


import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation

A			:						List[str]        =  logging.get_logger(__name__)


A			:						List[str]        =  {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

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






@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 					UpperCamelCase   (      )  ->    Any:
		"""simple docstring"""




		lowercase__	     =						(
		    list(range(ord("""!"""	)       ,       ord("""~"""	) + 1	)	) + list(range(ord("""¡"""	)       ,       ord("""¬"""	) + 1	)	) + list(range(ord("""®"""	)       ,       ord("""ÿ"""	) + 1	)	)
		)
		lowercase__	     =						bs[:]
		lowercase__	     =						0
		for b in range(2**8	):
				if b not in bs:
						bs.append(__magic_name__	)
						cs.append(2**8 + n	)
						n += 1
		lowercase__	     =						[chr(__magic_name__	) for n in cs]
		return dict(zip(__magic_name__       ,       __magic_name__	)	)






def 					UpperCamelCase   (      __magic_name__	:				Any	)  ->    List[str]:
		"""simple docstring"""




		lowercase__	     =						set()
		lowercase__	     =						word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)	)
				lowercase__	     =						char
		return pairs







class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					VOCAB_FILES_NAMES
					A__     =					PRETRAINED_VOCAB_FILES_MAP
					A__     =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A__     =					['''input_ids''', '''attention_mask''']

					def __init__(self       :		List[Any] ,   _UpperCAmelCase       :		Dict ,   _UpperCAmelCase       :		List[str] ,   _UpperCAmelCase       :		str="replace" ,   _UpperCAmelCase       :		int="<s>" ,   _UpperCAmelCase       :		List[Any]="</s>" ,   _UpperCAmelCase       :		List[str]="</s>" ,   _UpperCAmelCase       :		Optional[int]="<s>" ,   _UpperCAmelCase       :		Tuple="<unk>" ,   _UpperCAmelCase       :		str="<pad>" ,   _UpperCAmelCase       :		Optional[Any]="<mask>" ,   _UpperCAmelCase       :		List[Any]=False ,   **_UpperCAmelCase       :		List[Any] ,   )		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else bos_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else eos_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else sep_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else cls_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else unk_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else pad_token

							# Mask token behave like a normal word, i.e. include the space before it
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else mask_token

							super().__init__(
							    errors=_UpperCAmelCase ,   bos_token=_UpperCAmelCase ,   eos_token=_UpperCAmelCase ,   unk_token=_UpperCAmelCase ,   sep_token=_UpperCAmelCase ,   cls_token=_UpperCAmelCase ,   pad_token=_UpperCAmelCase ,   mask_token=_UpperCAmelCase ,   add_prefix_space=_UpperCAmelCase ,   **_UpperCAmelCase ,   )

							with open(_UpperCAmelCase ,   encoding="""utf-8"""						) as vocab_handle:
									lowercase__	     =						json.load(_UpperCAmelCase						)
							lowercase__	     =						{v: k for k, v in self.encoder.items()}
							lowercase__	     =						errors  # how to handle errors in decoding
							lowercase__	     =						bytes_to_unicode()
							lowercase__	     =						{v: k for k, v in self.byte_encoder.items()}
							with open(_UpperCAmelCase ,   encoding="""utf-8"""						) as merges_handle:
									lowercase__	     =						merges_handle.read().split("""\n"""						)[1:-1]
							lowercase__	     =						[tuple(merge.split()						) for merge in bpe_merges]
							lowercase__	     =						dict(zip(_UpperCAmelCase ,   range(len(_UpperCAmelCase						)						)						)						)
							lowercase__	     =						{}
							lowercase__	     =						add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							lowercase__	     =						re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""						)

					@property
					# Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
					def     lowerCamelCase__	(self       :		Tuple						)		->  Tuple:




							"""simple docstring"""


							return len(self.encoder						)

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




							"""simple docstring"""


							return dict(self.encoder ,   **self.added_tokens_encoder						)

					def     lowerCamelCase__	(self       :		List[str] ,   _UpperCAmelCase       :		Union[str, Any]						)		->  List[Any]:




							"""simple docstring"""


							if token in self.cache:
									return self.cache[token]
							lowercase__	     =						tuple(_UpperCAmelCase						)
							lowercase__	     =						get_pairs(_UpperCAmelCase						)

							if not pairs:
									return token

							while True:
									lowercase__	     =						min(_UpperCAmelCase ,   key=lambda _UpperCAmelCase						: self.bpe_ranks.get(_UpperCAmelCase ,   float("""inf"""						)						)						)
									if bigram not in self.bpe_ranks:
											break
									lowercase__     ,      lowercase__	     =						bigram
									lowercase__	     =						[]
									lowercase__	     =						0
									while i < len(_UpperCAmelCase						):
											try:
													lowercase__	     =						word.index(_UpperCAmelCase ,   _UpperCAmelCase						)
											except ValueError:
													new_word.extend(word[i:]						)
													break
											else:
													new_word.extend(word[i:j]						)
													lowercase__	     =						j

											if word[i] == first and i < len(_UpperCAmelCase						) - 1 and word[i + 1] == second:
													new_word.append(first + second						)
													i += 2
											else:
													new_word.append(word[i]						)
													i += 1
									lowercase__	     =						tuple(_UpperCAmelCase						)
									lowercase__	     =						new_word
									if len(_UpperCAmelCase						) == 1:
											break
									else:
											lowercase__	     =						get_pairs(_UpperCAmelCase						)
							lowercase__	     =						""" """.join(_UpperCAmelCase						)
							lowercase__	     =						word
							return word

					def     lowerCamelCase__	(self       :		Optional[int] ,   _UpperCAmelCase       :		List[str]						)		->  int:




							"""simple docstring"""


							lowercase__	     =						[]
							for token in re.findall(self.pat ,   _UpperCAmelCase						):
									lowercase__	     =						"""""".join(
									    self.byte_encoder[b] for b in token.encode("""utf-8"""						)						)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
									bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_UpperCAmelCase						).split(""" """						)						)
							return bpe_tokens

					def     lowerCamelCase__	(self       :		Optional[int] ,   _UpperCAmelCase       :		Optional[int]						)		->  int:




							"""simple docstring"""


							return self.encoder.get(_UpperCAmelCase ,   self.encoder.get(self.unk_token						)						)

					def     lowerCamelCase__	(self       :		Optional[Any] ,   _UpperCAmelCase       :		List[Any]						)		->  int:




							"""simple docstring"""


							return self.decoder.get(_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		str ,   _UpperCAmelCase       :		Any						)		->  Optional[Any]:




							"""simple docstring"""


							lowercase__	     =						"""""".join(_UpperCAmelCase						)
							lowercase__	     =						bytearray([self.byte_decoder[c] for c in text]						).decode("""utf-8""" ,   errors=self.errors						)
							return text

					def     lowerCamelCase__	(self       :		Dict ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		Optional[str] = None						)		->  Tuple[str]:




							"""simple docstring"""


							if not os.path.isdir(_UpperCAmelCase						):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
									return
							lowercase__	     =						os.path.join(
							    _UpperCAmelCase ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]						)
							lowercase__	     =						os.path.join(
							    _UpperCAmelCase ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]						)

							with open(_UpperCAmelCase ,   """w""" ,   encoding="""utf-8"""						) as f:
									f.write(json.dumps(self.encoder ,   indent=2 ,   sort_keys=_UpperCAmelCase ,   ensure_ascii=_UpperCAmelCase						) + """\n"""						)

							lowercase__	     =						0
							with open(_UpperCAmelCase ,   """w""" ,   encoding="""utf-8"""						) as writer:
									writer.write("""#version: 0.2\n"""						)
									for bpe_tokens, token_index in sorted(self.bpe_ranks.items() ,   key=lambda _UpperCAmelCase						: kv[1]						):
											if index != token_index:
													logger.warning(
													    f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
													    """ Please check that the tokenizer is not corrupted!"""						)
													lowercase__	     =						token_index
											writer.write(""" """.join(_UpperCAmelCase						) + """\n"""						)
											index += 1

							return vocab_file, merge_file

					def     lowerCamelCase__	(self       :		Tuple ,   _UpperCAmelCase       :		List[int] ,   _UpperCAmelCase       :		Optional[List[int]] = None ,   _UpperCAmelCase       :		bool = False						)		->  List[int]:




							"""simple docstring"""


							if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=_UpperCAmelCase ,   token_ids_a=_UpperCAmelCase ,   already_has_special_tokens=_UpperCAmelCase						)

							if token_ids_a is None:
									return [1] + ([0] * len(_UpperCAmelCase						)) + [1]
							return [1] + ([0] * len(_UpperCAmelCase						)) + [1, 1] + ([0] * len(_UpperCAmelCase						)) + [1]

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




							"""simple docstring"""


							lowercase__	     =						[self.sep_token_id]
							lowercase__	     =						[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     lowerCamelCase__	(self       :		Optional[int] ,   _UpperCAmelCase       :		List[str] ,   _UpperCAmelCase       :		Any=False ,   **_UpperCAmelCase       :		Tuple						)		->  Any:




							"""simple docstring"""


							lowercase__	     =						kwargs.pop("""add_prefix_space""" ,   self.add_prefix_space						)
							if (is_split_into_words or add_prefix_space) and (len(_UpperCAmelCase						) > 0 and not text[0].isspace()):
									lowercase__	     =						""" """ + text
							return (text, kwargs)

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




							"""simple docstring"""


							return token_ids_a + [self.eos_token_id]


					def     lowerCamelCase__	(self       :		Optional[Any] ,   _UpperCAmelCase       :		"Conversation"						)		->  List[int]:




							"""simple docstring"""


							lowercase__	     =						[]
							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						)

							lowercase__	     =						"""  """.join(_UpperCAmelCase						)
							lowercase__	     =						self.encode(_UpperCAmelCase						)
							if len(_UpperCAmelCase						) > self.model_max_length:
									lowercase__	     =						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'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__SCREAMING_SNAKE_CASE					:				List[str]									=		{
    '''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE					:				Optional[Any]									=		[
							    '''GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''GraphormerForGraphClassification''',
							    '''GraphormerModel''',
							    '''GraphormerPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_graphormer import (
														    GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
														    GraphormerForGraphClassification,
														    GraphormerModel,
														    GraphormerPreTrainedModel,
														)


else:
							import sys

							__SCREAMING_SNAKE_CASE					:				Optional[int]									=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





