



"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot import BlenderbotTokenizer


if TYPE_CHECKING:
			from transformers.pipelines.conversational import Conversation

__SCREAMING_SNAKE_CASE  :						int    							=						logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE  :						Tuple    							=						{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__SCREAMING_SNAKE_CASE  :						Tuple    							=						{
    '''vocab_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'''},
    '''merges_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'''},
    '''tokenizer_config_file''': {
        '''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'''
    },
}

__SCREAMING_SNAKE_CASE  :						List[Any]    							=						{'''facebook/blenderbot-3B''': 1_2_8}


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					lowercase__   :       Union[str, Any]										= VOCAB_FILES_NAMES
					lowercase__   :       Any										= PRETRAINED_VOCAB_FILES_MAP
					lowercase__   :       Optional[Any]										= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__   :       Optional[Any]										= ['input_ids', 'attention_mask']
					lowercase__   :       List[Any]										= BlenderbotTokenizer

					def __init__(    self				,       lowerCamelCase__=None				,       lowerCamelCase__=None				,       lowerCamelCase__=None				,       lowerCamelCase__="replace"				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="<unk>"				,       lowerCamelCase__="<pad>"				,       lowerCamelCase__="<mask>"				,       lowerCamelCase__=False				,       lowerCamelCase__=True				,       **lowerCamelCase__				,       ):
									super().__init__(
									    __UpperCamelCase				,       __UpperCamelCase				,       tokenizer_file=__UpperCamelCase				,       errors=__UpperCamelCase				,       bos_token=__UpperCamelCase				,       eos_token=__UpperCamelCase				,       sep_token=__UpperCamelCase				,       cls_token=__UpperCamelCase				,       unk_token=__UpperCamelCase				,       pad_token=__UpperCamelCase				,       mask_token=__UpperCamelCase				,       add_prefix_space=__UpperCamelCase				,       trim_offsets=__UpperCamelCase				,       **__UpperCamelCase				,       )

									_lowerCamelCase        =				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
									if pre_tok_state.get('''add_prefix_space'''				,       __UpperCamelCase   ) != add_prefix_space:
													_lowerCamelCase        =				getattr(__UpperCamelCase				,       pre_tok_state.pop('''type'''   )   )
													_lowerCamelCase        =				add_prefix_space
													_lowerCamelCase        =				pre_tok_class(**__UpperCamelCase   )

									_lowerCamelCase        =				add_prefix_space

									_lowerCamelCase        =				'''post_processor'''
									_lowerCamelCase        =				getattr(self.backend_tokenizer				,       __UpperCamelCase				,       __UpperCamelCase   )
									if tokenizer_component_instance:
													_lowerCamelCase        =				json.loads(tokenizer_component_instance.__getstate__()   )

													# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
													if "sep" in state:
																	_lowerCamelCase        =				tuple(state['''sep''']   )
													if "cls" in state:
																	_lowerCamelCase        =				tuple(state['''cls''']   )

													_lowerCamelCase        =				False

													if state.get('''add_prefix_space'''				,       __UpperCamelCase   ) != add_prefix_space:
																	_lowerCamelCase        =				add_prefix_space
																	_lowerCamelCase        =				True

													if state.get('''trim_offsets'''				,       __UpperCamelCase   ) != trim_offsets:
																	_lowerCamelCase        =				trim_offsets
																	_lowerCamelCase        =				True

													if changes_to_apply:
																	_lowerCamelCase        =				getattr(__UpperCamelCase				,       state.pop('''type'''   )   )
																	_lowerCamelCase        =				component_class(**__UpperCamelCase   )
																	setattr(self.backend_tokenizer				,       __UpperCamelCase				,       __UpperCamelCase   )

					@property
					# Copied from transformers.models.roberta.tokenization_roberta_fast.RobertaTokenizerFast.mask_token with Roberta->Blenderbot, RoBERTa->Blenderbot
					def 			snake_case__      (    self   ):
									if self._mask_token is None:
													if self.verbose:
																	logger.error('''Using mask_token, but it is not set yet.'''   )
													return None
									return str(self._mask_token   )

					@mask_token.setter
					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				AddedToken(__UpperCamelCase				,       lstrip=__UpperCamelCase				,       rstrip=__UpperCamelCase   ) if isinstance(__UpperCamelCase				,       __UpperCamelCase   ) else value
									_lowerCamelCase        =				value

					def 			snake_case__      (    self				,       *lowerCamelCase__				,       **lowerCamelCase__   ):
									_lowerCamelCase        =				kwargs.get('''is_split_into_words'''				,       __UpperCamelCase   )
									assert self.add_prefix_space or not is_split_into_words, (
									    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
									    "to use it with pretokenized inputs."
									)

									return super()._batch_encode_plus(*__UpperCamelCase				,       **__UpperCamelCase   )

					def 			snake_case__      (    self				,       *lowerCamelCase__				,       **lowerCamelCase__   ):
									_lowerCamelCase        =				kwargs.get('''is_split_into_words'''				,       __UpperCamelCase   )

									assert self.add_prefix_space or not is_split_into_words, (
									    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
									    "to use it with pretokenized inputs."
									)

									return super()._encode_plus(*__UpperCamelCase				,       **__UpperCamelCase   )

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				self._tokenizer.model.save(__UpperCamelCase				,       name=__UpperCamelCase   )
									return tuple(__UpperCamelCase   )

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				[self.sep_token_id]
									_lowerCamelCase        =				[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 + sep + token_ids_a + sep   ) * [0]

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									return token_ids_a + [self.eos_token_id]





					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				[]
									for is_user, text in conversation.iter_texts():
													if is_user:
																	# We need to space prefix as it's being done within blenderbot
																	inputs.append(''' ''' + text   )
													else:
																	# Generated responses should contain them already.
																	inputs.append(__UpperCamelCase   )

									_lowerCamelCase        =				'''  '''.join(__UpperCamelCase   )
									_lowerCamelCase        =				self.encode(__UpperCamelCase   )
									if len(__UpperCamelCase   ) > self.model_max_length:
													_lowerCamelCase        =				input_ids[-self.model_max_length :]
													logger.warning(F"""Trimmed input from conversation as it was longer than {self.model_max_length} tokens."""   )
									return input_ids





"""simple docstring"""
import warnings

from .generation import TFGenerationMixin


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					warnings.warn(
					    'Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '
					    'be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead.',				A__,				)
