
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


lowerCAmelCase__:    Dict      = logging.get_logger(__name__)

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

lowerCAmelCase__:    Dict      = {
    "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"
        )
    },
}

lowerCAmelCase__:    str      = {
    "facebook/blenderbot_small-90M": 512,
}

class 							snake_case_ (				A__    ):
			__lowerCamelCase							:     List[str]						=			VOCAB_FILES_NAMES
			__lowerCamelCase							:     Tuple						=			PRETRAINED_VOCAB_FILES_MAP
			__lowerCamelCase							:     Tuple						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__lowerCamelCase							:     Optional[int]						=			BlenderbotSmallTokenizer





			def __init__(		self      ,						__lowerCAmelCase=None      ,						__lowerCAmelCase=None      ,						__lowerCAmelCase="<|endoftext|>"      ,						__lowerCAmelCase="<|endoftext|>"      ,						__lowerCAmelCase="<|endoftext|>"      ,						__lowerCAmelCase=False      ,						__lowerCAmelCase=True      ,						**__lowerCAmelCase      ,						):
					super().__init__(
					    ByteLevelBPETokenizer(
					        vocab=_UpperCamelCase      ,						merges=_UpperCamelCase      ,						add_prefix_space=_UpperCamelCase      ,						trim_offsets=_UpperCamelCase      ,						)      ,						bos_token=_UpperCamelCase      ,						eos_token=_UpperCamelCase      ,						unk_token=_UpperCamelCase      ,						**_UpperCamelCase      ,						)
					SCREAMING_SNAKE_CASE_					:	Optional[int]		  =			add_prefix_space





			def 						__A						(		self      ,						__lowerCAmelCase      ,						__lowerCAmelCase=None      ):
					SCREAMING_SNAKE_CASE_					:	str		  =			[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      ,						__lowerCAmelCase      ,						__lowerCAmelCase = None      ):
					SCREAMING_SNAKE_CASE_					:	List[str]		  =			[self.sep_token_id]
					SCREAMING_SNAKE_CASE_					:	Union[str, 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]













import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


UpperCAmelCase_           =	logging.get_logger(__name__)




class 			__UpperCamelCase    (							A__    ):





     def __init__(     self				,							*_UpperCamelCase				,							**_UpperCamelCase					):
        warnings.warn(
            '''The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
            ''' use GLPNImageProcessor instead.'''				,							_UpperCamelCase				,							)
        super().__init__(*_UpperCamelCase				,							**_UpperCamelCase					)