





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer


__UpperCAmelCase       :   Optional[int]				       =							logging.get_logger(__name__)

__UpperCAmelCase       :   List[str]				       =							{'''vocab_file''': '''vocab.txt'''}

__UpperCAmelCase       :   Optional[int]				       =							{
    '''vocab_file''': {
        '''YituTech/conv-bert-base''': '''https://huggingface.co/YituTech/conv-bert-base/resolve/main/vocab.txt''',
        '''YituTech/conv-bert-medium-small''': (
            '''https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/vocab.txt'''
        ),
        '''YituTech/conv-bert-small''': '''https://huggingface.co/YituTech/conv-bert-small/resolve/main/vocab.txt''',
    }
}

__UpperCAmelCase       :   Any				       =							{
    '''YituTech/conv-bert-base''': 512,
    '''YituTech/conv-bert-medium-small''': 512,
    '''YituTech/conv-bert-small''': 512,
}


__UpperCAmelCase       :   Optional[Any]				       =							{
    '''YituTech/conv-bert-base''': {'''do_lower_case''': True},
    '''YituTech/conv-bert-medium-small''': {'''do_lower_case''': True},
    '''YituTech/conv-bert-small''': {'''do_lower_case''': True},
}







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       lowerCAmelCase__      		=     VOCAB_FILES_NAMES
       lowerCAmelCase__      		=     PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__      		=     PRETRAINED_INIT_CONFIGURATION
       lowerCAmelCase__      		=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__      		=     ConvBertTokenizer




       def __init__(  self :    int							,				A :    str=None							,				A :    Optional[int]=None							,				A :    int=True							,				A :    int="[UNK]"							,				A :    Dict="[SEP]"							,				A :    str="[PAD]"							,				A :    Tuple="[CLS]"							,				A :    List[Any]="[MASK]"							,				A :    str=True							,				A :    Union[str, Any]=None							,				**A :    List[str]							,				):
         super().__init__(
             A							,				tokenizer_file=A							,				do_lower_case=A							,				unk_token=A							,				sep_token=A							,				pad_token=A							,				cls_token=A							,				mask_token=A							,				tokenize_chinese_chars=A							,				strip_accents=A							,				**A							,				)

         __snake_case:						Optional[int]   =						json.loads(self.backend_tokenizer.normalizer.__getstate__()		)
         if (
             normalizer_state.get("""lowercase"""							,				A		) != do_lower_case
             or normalizer_state.get("""strip_accents"""							,				A		) != strip_accents
             or normalizer_state.get("""handle_chinese_chars"""							,				A		) != tokenize_chinese_chars
         ):
           __snake_case:						int   =						getattr(A							,				normalizer_state.pop("""type"""		)		)
           __snake_case:						Tuple   =						do_lower_case
           __snake_case:						List[Any]   =						strip_accents
           __snake_case:						List[Any]   =						tokenize_chinese_chars
           __snake_case:						List[Any]   =						normalizer_class(**A		)

         __snake_case:						Dict   =						do_lower_case




       def 							UpperCAmelCase__ (  self :    Tuple							,				A :    str							,				A :    Optional[int]=None		):
         __snake_case:						Optional[int]   =						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

         if token_ids_a:
           output += token_ids_a + [self.sep_token_id]

         return output




       def 							UpperCAmelCase__ (  self :    int							,				A :    List[int]							,				A :    Optional[List[int]] = None		):
         __snake_case:						Any   =						[self.sep_token_id]
         __snake_case:						Any   =						[self.cls_token_id]
         if token_ids_a is None:
           return len(cls + token_ids_a + sep		) * [0]
         return len(cls + token_ids_a + sep		) * [0] + len(token_ids_a + sep		) * [1]






       def 							UpperCAmelCase__ (  self :    List[str]							,				A :    str							,				A :    Optional[str] = None		):
         __snake_case:						Union[str, Any]   =						self._tokenizer.model.save(A							,				name=A		)
         return tuple(A		)








import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
			import torch




@require_torch
@require_optimum
@slow
class    SCREAMING_SNAKE_CASE__     (	unittest.TestCase					):





	'''simple docstring'''



	def  A							(  self	:    Optional[int]	):


				'''simple docstring'''


				_snake_case		=			'hf-internal-testing/tiny-random-t5'
				_snake_case		=			AutoTokenizer.from_pretrained(lowercase	)
				_snake_case		=			AutoModelForSeqaSeqLM.from_pretrained(lowercase	)

				_snake_case		=			tokenizer('This is me'			,  return_tensors='pt'	)

				_snake_case		=			model.to_bettertransformer()

				self.assertTrue(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()	)	)

				_snake_case		=			model.generate(**lowercase	)

				_snake_case		=			model.reverse_bettertransformer()

				self.assertFalse(any('BetterTransformer' in mod.__class__.__name__ for _, mod in model.named_modules()	)	)

				with tempfile.TemporaryDirectory() as tmpdirname:
							model.save_pretrained(lowercase	)

							_snake_case		=			AutoModelForSeqaSeqLM.from_pretrained(lowercase	)

							self.assertFalse(
							    any('BetterTransformer' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()	)	)

							_snake_case		=			model_reloaded.generate(**lowercase	)
							self.assertTrue(torch.allclose(lowercase			,  lowercase	)	)





	def  A							(  self	:    List[Any]	):


				'''simple docstring'''


				_snake_case		=			'hf-internal-testing/tiny-random-t5'
				_snake_case		=			AutoModelForSeqaSeqLM.from_pretrained(lowercase	)

				_snake_case		=			model.to_bettertransformer()

				with tempfile.TemporaryDirectory() as tmpdirname:
							with self.assertRaises(lowercase	):
										model.save_pretrained(lowercase	)

							_snake_case		=			model.reverse_bettertransformer()
							model.save_pretrained(lowercase	)