inside the interval
														if i <= right_pointer:
																					_lowerCAmelCase  	=			min(right_pointer - i + 1     ,  z_result[i - left_pointer]						)
																					_lowerCAmelCase  	=			min_edge

														while go_next(SCREAMING_SNAKE_CASE     ,  SCREAMING_SNAKE_CASE     ,  SCREAMING_SNAKE_CASE						):
																					z_result[i] += 1

														# if new index's result gives us more right interval,
														# we've to update left_pointer and right_pointer
														if i + z_result[i] - 1 > right_pointer:
																					_lowerCAmelCase	,		_lowerCAmelCase  	=			i, i + z_result[i] - 1

							return z_result






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					int     ,  SCREAMING_SNAKE_CASE:					list[int]     ,  SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



							return i + z_result[i] < len(SCREAMING_SNAKE_CASE						) and s[z_result[i]] == s[i + z_result[i]]






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					str     ,  SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



							_lowerCAmelCase  	=			0
							# concatenate 'pattern' and 'input_str' and call z_function
							# with concatenated string
							_lowerCAmelCase  	=			z_function(pattern + input_str						)

							for val in z_result:
														# if value is greater then length of the pattern string
														# that means this index is starting position of substring
														# which is equal to pattern string
														if val >= len(SCREAMING_SNAKE_CASE						):
																					answer += 1

							return answer


if __name__ == "__main__":
	import doctest

	doctest.testmod()






