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
__UpperCamelCase		:       int									=     pytest.mark.integration


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

__UpperCamelCase		:       Optional[int]									=     {'code_eval'}
__UpperCamelCase		:       List[str]									=     os.name == 'nt'

__UpperCamelCase		:       List[Any]									=     {'bertscore', 'frugalscore', 'perplexity'}
__UpperCamelCase		:       List[str]									=     importlib.util.find_spec('transformers') is not None
def       A	(    _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       A	(    _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       A	(    _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       A	(    ):
						SCREAMING_SNAKE_CASE							:    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(
    UpperCamelCase_	,							UpperCamelCase_	,							UpperCamelCase_)
@local
class 					lowercase__						(   parameterized.TestCase):
						UpperCamelCase_     =		{}
						UpperCamelCase_     =		None


						@pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''						)
						@pytest.mark.filterwarnings('''ignore:load_metric is deprecated:FutureWarning'''						)
						def        __A       (       self	:				Union[str, Any]    ,		UpperCamelCase__	:				Optional[Any]						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    int							=							'''[...]'''
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							importlib.import_module(
												    datasets.load.metric_module_factory(os.path.join('''metrics'''    ,		UpperCamelCase__						)						).module_path						)
												SCREAMING_SNAKE_CASE							:    str							=							datasets.load.import_main_class(metric_module.__name__    ,		dataset=UpperCamelCase__						)
												# check parameters
												SCREAMING_SNAKE_CASE							:    Tuple							=							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:
																														SCREAMING_SNAKE_CASE							:    List[Any]							=							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        __A       (       self	:				Union[str, Any]    ,		UpperCamelCase__	:				Any						):





												'''simple docstring'''





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


						@contextmanager
						def        __A       (       self	:				List[Any]    ,		UpperCamelCase__	:				Optional[int]    ,		UpperCamelCase__	:				Optional[Any]						):





												'''simple docstring'''





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


						@contextmanager
						def        __A       (       self	:				Optional[Any]						):





												'''simple docstring'''





												def load_local_metric(UpperCamelCase__	:				str    ,		*UpperCamelCase__	:				Tuple    ,		**UpperCamelCase__	:				str						):
																		return load_metric(os.path.join('''metrics'''    ,		UpperCamelCase__						)    ,		*UpperCamelCase__    ,		**UpperCamelCase__						)

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



						@classmethod
						def        __A       (       cls	:				int    ,		UpperCamelCase__	:				Any						):





												'''simple docstring'''





												def wrapper(UpperCamelCase__	:				List[Any]						):
																		SCREAMING_SNAKE_CASE							:    List[Any]							=							contextmanager(UpperCamelCase__						)
																		SCREAMING_SNAKE_CASE							:    List[str]							=							patcher
																		return patcher

												return wrapper






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

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





						class 					lowercase__						(   UpperCamelCase_):


												def        __A       (       self	:				List[str]    ,		UpperCamelCase__	:				List[Any]						):





																		'''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:
												SCREAMING_SNAKE_CASE							:    List[str]							=							MockedPredictor()
												yield
@LocalMetricTest.register_intensive_calls_patcher('''bertscore'''						)
def       A	(    _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:
												SCREAMING_SNAKE_CASE							:    str							=							bert_cos_score_idf
												yield
@LocalMetricTest.register_intensive_calls_patcher('''comet'''						)
def       A	(    _lowercase						):
						def load_from_checkpoint(_lowercase						):





												class 					lowercase__						:


																		def        __A       (       self	:				Union[str, Any]    ,		UpperCamelCase__	:				int    ,		*UpperCamelCase__	:				Any    ,		**UpperCamelCase__	:				Optional[Any]						):





																								'''simple docstring'''





																								assert len(UpperCamelCase__						) == 2
																								SCREAMING_SNAKE_CASE							:    Tuple							=							[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:
												SCREAMING_SNAKE_CASE							:    List[str]							=							None
												with patch('''comet.load_from_checkpoint'''						) as mock_load_from_checkpoint:
																		SCREAMING_SNAKE_CASE							:    Tuple							=							load_from_checkpoint
																		yield



def       A	(    ):
						SCREAMING_SNAKE_CASE							:    Any							=							load_metric(os.path.join('''metrics'''		,  '''seqeval'''						)						)
						SCREAMING_SNAKE_CASE							:    Dict							=							'''ERROR'''
						SCREAMING_SNAKE_CASE							:    str							=							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						)






def       A	(    _lowercase		,  _lowercase		,  _lowercase						):
						return round(float(moles / volume						) * nfactor						)
def       A	(    _lowercase		,  _lowercase		,  _lowercase						):
						return round(float((moles * 0.0821 * temperature) / (volume)						)						)
def       A	(    _lowercase		,  _lowercase		,  _lowercase						):
						return round(float((moles * 0.0821 * temperature) / (pressure)						)						)
def       A	(    _lowercase		,  _lowercase		,  _lowercase						):
						return round(float((pressure * volume) / (0.0821 * moles)						)						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()





