

"""simple docstring"""


class     snake_case	:

				def __init__(	self							:				Optional[Any])->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Any          =			0
						__lowerCAmelCase:       Union[str, Any]          =			0
						__lowerCAmelCase:       Any          =			{}

				def 							lowercase_     (	self							:				int     ,  UpperCamelCase__							:				Optional[int])->   int:



						'''simple docstring'''


						if vertex not in self.adjacency:
								__lowerCAmelCase:       Dict          =			{}
								self.num_vertices += 1

				def 							lowercase_     (	self							:				List[str]     ,  UpperCamelCase__							:				Optional[Any]     ,  UpperCamelCase__							:				Optional[int]     ,  UpperCamelCase__							:				Tuple)->   Tuple:



						'''simple docstring'''


						self.add_vertex(UpperCamelCase__)
						self.add_vertex(UpperCamelCase__)

						if head == tail:
								return

						__lowerCAmelCase:       Dict          =			weight
						__lowerCAmelCase:       Any          =			weight

				def 							lowercase_     (	self							:				Dict)->   Union[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			self.get_edges()
						for edge in edges:
								__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase:       Union[str, Any]          =			edge
								edges.remove((tail, head, weight))
						for i in range(len(UpperCamelCase__)):
								__lowerCAmelCase:       str          =			list(edges[i])

						edges.sort(key=lambda UpperCamelCase__: e[2])
						for i in range(len(UpperCamelCase__) - 1):
								if edges[i][2] >= edges[i + 1][2]:
										__lowerCAmelCase:       List[str]          =			edges[i][2] + 1
						for edge in edges:
								__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase:       Optional[Any]          =			edge
								__lowerCAmelCase:       int          =			weight
								__lowerCAmelCase:       Tuple          =			weight

				def __str__(	self							:				List[str])->   Dict:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			""
						for tail in self.adjacency:
								for head in self.adjacency[tail]:
										__lowerCAmelCase:       List[str]          =			self.adjacency[head][tail]
										string += f"{head} -> {tail} == {weight}\n"
						return string.rstrip("\n")

				def 							lowercase_     (	self							:				List[Any])->   List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			[]
						for tail in self.adjacency:
								for head in self.adjacency[tail]:
										output.append((tail, head, self.adjacency[head][tail]))
						return output

				def 							lowercase_     (	self							:				int)->   int:



						'''simple docstring'''


						return self.adjacency.keys()

				@staticmethod
				def 							lowercase_     (	UpperCamelCase__							:				List[Any]=None     ,  UpperCamelCase__							:				Union[str, Any]=None)->   Union[str, Any]:



						'''simple docstring'''


						__lowerCAmelCase:       Dict          =			Graph()
						if vertices is None:
								__lowerCAmelCase:       Optional[int]          =			[]
						if edges is None:
								__lowerCAmelCase:       List[Any]          =			[]
						for vertex in vertices:
								g.add_vertex(UpperCamelCase__)
						for edge in edges:
								g.add_edge(*UpperCamelCase__)
						return g





				class     snake_case	:

								def __init__(	self							:				int)->   List[Any]:



										'''simple docstring'''


										__lowerCAmelCase:       int          =			{}
										__lowerCAmelCase:       List[Any]          =			{}

								def __len__(	self							:				Optional[int])->   List[Any]:



										'''simple docstring'''


										return len(self.parent)

								def 							lowercase_     (	self							:				List[str]     ,  UpperCamelCase__							:				Tuple)->   Optional[int]:



										'''simple docstring'''


										if item in self.parent:
												return self.find(UpperCamelCase__)

										__lowerCAmelCase:       Dict          =			item
										__lowerCAmelCase:       Any          =			0
										return item

								def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				List[str])->   List[str]:



										'''simple docstring'''


										if item not in self.parent:
												return self.make_set(UpperCamelCase__)
										if item != self.parent[item]:
												__lowerCAmelCase:       Tuple          =			self.find(self.parent[item])
										return self.parent[item]




								def 							lowercase_     (	self							:				Any     ,  UpperCamelCase__							:				Dict     ,  UpperCamelCase__							:				Optional[Any])->   List[Any]:



										'''simple docstring'''


										__lowerCAmelCase:       Optional[Any]          =			self.find(UpperCamelCase__)
										__lowerCAmelCase:       List[Any]          =			self.find(UpperCamelCase__)

										if roota == roota:
												return roota

										if self.rank[roota] > self.rank[roota]:
												__lowerCAmelCase:       Optional[int]          =			roota
												return roota

										if self.rank[roota] < self.rank[roota]:
												__lowerCAmelCase:       Dict          =			roota
												return roota

										if self.rank[roota] == self.rank[roota]:
												self.rank[roota] += 1
												__lowerCAmelCase:       int          =			roota
												return roota
										return None


				@staticmethod
				def 							lowercase_     (	UpperCamelCase__							:				int)->   str:



						'''simple docstring'''


						__lowerCAmelCase:       List[str]          =			graph.num_vertices

						__lowerCAmelCase:       Dict          =			Graph.UnionFind()
						__lowerCAmelCase:       List[str]          =			[]
						while num_components > 1:
								__lowerCAmelCase:       str          =			{}
								for vertex in graph.get_vertices():
										__lowerCAmelCase:       Dict          =			-1

								__lowerCAmelCase:       int          =			graph.get_edges()
								for edge in edges:
										__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase:       Dict          =			edge
										edges.remove((tail, head, weight))
								for edge in edges:
										__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase:       str          =			edge
										__lowerCAmelCase:       Any          =			union_find.find(UpperCamelCase__)
										__lowerCAmelCase:       int          =			union_find.find(UpperCamelCase__)
										if seta != seta:
												if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
														__lowerCAmelCase:       List[Any]          =			[head, tail, weight]

												if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
														__lowerCAmelCase:       str          =			[head, tail, weight]
								for vertex in cheap_edge:
										if cheap_edge[vertex] != -1:
												__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase:       List[Any]          =			cheap_edge[vertex]
												if union_find.find(UpperCamelCase__) != union_find.find(UpperCamelCase__):
														union_find.union(UpperCamelCase__     ,  UpperCamelCase__)
														mst_edges.append(cheap_edge[vertex])
														__lowerCAmelCase:       int          =			num_components - 1
						__lowerCAmelCase:       Tuple          =			Graph.build(edges=UpperCamelCase__)
						return mst





"""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

__A						   =			logging.get_logger(__name__)


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

__A						   =			{
    "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"
    },
}

__A						   =			{"facebook/blenderbot-3B": 128}





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Dict         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      str         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      Optional[Any]         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  ["""input_ids""", """attention_mask"""]
				SCREAMING_SNAKE_CASE_   :      List[Any]         =  BlenderbotTokenizer

				def __init__(	self							:				Any     ,  UpperCamelCase__							:				str=None     ,  UpperCamelCase__							:				Tuple=None     ,  UpperCamelCase__							:				List[Any]=None     ,  UpperCamelCase__							:				Optional[Any]="replace"     ,  UpperCamelCase__							:				int="<s>"     ,  UpperCamelCase__							:				str="</s>"     ,  UpperCamelCase__							:				List[Any]="</s>"     ,  UpperCamelCase__							:				Union[str, Any]="<s>"     ,  UpperCamelCase__							:				List[str]="<unk>"     ,  UpperCamelCase__							:				Dict="<pad>"     ,  UpperCamelCase__							:				List[Any]="<mask>"     ,  UpperCamelCase__							:				Any=False     ,  UpperCamelCase__							:				int=True     ,  **UpperCamelCase__							:				Union[str, Any]     ,  )->   int:



						'''simple docstring'''


						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:       Any          =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
						if pre_tok_state.get("add_prefix_space"     ,  UpperCamelCase__) != add_prefix_space:
								__lowerCAmelCase:       Dict          =			getattr(UpperCamelCase__     ,  pre_tok_state.pop("type"))
								__lowerCAmelCase:       int          =			add_prefix_space
								__lowerCAmelCase:       str          =			pre_tok_class(**UpperCamelCase__)

						__lowerCAmelCase:       List[Any]          =			add_prefix_space

						__lowerCAmelCase:       Union[str, Any]          =			"post_processor"
						__lowerCAmelCase:       Tuple          =			getattr(self.backend_tokenizer     ,  UpperCamelCase__     ,  UpperCamelCase__)
						if tokenizer_component_instance:
								__lowerCAmelCase:       List[Any]          =			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:       str          =			tuple(state["sep"])
								if "cls" in state:
										__lowerCAmelCase:       Any          =			tuple(state["cls"])

								__lowerCAmelCase:       int          =			False

								if state.get("add_prefix_space"     ,  UpperCamelCase__) != add_prefix_space:
										__lowerCAmelCase:       Dict          =			add_prefix_space
										__lowerCAmelCase:       Optional[Any]          =			True

								if state.get("trim_offsets"     ,  UpperCamelCase__) != trim_offsets:
										__lowerCAmelCase:       Dict          =			trim_offsets
										__lowerCAmelCase:       Tuple          =			True

								if changes_to_apply:
										__lowerCAmelCase:       Dict          =			getattr(UpperCamelCase__     ,  state.pop("type"))
										__lowerCAmelCase:       str          =			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 							lowercase_     (	self							:				Optional[Any])->   str:



						'''simple docstring'''


						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 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				Union[str, Any])->   Tuple:



						'''simple docstring'''


						__lowerCAmelCase:       int          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else value
						__lowerCAmelCase:       Any          =			value

				def 							lowercase_     (	self							:				Union[str, Any]     ,  *UpperCamelCase__							:				List[str]     ,  **UpperCamelCase__							:				Optional[int])->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       List[str]          =			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 							lowercase_     (	self							:				Any     ,  *UpperCamelCase__							:				Optional[int]     ,  **UpperCamelCase__							:				int)->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			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 							lowercase_     (	self							:				List[str]     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			self._tokenizer.model.save(UpperCamelCase__     ,  name=UpperCamelCase__)
						return tuple(UpperCamelCase__)

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			[self.sep_token_id]
						__lowerCAmelCase:       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]

				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[Any]:



						'''simple docstring'''


						return token_ids_a + [self.eos_token_id]




				def 							lowercase_     (	self							:				Dict     ,  UpperCamelCase__							:				"Conversation")->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			[]
						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:       Optional[int]          =			"  ".join(UpperCamelCase__)
						__lowerCAmelCase:       Tuple          =			self.encode(UpperCamelCase__)
						if len(UpperCamelCase__) > self.model_max_length:
								__lowerCAmelCase:       int          =			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


