




"""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__			=		pytest.mark.integration


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

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

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







def 	_snake_case     (							lowercase__						):
				@wraps(lowercase__						)
				def wrapper(self				,       lowercase__						):
								if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
												self.skipTest('"test requires Fairseq"'						)
								else:
												test_case(self				,       lowercase__						)

				return wrapper







def 	_snake_case     (							lowercase__						):
				@wraps(lowercase__						)
				def wrapper(self				,       lowercase__						):
								if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
												self.skipTest('"test requires transformers"'						)
								else:
												test_case(self				,       lowercase__						)

				return wrapper







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

				return wrapper







def 	_snake_case     (							):
				_lowerCamelCase	:     Union[str, 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(
    lowercase,      lowercase,      lowercase		)
@local
class lowerCAmelCase__      (	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    A_       (    self    , lowercase    ):
							_lowerCamelCase	:     int       =       '[...]'
							_lowerCamelCase	:     Dict       =       importlib.import_module(
							    datasets.load.metric_module_factory(os.path.join('metrics'    , lowercase    )    ).module_path    )
							_lowerCamelCase	:     int       =       datasets.load.import_main_class(metric_module.__name__    , dataset=lowercase    )
							# check parameters
							_lowerCamelCase	:     List[str]       =       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(lowercase    , metric_module.__name__    ):
											with self.use_local_metrics():
															try:
																			_lowerCamelCase	:     Optional[int]       =       doctest.testmod(lowercase    , verbose=lowercase    , raise_on_error=lowercase    )
															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    A_       (    self    , lowercase    ):
							_lowerCamelCase	:     List[str]       =       '[...]'
							_lowerCamelCase	:     Optional[Any]       =       importlib.import_module(
							    datasets.load.metric_module_factory(os.path.join('metrics'    , lowercase    )    ).module_path    )
							# run doctest
							with self.use_local_metrics():
											_lowerCamelCase	:     List[str]       =       doctest.testmod(lowercase    , verbose=lowercase    , raise_on_error=lowercase    )
							self.assertEqual(results.failed    , 0    )
							self.assertGreater(results.attempted    , 1    )
			@contextmanager
			def    A_       (    self    , lowercase    , lowercase    ):
							if metric_name in self.INTENSIVE_CALLS_PATCHER:
											with self.INTENSIVE_CALLS_PATCHER[metric_name](lowercase    ):
															yield
							else:
											yield
			@contextmanager
			def    A_       (    self    ):
							def load_local_metric(lowercase    , *lowercase    , **lowercase    ):
											return load_metric(os.path.join('metrics'    , lowercase    )    , *lowercase    , **lowercase    )

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






			@classmethod
			def    A_       (    cls    , lowercase    ):
							def wrapper(lowercase    ):
											_lowerCamelCase	:     Union[str, Any]       =       contextmanager(lowercase    )
											_lowerCamelCase	:     Optional[Any]       =       patcher
											return patcher

							return wrapper







@LocalMetricTest.register_intensive_calls_patcher('bleurt'						)
def 	_snake_case     (							lowercase__						):
				import tensorflow.compat.va as tf
				from bleurt.score import Predictor

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






				class lowerCAmelCase__      (	lowercase		):






							'''simple docstring'''



							def    A_       (    self    , lowercase    ):
											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	:     Tuple       =       MockedPredictor()
								yield







@LocalMetricTest.register_intensive_calls_patcher('bertscore'						)
def 	_snake_case     (							lowercase__						):
				import torch

				def bert_cos_score_idf(lowercase__				,       lowercase__				,       *lowercase__				,       **lowercase__						):
								return torch.tensor([[1.0, 1.0, 1.0]] * len(lowercase__						)						)

				# 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	:     Any       =       bert_cos_score_idf
								yield







@LocalMetricTest.register_intensive_calls_patcher('comet'						)
def 	_snake_case     (							lowercase__						):
				def load_from_checkpoint(lowercase__						):






								class lowerCAmelCase__      :






											'''simple docstring'''



											def    A_       (    self    , lowercase    , *lowercase    , **lowercase    ):
															assert len(lowercase    ) == 2
															_lowerCamelCase	:     List[str]       =       [0.19, 0.92]
															return scores, sum(lowercase    ) / len(lowercase    )

								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	:     Optional[Any]       =       None
								with patch('comet.load_from_checkpoint'						) as mock_load_from_checkpoint:
												_lowerCamelCase	:     int       =       load_from_checkpoint
												yield







def 	_snake_case     (							):
				_lowerCamelCase	:     Any       =       load_metric(os.path.join('metrics'				,       'seqeval'						)						)
				_lowerCamelCase	:     Tuple       =       'ERROR'
				_lowerCamelCase	:     Union[str, Any]       =       f'''Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}'''
				with pytest.raises(lowercase__				,       match=re.escape(lowercase__						)						):
								metric.compute(predictions=[]				,       references=[]				,       scheme=lowercase__						)





"""simple docstring"""






def 	_snake_case     (							lowercase__ = 1				,       lowercase__ = 1000						):
				_lowerCamelCase	:     Optional[int]       =       1
				_lowerCamelCase	:     List[Any]       =       0

				for divide_by_number in range(lowercase__				,       digit + 1						):
								_lowerCamelCase	:     list[int]       =       []
								_lowerCamelCase	:     Dict       =       numerator
								for _ in range(1				,       digit + 1						):
												if now_divide in has_been_divided:
																if longest_list_length < len(lowercase__						):
																				_lowerCamelCase	:     Any       =       len(lowercase__						)
																				_lowerCamelCase	:     Any       =       divide_by_number
												else:
																has_been_divided.append(lowercase__						)
																_lowerCamelCase	:     int       =       now_divide * 10 % divide_by_number

				return the_digit


# Tests
if __name__ == "__main__":
			import doctest

			doctest.testmod()