






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

							return wrapper





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

							return wrapper





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

							return wrapper





def 		__UpperCAmelCase     (	):
							snake_case_           =				[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(
    snake_case_			,   snake_case_			,   snake_case_							)
@local
class 					UpperCamelCase_ (     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			,     a   )			->       Tuple:
								snake_case_           =				'[...]'
								snake_case_           =				importlib.import_module(
								    datasets.load.metric_module_factory(os.path.join('metrics'			,     a   )   ).module_path   )
								snake_case_           =				datasets.load.import_main_class(metric_module.__name__			,     dataset=a   )
								# check parameters
								snake_case_           =				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(a			,     metric_module.__name__   ):
															with self.use_local_metrics():
																						try:
																													snake_case_           =				doctest.testmod(a			,     verbose=a			,     raise_on_error=a   )
																						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			,     a   )			->       Any:
								snake_case_           =				'[...]'
								snake_case_           =				importlib.import_module(
								    datasets.load.metric_module_factory(os.path.join('metrics'			,     a   )   ).module_path   )
								# run doctest
								with self.use_local_metrics():
															snake_case_           =				doctest.testmod(a			,     verbose=a			,     raise_on_error=a   )
								self.assertEqual(results.failed			,     0   )
								self.assertGreater(results.attempted			,     1   )




	@contextmanager
	def 				_UpperCamelCase     (			self			,     a			,     a   )			->       str:
								if metric_name in self.INTENSIVE_CALLS_PATCHER:
															with self.INTENSIVE_CALLS_PATCHER[metric_name](a   ):
																						yield
								else:
															yield




	@contextmanager
	def 				_UpperCamelCase     (			self   )			->       List[Any]:
								def load_local_metric(a			,     *a			,     **a   ):
															return load_metric(os.path.join('metrics'			,     a   )			,     *a			,     **a   )

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






	@classmethod
	def 				_UpperCamelCase     (			cls			,     a   )			->       Union[str, Any]:
								def wrapper(a   ):
															snake_case_           =				contextmanager(a   )
															snake_case_           =				patcher
															return patcher

								return wrapper






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

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




							class 					UpperCamelCase_ (     snake_case_							):



								'''simple docstring'''




								def 				_UpperCamelCase     (			self			,     a   )			->       Union[str, Any]:
															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:
														snake_case_           =				MockedPredictor()
														yield





@LocalMetricTest.register_intensive_calls_patcher('bertscore')
def 		__UpperCAmelCase     (	a_):
							import torch

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

							# 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:
														snake_case_           =				bert_cos_score_idf
														yield





@LocalMetricTest.register_intensive_calls_patcher('comet')
def 		__UpperCAmelCase     (	a_):
							def load_from_checkpoint(a_):




														class 					UpperCamelCase_ :



															'''simple docstring'''




															def 				_UpperCamelCase     (			self			,     a			,     *a			,     **a   )			->       Tuple:
																						assert len(a   ) == 2
																						snake_case_           =				[0.19, 0.92]
																						return scores, sum(a   ) / len(a   )






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





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













def 		__UpperCAmelCase     (	a_ = 10**9):
							snake_case_           =				1
							snake_case_           =				2

							snake_case_           =				0
							snake_case_           =				0
							snake_case_           =				0
							while perimeter <= max_perimeter:
														perimeters_sum += perimeter

														prev_value += 2 * value
														value += prev_value

														snake_case_           =				2 * value + 2 if i % 2 == 0 else 2 * value - 2
														i += 1

							return perimeters_sum


if __name__ == "__main__":
	print(f'{solution() = }')





