
import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
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


lowercase__		:Any   =    get_tests_dir("fixtures/test_sentencepiece.model")







@require_sentencepiece
@require_tokenizers
class 				lowercase		(					SCREAMING_SNAKE_CASE__       ,  unittest.TestCase		):
							lowercase_       :       Union[str, Any]       					=ReformerTokenizer
							lowercase_       :       Union[str, Any]       					=ReformerTokenizerFast
							lowercase_       :       Dict       					=True
							lowercase_       :       Union[str, Any]       					=False
							lowercase_       :       Any       					=True




							def  A__      (				self):
												super().setUp()

												lowercase							=						ReformerTokenizer(A__   ,keep_accents=A__)
												tokenizer.save_pretrained(self.tmpdirname)




							def  A__      (				self):
												lowercase							=						'''<s>'''
												lowercase							=						1

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




							def  A__      (				self):
												lowercase							=						list(self.get_tokenizer().get_vocab().keys())

												self.assertEqual(vocab_keys[0]   ,'''<unk>''')
												self.assertEqual(vocab_keys[1]   ,'''<s>''')
												self.assertEqual(vocab_keys[-1]   ,'''j''')
												self.assertEqual(len(A__)   ,1_0_0_0)




							def  A__      (				self):
												self.assertEqual(self.get_tokenizer().vocab_size   ,1_0_0_0)




							def  A__      (				self):
												if not self.test_rust_tokenizer:
																	return

												lowercase							=						self.get_tokenizer()
												lowercase							=						self.get_rust_tokenizer()

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

												lowercase							=						tokenizer.tokenize(A__)
												lowercase							=						rust_tokenizer.tokenize(A__)
												self.assertListEqual(A__   ,A__)

												lowercase							=						tokenizer.encode(A__   ,add_special_tokens=A__)
												lowercase							=						rust_tokenizer.encode(A__   ,add_special_tokens=A__)
												self.assertListEqual(A__   ,A__)

												lowercase							=						self.get_rust_tokenizer()
												lowercase							=						tokenizer.encode(A__)
												lowercase							=						rust_tokenizer.encode(A__)
												self.assertListEqual(A__   ,A__)




							def  A__      (				self   ,A__=1_5):
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
																						lowercase							=						self.rust_tokenizer_class.from_pretrained(A__   ,**A__)

																						# Simple input
																						lowercase							=						'''This is a simple input'''
																						lowercase							=						['''This is a simple input 1''', '''This is a simple input 2''']
																						lowercase							=						('''This is a simple input''', '''This is a pair''')
																						lowercase							=						[
																						    ('''This is a simple input 1''', '''This is a simple input 2'''),
																						    ('''This is a simple pair 1''', '''This is a simple pair 2'''),
																						]

																						# Simple input tests
																						self.assertRaises(A__   ,tokenizer_r.encode   ,A__   ,max_length=A__   ,padding='''max_length''')

																						# Simple input
																						self.assertRaises(A__   ,tokenizer_r.encode_plus   ,A__   ,max_length=A__   ,padding='''max_length''')

																						# Simple input
																						self.assertRaises(
																						    A__   ,tokenizer_r.batch_encode_plus   ,A__   ,max_length=A__   ,padding='''max_length'''   ,)

																						# Pair input
																						self.assertRaises(A__   ,tokenizer_r.encode   ,A__   ,max_length=A__   ,padding='''max_length''')

																						# Pair input
																						self.assertRaises(A__   ,tokenizer_r.encode_plus   ,A__   ,max_length=A__   ,padding='''max_length''')

																						# Pair input
																						self.assertRaises(
																						    A__   ,tokenizer_r.batch_encode_plus   ,A__   ,max_length=A__   ,padding='''max_length'''   ,)




							def  A__      (				self):
												pass




							def  A__      (				self):
												lowercase							=						ReformerTokenizer(A__   ,keep_accents=A__)

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

												self.assertListEqual(
												    tokenizer.convert_tokens_to_ids(A__)   ,[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]   ,)

												lowercase							=						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''',
												        '''.''',
												    ]   ,)
												lowercase							=						tokenizer.convert_tokens_to_ids(A__)
												self.assertListEqual(
												    A__   ,[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]   ,)

												lowercase							=						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  A__      (				self):
												return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment''')




							@slow
							def  A__      (				self):
												lowercase							=						'''Hello World!'''
												lowercase							=						[1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

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




							@slow
							def  A__      (				self):
												lowercase							=						(
												    '''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'''
												)
												lowercase							=						[
												    1_0_8,
												    2_6_5,
												    2_4,
												    1_1_1,
												    4,
												    2_5_8,
												    1_5_6,
												    3_5,
												    2_8,
												    2_7_5,
												    3,
												    2_5_9,
												    2_9_7,
												    2_6_0,
												    8_4,
												    4,
												    3_5,
												    1_1_0,
												    4_4,
												    8,
												    2_5_9,
												    9_1,
												    2_6_8,
												    2_1,
												    1_1,
												    2_0_9,
												    2_7_4,
												    1_0_9,
												    2_6_6,
												    2_7_7,
												    1_1_7,
												    8_6,
												    9_3,
												    3_1_5,
												    2_5_8,
												    2_7_8,
												    2_5_8,
												    2_7_7,
												    2_5_8,
												    0,
												    2_5_8,
												    2_8_8,
												    2_5_8,
												    3_1_9,
												    2_5_8,
												    0,
												    2_5_8,
												    0,
												    2_5_8,
												    0,
												    2_5_8,
												    0,
												    2_5_8,
												    2_8_7,
												    2_5_8,
												    3_1_5,
												    2_5_8,
												    2_8_9,
												    2_5_8,
												    2_7_8,
												    9_9,
												    2_6_9,
												    2_6_6,
												    2_6_2,
												    8,
												    2_5_9,
												    2_4_1,
												    4,
												    2_1_7,
												    2_3_0,
												    2_6_8,
												    2_6_6,
												    5_5,
												    1_6_8,
												    1_0_6,
												    7_5,
												    1_9_3,
												    2_6_6,
												    2_2_3,
												    2_7,
												    4_9,
												    2_6,
												    2_8_2,
												    2_5,
												    2_6_4,
												    2_9_9,
												    1_9,
												    2_6,
												    0,
												    2_5_8,
												    2_7_7,
												    1_1_7,
												    8_6,
												    9_3,
												    1_7_6,
												    1_8_3,
												    2_7_0,
												    1_1,
												    2_6_2,
												    4_2,
												    6_1,
												    2_6_5,
												]

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




							@require_torch
							@slow
							def  A__      (				self):
												import torch

												from transformers import ReformerConfig, ReformerModel

												# Build sequence
												lowercase							=						list(self.big_tokenizer.get_vocab().keys())[:1_0]
												lowercase							=						''' '''.join(A__)
												lowercase							=						self.big_tokenizer.encode_plus(A__   ,return_tensors='''pt''')
												lowercase							=						self.big_tokenizer.batch_encode_plus([sequence, sequence]   ,return_tensors='''pt''')

												lowercase							=						ReformerConfig()
												# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
												lowercase							=						encoded_sequence['''input_ids'''].shape
												lowercase							=						ReformerModel(A__)

												# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
												assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

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





							@slow
							def  A__      (				self):
												# fmt: off
												lowercase							=						{'''input_ids''': [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], '''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]]}  # noqa: E501
												# fmt: on

												# This tokenizer does not know some characters like ")".
												# That is the reason why we use very simple texts here.
												# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
												lowercase							=						[
												    '''This is a very simple sentence.''',
												    '''The quick brown fox jumps over the lazy dog.''',
												]

												self.tokenizer_integration_test_util(
												    expected_encoding=A__   ,model_name='''google/reformer-crime-and-punishment'''   ,revision='''0e6c3decb8211d49bf881013425dc8b0448b3f5a'''   ,padding=A__   ,sequences=A__   ,)






import os
import sys

lowercase__		:Tuple   =    os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


lowercase__		:List[Any]   =    [
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]



@add_start_docstrings(AutoConfig.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoConfig.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoTokenizer.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoTokenizer.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModel.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModel.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForCausalLM.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForCausalLM.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForMaskedLM.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForMaskedLM.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForSequenceClassification.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForSequenceClassification.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)



@add_start_docstrings(AutoModelForQuestionAnswering.__doc__		)
def        UpperCamelCase    (							*lowerCAmelCase__ ,			**lowerCAmelCase__		):
					'''simple docstring'''
					return AutoModelForQuestionAnswering.from_pretrained(*lowerCAmelCase__ ,			**lowerCAmelCase__		)




