
from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


UpperCamelCase_						:     Optional[Any]	       =							logging.get_logger(__name__)

UpperCamelCase_						:     Dict	       =							{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

UpperCamelCase_						:     Any	       =							{
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

UpperCamelCase_						:     Tuple	       =							{
    """facebook/blenderbot_small-90M""": 512,
}




class   __lowercase						(						__snake_case       ):
	_A       =   VOCAB_FILES_NAMES
	_A       =   PRETRAINED_VOCAB_FILES_MAP
	_A       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A       =   BlenderbotSmallTokenizer






	def __init__(self				: Optional[Any]      ,	snake_case				: Tuple=None      ,	snake_case				: Optional[Any]=None      ,	snake_case				: Union[str, Any]="<|endoftext|>"      ,	snake_case				: Any="<|endoftext|>"      ,	snake_case				: Dict="<|endoftext|>"      ,	snake_case				: Any=False      ,	snake_case				: Optional[int]=True      ,	**snake_case				: int      ,	) ->			Tuple:
							super().__init__(
							    ByteLevelBPETokenizer(
							        vocab=snake_case      ,	merges=snake_case      ,	add_prefix_space=snake_case      ,	trim_offsets=snake_case      ,	)      ,	bos_token=snake_case      ,	eos_token=snake_case      ,	unk_token=snake_case      ,	**snake_case      ,	)
							_lowercase       :	Tuple           =   add_prefix_space






	def       _a(self				: str      ,	snake_case				: Any      ,	snake_case				: str=None    ) ->			Dict:
							_lowercase       :	Optional[Any]           =   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
							if token_ids_a is None:
													return output

							return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






	def       _a(self				: Union[str, Any]      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None    ) ->			List[int]:
							_lowercase       :	Optional[int]           =   [self.sep_token_id]
							_lowercase       :	Optional[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 + sep + token_ids_a + sep    ) * [0]






from ...configuration_utils import PretrainedConfig
from ...utils import logging


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




class   __lowercase						(						__snake_case       ):
	_A       =   "timm_backbone"






	def __init__(self				: Any      ,	snake_case				: List[Any]=None      ,	snake_case				: int=3      ,	snake_case				: Dict=True      ,	snake_case				: Union[str, Any]=True      ,	snake_case				: Any=None      ,	**snake_case				: int      ,	) ->			Optional[int]:
							super().__init__(**snake_case    )
							_lowercase       :	Dict           =   backbone
							_lowercase       :	Optional[Any]           =   num_channels
							_lowercase       :	Union[str, Any]           =   features_only
							_lowercase       :	Tuple           =   use_pretrained_backbone
							_lowercase       :	List[str]           =   True
							_lowercase       :	Tuple           =   out_indices if out_indices is not None else (-1,)




