import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


snake_case__				= get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
@require_tokenizers
class  UpperCamelCase				( __lowercase   ,  unittest.TestCase ):

     '''simple docstring'''

     A_										=  XGLMTokenizer
     A_										=  XGLMTokenizerFast
     A_										=  True
     A_										=  True



     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           super().setUp()

           # We have a SentencePiece fixture for testing
           _lowerCamelCase			    =				XGLMTokenizer(A_				,				keep_accents=A_						)
           tokenizer.save_pretrained(self.tmpdirname						)



     def 		UpperCamelCase_						(					self						) ->				str:






           """simple docstring"""
           _lowerCamelCase			    =				'''<pad>'''
           _lowerCamelCase			    =				1

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



     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           _lowerCamelCase			    =				list(self.get_tokenizer().get_vocab().keys()						)

           self.assertEqual(vocab_keys[0]				,				'''<s>'''						)
           self.assertEqual(vocab_keys[1]				,				'''<pad>'''						)
           self.assertEqual(len(A_						)				,				10_08						)



     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           self.assertEqual(self.get_tokenizer().vocab_size				,				10_08						)



     def 		UpperCamelCase_						(					self						) ->				str:






           """simple docstring"""
           _lowerCamelCase			    =				XGLMTokenizer(A_				,				keep_accents=A_						)

           _lowerCamelCase			    =				tokenizer.tokenize('''This is a test'''						)
           self.assertListEqual(A_				,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']						)

           self.assertListEqual(
               tokenizer.convert_tokens_to_ids(A_						)				,				[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]				,				)

           _lowerCamelCase			    =				tokenizer.tokenize('''I was born in 92000, and this is falsé.'''						)
           self.assertListEqual(
               A_				,				[
                   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''',
                   '''.''',
               ]				,				)
           _lowerCamelCase			    =				tokenizer.convert_tokens_to_ids(A_						)
           self.assertListEqual(
               A_				,				[
                   value + tokenizer.fairseq_offset
                   for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
               ]				,				)

           _lowerCamelCase			    =				tokenizer.convert_ids_to_tokens(A_						)
           self.assertListEqual(
               A_				,				[
                   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 		UpperCamelCase_						(					self						) ->				Optional[Any]:






           """simple docstring"""
           return XGLMTokenizer.from_pretrained('''facebook/xglm-564M'''						)



     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           with tempfile.NamedTemporaryFile() as f:
                 shutil.copyfile(A_				,				f.name						)
                 _lowerCamelCase			    =				XGLMTokenizer(f.name				,				keep_accents=A_						)
                 _lowerCamelCase			    =				pickle.dumps(A_						)
           pickle.loads(A_						)



     def 		UpperCamelCase_						(					self						) ->				str:






           """simple docstring"""
           if not self.test_rust_tokenizer:
                 return

           _lowerCamelCase			    =				self.get_tokenizer()
           _lowerCamelCase			    =				self.get_rust_tokenizer()

           _lowerCamelCase			    =				'''I was born in 92000, and this is falsé.'''

           _lowerCamelCase			    =				tokenizer.tokenize(A_						)
           _lowerCamelCase			    =				rust_tokenizer.tokenize(A_						)
           self.assertListEqual(A_				,				A_						)

           _lowerCamelCase			    =				tokenizer.encode(A_				,				add_special_tokens=A_						)
           _lowerCamelCase			    =				rust_tokenizer.encode(A_				,				add_special_tokens=A_						)
           self.assertListEqual(A_				,				A_						)

           _lowerCamelCase			    =				self.get_rust_tokenizer()
           _lowerCamelCase			    =				tokenizer.encode(A_						)
           _lowerCamelCase			    =				rust_tokenizer.encode(A_						)
           self.assertListEqual(A_				,				A_						)



     @slow
     def 		UpperCamelCase_						(					self						) ->				Optional[int]:






           """simple docstring"""
           _lowerCamelCase			    =				'''Hello World!'''
           _lowerCamelCase			    =				[2, 3_12_27, 44_47, 35]

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



     @slow
     def 		UpperCamelCase_						(					self						) ->				Optional[Any]:






           """simple docstring"""
           _lowerCamelCase			    =				(
               '''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
           _lowerCamelCase			    =				[2, 10_18, 67, 11, 19_88, 26_17, 56_31, 2_78, 11, 34_07, 48, 7_16_30, 2_80_85, 4, 32_34, 1_57, 13, 6, 5, 6, 4, 35_26, 7_68, 15, 6_59, 57, 2_98, 39_83, 8_64, 1_29, 21, 6, 5, 1_36_75, 3_77, 6_52, 75_80, 1_03_41, 1_55, 28_17, 4_22, 16_66, 7, 16_74, 53, 1_13, 20_22_77, 1_78_92, 33, 60, 87, 4, 32_34, 1_57, 61, 26_67, 5_23_76, 19, 88, 23, 7_35]
           # fmt: on

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





     @slow
     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           # fmt: off
           _lowerCamelCase			    =				{
               '''input_ids''': [[2, 10_88_25, 11_63, 15, 8_80_10, 4_73, 1_58_98, 1_57, 1_36_72, 18_57, 3_12, 8, 23_80_21, 11_63, 53, 1_36_72, 18_57, 3_12, 8, 5_32_83, 18_23_96, 8, 1_85_66, 16, 3_67_33, 41_01, 8, 2_30, 24_40_17, 12_25_53, 7, 15, 13_25_97, 4, 2_93, 1_25_11, 76_10, 4, 34_14, 13_25_97, 9, 4, 3_23_61, 3_62, 4, 7_34, 2_85_12, 3_25_69, 18, 4, 3_23_61, 2_60_96, 1_49_82, 73, 1_87_15, 2_14_33, 23_52_61, 15, 4_92, 1_24_27, 16, 53, 1_87_15, 2_14_33, 6_54_54, 15, 2_36_59, 5_63, 16, 2_78, 5_97, 28_43, 5_95, 79_31, 18_23_96, 6_41_86, 22, 8_86, 5_95, 13_29_81, 53, 2_55_40, 34_49, 4_39_82, 3_99_01, 59_51, 8_78, 3_30, 4, 2_76_94, 8_02_69, 3_12, 53, 65_17, 1_17_80, 6_11, 2_04_08, 5], [2, 6, 13_25_97, 67, 4_28_97, 33, 5_92, 8, 16_37_29, 2_55_40, 3_61, 13_69_97, 10_95_14, 17_32_30, 7, 5_01, 60, 10_29_13, 1_96, 56_31, 2_35, 6_32_43, 4_73, 6, 23_17_57, 74, 52_77, 79_05, 53, 30_95, 3_73_17, 22, 4_54, 18_38_74, 5], [2, 2_68, 3_12_98, 4_65_30, 6, 13_29_35, 4_38_31, 7, 5_97, 32, 24, 36_88, 98_65, 5]],
               '''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, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
           }  # noqa: E501
           # fmt: on

           self.tokenizer_integration_test_util(
               expected_encoding=A_				,				model_name='''facebook/xglm-564M'''				,				padding=A_				,				)
from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)