

'''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
UpperCamelCase_							=					pytest.mark.integration


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

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

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






def 							_lowerCAmelCase (      __magic_name__	:    str	):
						@wraps(SCREAMING_SNAKE_CASE_	)
						def wrapper(self	:    Optional[int]      ,   __magic_name__	:    Optional[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 							_lowerCAmelCase (      __magic_name__	:    Dict	):
						@wraps(SCREAMING_SNAKE_CASE_	)
						def wrapper(self	:    Dict      ,   __magic_name__	:    str	):
												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 							_lowerCAmelCase (      __magic_name__	:    Dict	):
						@wraps(SCREAMING_SNAKE_CASE_	)
						def wrapper(self	:    Optional[Any]      ,   __magic_name__	:    Optional[int]	):
												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 							_lowerCAmelCase (      ):
						lowercase   :       Tuple								=[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(
    _lowerCamelCase	,       _lowerCamelCase	,       _lowerCamelCase			)
@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    lowerCamelCase_  (					self    :		int		,				UpperCAmelCase__    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       str								='''[...]'''
										lowercase   :       int								=importlib.import_module(
										    datasets.load.metric_module_factory(os.path.join('''metrics'''		,				A__      )      ).module_path      )
										lowercase   :       str								=datasets.load.import_main_class(metric_module.__name__		,				dataset=A__      )
										# check parameters
										lowercase   :       List[Any]								=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:
																												lowercase   :       Union[str, Any]								=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    lowerCamelCase_  (					self    :		Union[str, Any]		,				UpperCAmelCase__    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       Optional[int]								='''[...]'''
										lowercase   :       List[str]								=importlib.import_module(
										    datasets.load.metric_module_factory(os.path.join('''metrics'''		,				A__      )      ).module_path      )
										# run doctest
										with self.use_local_metrics():
																lowercase   :       Optional[Any]								=doctest.testmod(A__		,				verbose=A__		,				raise_on_error=A__      )
										self.assertEqual(results.failed		,				0      )
										self.assertGreater(results.attempted		,				1      )







				@contextmanager
				def    lowerCamelCase_  (					self    :		List[Any]		,				UpperCAmelCase__    :		List[Any]		,				UpperCAmelCase__    :		int      ):
										'''simple docstring'''
										if metric_name in self.INTENSIVE_CALLS_PATCHER:
																with self.INTENSIVE_CALLS_PATCHER[metric_name](A__      ):
																						yield
										else:
																yield







				@contextmanager
				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										def load_local_metric(UpperCAmelCase__    :		Optional[int]		,				*UpperCAmelCase__    :		Union[str, Any]		,				**UpperCAmelCase__    :		Any      ):
																return load_metric(os.path.join('''metrics'''		,				A__      )		,				*A__		,				**A__      )

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







				@classmethod
				def    lowerCamelCase_  (					cls    :		Optional[int]		,				UpperCAmelCase__    :		List[str]      ):
										'''simple docstring'''
										def wrapper(UpperCAmelCase__    :		Any      ):
																lowercase   :       Union[str, Any]								=contextmanager(A__      )
																lowercase   :       List[Any]								=patcher
																return patcher

										return wrapper






@LocalMetricTest.register_intensive_calls_patcher('''bleurt'''	)
def 							_lowerCAmelCase (      __magic_name__	:    Dict	):
						import tensorflow.compat.va as tf
						from bleurt.score import Predictor

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





						class 		__SCREAMING_SNAKE_CASE       ( _lowerCamelCase			):







										def    lowerCamelCase_  (					self    :		List[str]		,				UpperCAmelCase__    :		Dict      ):
																'''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:
												lowercase   :       int								=MockedPredictor()
												yield






@LocalMetricTest.register_intensive_calls_patcher('''bertscore'''	)
def 							_lowerCAmelCase (      __magic_name__	:    str	):
						import torch

						def bert_cos_score_idf(__magic_name__	:    Tuple      ,   __magic_name__	:    Any      ,   *__magic_name__	:    Union[str, Any]      ,   **__magic_name__	:    Dict	):
												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:
												lowercase   :       List[Any]								=bert_cos_score_idf
												yield






@LocalMetricTest.register_intensive_calls_patcher('''comet'''	)
def 							_lowerCAmelCase (      __magic_name__	:    int	):
						def load_from_checkpoint(__magic_name__	:    Dict	):





												class 		__SCREAMING_SNAKE_CASE       :







																def    lowerCamelCase_  (					self    :		str		,				UpperCAmelCase__    :		List[Any]		,				*UpperCAmelCase__    :		List[Any]		,				**UpperCAmelCase__    :		int      ):
																						'''simple docstring'''
																						assert len(A__      ) == 2
																						lowercase   :       Dict								=[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:
												lowercase   :       List[Any]								=None
												with patch('''comet.load_from_checkpoint'''	) as mock_load_from_checkpoint:
																		lowercase   :       List[str]								=load_from_checkpoint
																		yield







def 							_lowerCAmelCase (      ):
						lowercase   :       Union[str, Any]								=load_metric(os.path.join('''metrics'''      ,   '''seqeval'''	)	)
						lowercase   :       Union[str, Any]								='''ERROR'''
						lowercase   :       List[Any]								=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'''





import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase_							=					"""▁"""

UpperCamelCase_							=					get_tests_dir("""fixtures/test_sentencepiece.model""")





@require_sentencepiece
@require_tokenizers
class 		__SCREAMING_SNAKE_CASE       ( lowercase__	,       unittest.TestCase			):
				lowerCamelCase_							=						BigBirdTokenizer
				lowerCamelCase_							=						BigBirdTokenizerFast
				lowerCamelCase_							=						True
				lowerCamelCase_							=						True







				def    lowerCamelCase_  (					self    :		Any      ):
										'''simple docstring'''
										super().setUp()

										lowercase   :       Optional[int]								=self.tokenizer_class(UpperCAmelCase__		,				keep_accents=UpperCAmelCase__      )
										tokenizer.save_pretrained(self.tmpdirname      )







				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										lowercase   :       Optional[int]								='''<s>'''
										lowercase   :       int								=1

										self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase__      )		,				UpperCAmelCase__      )
										self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase__      )		,				UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										lowercase   :       Dict								=list(self.get_tokenizer().get_vocab().keys()      )

										self.assertEqual(vocab_keys[0]		,				'''<unk>'''      )
										self.assertEqual(vocab_keys[1]		,				'''<s>'''      )
										self.assertEqual(vocab_keys[-1]		,				'''[MASK]'''      )
										self.assertEqual(len(UpperCAmelCase__      )		,				1004      )







				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										self.assertEqual(self.get_tokenizer().vocab_size		,				1000      )







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										if not self.test_rust_tokenizer:
																return

										lowercase   :       Optional[int]								=self.get_tokenizer()
										lowercase   :       Any								=self.get_rust_tokenizer()

										lowercase   :       int								='''I was born in 92000, and this is falsé.'''

										lowercase   :       List[str]								=tokenizer.tokenize(UpperCAmelCase__      )
										lowercase   :       Dict								=rust_tokenizer.tokenize(UpperCAmelCase__      )
										self.assertListEqual(UpperCAmelCase__		,				UpperCAmelCase__      )

										lowercase   :       str								=tokenizer.encode(UpperCAmelCase__		,				add_special_tokens=UpperCAmelCase__      )
										lowercase   :       Union[str, Any]								=rust_tokenizer.encode(UpperCAmelCase__		,				add_special_tokens=UpperCAmelCase__      )
										self.assertListEqual(UpperCAmelCase__		,				UpperCAmelCase__      )

										lowercase   :       Optional[Any]								=self.get_rust_tokenizer()
										lowercase   :       Optional[Any]								=tokenizer.encode(UpperCAmelCase__      )
										lowercase   :       Union[str, Any]								=rust_tokenizer.encode(UpperCAmelCase__      )
										self.assertListEqual(UpperCAmelCase__		,				UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Any      ):
										'''simple docstring'''
										lowercase   :       Tuple								=BigBirdTokenizer(UpperCAmelCase__		,				keep_accents=UpperCAmelCase__      )

										lowercase   :       Tuple								=tokenizer.tokenize('''This is a test'''      )
										self.assertListEqual(UpperCAmelCase__		,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']      )

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(UpperCAmelCase__      )		,				[285, 46, 10, 170, 382]		,				)

										lowercase   :       Tuple								=tokenizer.tokenize('''I was born in 92000, and this is falsé.'''      )
										self.assertListEqual(
										    UpperCAmelCase__		,				[
										        SPIECE_UNDERLINE + '''I''',
										        SPIECE_UNDERLINE + '''was''',
										        SPIECE_UNDERLINE + '''b''',
										        '''or''',
										        '''n''',
										        SPIECE_UNDERLINE + '''in''',
										        SPIECE_UNDERLINE + '''''',
										        '''9''',
										        '''2''',
										        '''0''',
										        '''0''',
										        '''0''',
										        ''',''',
										        SPIECE_UNDERLINE + '''and''',
										        SPIECE_UNDERLINE + '''this''',
										        SPIECE_UNDERLINE + '''is''',
										        SPIECE_UNDERLINE + '''f''',
										        '''al''',
										        '''s''',
										        '''é''',
										        '''.''',
										    ]		,				)
										lowercase   :       Any								=tokenizer.convert_tokens_to_ids(UpperCAmelCase__      )
										self.assertListEqual(
										    UpperCAmelCase__		,				[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]		,				)

										lowercase   :       List[Any]								=tokenizer.convert_ids_to_tokens(UpperCAmelCase__      )
										self.assertListEqual(
										    UpperCAmelCase__		,				[
										        SPIECE_UNDERLINE + '''I''',
										        SPIECE_UNDERLINE + '''was''',
										        SPIECE_UNDERLINE + '''b''',
										        '''or''',
										        '''n''',
										        SPIECE_UNDERLINE + '''in''',
										        SPIECE_UNDERLINE + '''''',
										        '''<unk>''',
										        '''2''',
										        '''0''',
										        '''0''',
										        '''0''',
										        ''',''',
										        SPIECE_UNDERLINE + '''and''',
										        SPIECE_UNDERLINE + '''this''',
										        SPIECE_UNDERLINE + '''is''',
										        SPIECE_UNDERLINE + '''f''',
										        '''al''',
										        '''s''',
										        '''<unk>''',
										        '''.''',
										    ]		,				)







				@cached_property
				def    lowerCamelCase_  (					self    :		str      ):
										'''simple docstring'''
										return BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''      )







				@slow
				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       str								='''Hello World!'''
										lowercase   :       Union[str, Any]								=[65, 18536, 2260, 101, 66]

										self.assertListEqual(UpperCAmelCase__		,				self.big_tokenizer.encode(UpperCAmelCase__      )      )







				@slow
				def    lowerCamelCase_  (					self    :		List[str]      ):
										'''simple docstring'''
										lowercase   :       int								=(
										    '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
										    ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
										)
										# fmt: off
										lowercase   :       Tuple								=[65, 871, 419, 358, 946, 991, 2521, 452, 358, 1357, 387, 7751, 3536, 112, 985, 456, 126, 865, 938, 5400, 5734, 458, 1368, 467, 786, 2462, 5246, 1159, 633, 865, 4519, 457, 582, 852, 2557, 427, 916, 508, 405, 34324, 497, 391, 408, 11342, 1244, 385, 100, 938, 985, 456, 574, 362, 12597, 3200, 3129, 1172, 66]  # noqa: E231
										# fmt: on
										self.assertListEqual(UpperCAmelCase__		,				self.big_tokenizer.encode(UpperCAmelCase__      )      )







				@require_torch
				@slow
				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										import torch

										from transformers import BigBirdConfig, BigBirdModel

										# Build sequence
										lowercase   :       List[str]								=list(self.big_tokenizer.get_vocab().keys()      )[:10]
										lowercase   :       Dict								=''' '''.join(UpperCAmelCase__      )
										lowercase   :       Union[str, Any]								=self.big_tokenizer.encode_plus(UpperCAmelCase__		,				return_tensors='''pt'''		,				return_token_type_ids=UpperCAmelCase__      )
										lowercase   :       Dict								=self.big_tokenizer.batch_encode_plus(
										    [sequence + ''' ''' + sequence]		,				return_tensors='''pt'''		,				return_token_type_ids=UpperCAmelCase__      )

										lowercase   :       Optional[int]								=BigBirdConfig(attention_type='''original_full'''      )
										lowercase   :       Dict								=BigBirdModel(UpperCAmelCase__      )

										assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

										with torch.no_grad():
																model(**UpperCAmelCase__      )
																model(**UpperCAmelCase__      )







				@slow
				def    lowerCamelCase_  (					self    :		Tuple      ):
										'''simple docstring'''
										lowercase   :       Union[str, Any]								=BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''      )
										lowercase   :       Dict								=tokenizer.decode(tokenizer('''Paris is the [MASK].'''      ).input_ids      )

										self.assertTrue(decoded_text == '''[CLS] Paris is the[MASK].[SEP]'''      )







				@slow
				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										# fmt: off
										lowercase   :       str								={'''input_ids''': [[65, 39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114, 66], [65, 448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
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										self.tokenizer_integration_test_util(
										    expected_encoding=UpperCAmelCase__		,				model_name='''google/bigbird-roberta-base'''		,				revision='''215c99f1600e06f83acce68422f2035b2b5c3510'''		,				)





