

"""simple docstring"""


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						       =      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}






@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def    a__   (   )     ->     Dict:
		__lowerCAmelCase:	str   				=      (
		    list(range(ord("!"			) ,			ord("~"			) + 1			)			) + list(range(ord("¡"			) ,			ord("¬"			) + 1			)			) + list(range(ord("®"			) ,			ord("ÿ"			) + 1			)			)
		)
		__lowerCAmelCase:	Dict   				=      bs[:]
		__lowerCAmelCase:	Dict   				=      0
		for b in range(2**8			):
				if b not in bs:
						bs.append(snake_case__			)
						cs.append(2**8 + n			)
						n += 1
		__lowerCAmelCase:	List[str]   				=      [chr(snake_case__			) for n in cs]
		return dict(zip(snake_case__ ,			snake_case__			)			)






def    a__   (   __SCREAMING_SNAKE_CASE			)     ->     str:
		__lowerCAmelCase:	Dict   				=      set()
		__lowerCAmelCase:	Union[str, Any]   				=      word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)			)
				__lowerCAmelCase:	Optional[Any]   				=      char
		return pairs





class    snake_case     (    __lowerCAmelCase  ):
				SCREAMING_SNAKE_CASE_       :				List[str]       				=  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_       :				List[str]       				=  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_       :				List[Any]       				=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_       :				Optional[int]       				=  ['''input_ids''', '''attention_mask''']

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



						'''simple docstring'''


						__lowerCAmelCase:	Any   				=      AddedToken(lowerCAmelCase_					,  lstrip=lowerCAmelCase_					,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_					,  lowerCAmelCase_) else bos_token
						__lowerCAmelCase:	Optional[Any]   				=      AddedToken(lowerCAmelCase_					,  lstrip=lowerCAmelCase_					,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_					,  lowerCAmelCase_) else eos_token
						__lowerCAmelCase:	Any   				=      AddedToken(lowerCAmelCase_					,  lstrip=lowerCAmelCase_					,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_					,  lowerCAmelCase_) else sep_token
						__lowerCAmelCase:	List[str]   				=      AddedToken(lowerCAmelCase_					,  lstrip=lowerCAmelCase_					,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_					,  lowerCAmelCase_) else cls_token
						__lowerCAmelCase:	Optional[int]   				=      AddedToken(lowerCAmelCase_					,  lstrip=lowerCAmelCase_					,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_					,  lowerCAmelCase_) else unk_token
						__lowerCAmelCase:	List[str]   				=      AddedToken(lowerCAmelCase_					,  lstrip=lowerCAmelCase_					,  rstrip=lowerCAmelCase_) if isinstance(lowerCAmelCase_					,  lowerCAmelCase_) else pad_token

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

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

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

						# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
						__lowerCAmelCase:	List[Any]   				=      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 							lowercase_					(     self							:    Dict)->       str:



						'''simple docstring'''


						return len(self.encoder)

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



						'''simple docstring'''


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

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



						'''simple docstring'''


						if token in self.cache:
								return self.cache[token]
						__lowerCAmelCase:	Optional[int]   				=      tuple(lowerCAmelCase_)
						__lowerCAmelCase:	Any   				=      get_pairs(lowerCAmelCase_)

						if not pairs:
								return token

						while True:
								__lowerCAmelCase:	int   				=      min(lowerCAmelCase_					,  key=lambda UpperCamelCase__: self.bpe_ranks.get(lowerCAmelCase_					,  float("inf")))
								if bigram not in self.bpe_ranks:
										break
								__lowerCAmelCase				,			__lowerCAmelCase:	Optional[int]   				=      bigram
								__lowerCAmelCase:	Union[str, Any]   				=      []
								__lowerCAmelCase:	Tuple   				=      0
								while i < len(lowerCAmelCase_):
										try:
												__lowerCAmelCase:	Optional[Any]   				=      word.index(lowerCAmelCase_					,  lowerCAmelCase_)
										except ValueError:
												new_word.extend(word[i:])
												break
										else:
												new_word.extend(word[i:j])
												__lowerCAmelCase:	Tuple   				=      j

										if word[i] == first and i < len(lowerCAmelCase_) - 1 and word[i + 1] == second:
												new_word.append(first + second)
												i += 2
										else:
												new_word.append(word[i])
												i += 1
								__lowerCAmelCase:	Tuple   				=      tuple(lowerCAmelCase_)
								__lowerCAmelCase:	Union[str, Any]   				=      new_word
								if len(lowerCAmelCase_) == 1:
										break
								else:
										__lowerCAmelCase:	Optional[Any]   				=      get_pairs(lowerCAmelCase_)
						__lowerCAmelCase:	Optional[Any]   				=      " ".join(lowerCAmelCase_)
						__lowerCAmelCase:	Optional[int]   				=      word
						return word

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



						'''simple docstring'''


						__lowerCAmelCase:	Tuple   				=      []
						for token in re.findall(self.pat					,  lowerCAmelCase_):
								__lowerCAmelCase:	Tuple   				=      "".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(lowerCAmelCase_).split(" "))
						return bpe_tokens

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



						'''simple docstring'''


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

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



						'''simple docstring'''


						return self.decoder.get(lowerCAmelCase_)

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



						'''simple docstring'''


						__lowerCAmelCase:	Any   				=      "".join(lowerCAmelCase_)
						__lowerCAmelCase:	List[Any]   				=      bytearray([self.byte_decoder[c] for c in text]).decode("utf-8"					,  errors=self.errors)
						return text

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



						'''simple docstring'''


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

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

						__lowerCAmelCase:	List[str]   				=      0
						with open(lowerCAmelCase_					,  "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!")
												__lowerCAmelCase:	Optional[int]   				=      token_index
										writer.write(" ".join(lowerCAmelCase_) + "\n")
										index += 1

						return vocab_file, merge_file

				def 							lowercase_					(     self							:    Dict					,  UpperCamelCase__							:    int					,  UpperCamelCase__							:    List[Any] = None					,  UpperCamelCase__							:    Tuple = False)->       List[int]:



						'''simple docstring'''


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

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

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



						'''simple docstring'''


						__lowerCAmelCase:	List[str]   				=      [self.sep_token_id]
						__lowerCAmelCase:	int   				=      [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							:    Dict					,  UpperCamelCase__							:    Dict					,  UpperCamelCase__							:    int=False					,  **UpperCamelCase__							:    str)->       List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:	Dict   				=      kwargs.pop("add_prefix_space"					,  self.add_prefix_space)
						if (is_split_into_words or add_prefix_space) and (len(lowerCAmelCase_) > 0 and not text[0].isspace()):
								__lowerCAmelCase:	List[str]   				=      " " + text
						return (text, kwargs)

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



						'''simple docstring'''


						return token_ids_a + [self.eos_token_id]




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



						'''simple docstring'''


						__lowerCAmelCase:	Dict   				=      []
						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(lowerCAmelCase_)

						__lowerCAmelCase:	Optional[int]   				=      "  ".join(lowerCAmelCase_)
						__lowerCAmelCase:	List[Any]   				=      self.encode(lowerCAmelCase_)
						if len(lowerCAmelCase_) > self.model_max_length:
								__lowerCAmelCase:	Dict   				=      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 collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__A						       =      logging.get_logger(__name__)

__A						       =      {
    "facebook/data2vec-vision-base-ft": (
        "https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json"
    ),
}





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Union[str, Any]       				=  """data2vec-vision"""

				def __init__(     self							:    Optional[int]					,  UpperCamelCase__							:    str=7_6_8					,  UpperCamelCase__							:    Any=1_2					,  UpperCamelCase__							:    str=1_2					,  UpperCamelCase__							:    Optional[Any]=3_0_7_2					,  UpperCamelCase__							:    Union[str, Any]="gelu"					,  UpperCamelCase__							:    List[Any]=0.0					,  UpperCamelCase__							:    Dict=0.0					,  UpperCamelCase__							:    Union[str, Any]=0.02					,  UpperCamelCase__							:    str=1e-12					,  UpperCamelCase__							:    Dict=2_2_4					,  UpperCamelCase__							:    List[Any]=1_6					,  UpperCamelCase__							:    Optional[Any]=3					,  UpperCamelCase__							:    List[str]=False					,  UpperCamelCase__							:    List[Any]=False					,  UpperCamelCase__							:    str=False					,  UpperCamelCase__							:    List[str]=False					,  UpperCamelCase__							:    int=0.1					,  UpperCamelCase__							:    List[Any]=0.1					,  UpperCamelCase__							:    Optional[Any]=True					,  UpperCamelCase__							:    List[Any]=[3, 5, 7, 1_1]					,  UpperCamelCase__							:    List[str]=[1, 2, 3, 6]					,  UpperCamelCase__							:    Union[str, Any]=True					,  UpperCamelCase__							:    Any=0.4					,  UpperCamelCase__							:    Union[str, Any]=2_5_6					,  UpperCamelCase__							:    List[Any]=1					,  UpperCamelCase__							:    str=False					,  UpperCamelCase__							:    Optional[int]=2_5_5					,  **UpperCamelCase__							:    Dict					,  )->       List[str]:



						'''simple docstring'''


						super().__init__(**UpperCamelCase__)

						__lowerCAmelCase:	List[str]   				=      hidden_size
						__lowerCAmelCase:	Union[str, Any]   				=      num_hidden_layers
						__lowerCAmelCase:	Dict   				=      num_attention_heads
						__lowerCAmelCase:	Optional[int]   				=      intermediate_size
						__lowerCAmelCase:	int   				=      hidden_act
						__lowerCAmelCase:	Union[str, Any]   				=      hidden_dropout_prob
						__lowerCAmelCase:	Any   				=      attention_probs_dropout_prob
						__lowerCAmelCase:	Dict   				=      initializer_range
						__lowerCAmelCase:	Any   				=      layer_norm_eps

						__lowerCAmelCase:	Union[str, Any]   				=      image_size
						__lowerCAmelCase:	Tuple   				=      patch_size
						__lowerCAmelCase:	List[str]   				=      num_channels
						__lowerCAmelCase:	Optional[Any]   				=      use_mask_token
						__lowerCAmelCase:	str   				=      use_absolute_position_embeddings
						__lowerCAmelCase:	Optional[int]   				=      use_relative_position_bias
						__lowerCAmelCase:	str   				=      use_shared_relative_position_bias
						__lowerCAmelCase:	Union[str, Any]   				=      layer_scale_init_value
						__lowerCAmelCase:	Any   				=      drop_path_rate
						__lowerCAmelCase:	Dict   				=      use_mean_pooling
						# decode head attributes (semantic segmentation)
						__lowerCAmelCase:	int   				=      out_indices
						__lowerCAmelCase:	Any   				=      pool_scales
						# auxiliary head attributes (semantic segmentation)
						__lowerCAmelCase:	List[Any]   				=      use_auxiliary_head
						__lowerCAmelCase:	int   				=      auxiliary_loss_weight
						__lowerCAmelCase:	Dict   				=      auxiliary_channels
						__lowerCAmelCase:	Any   				=      auxiliary_num_convs
						__lowerCAmelCase:	Any   				=      auxiliary_concat_input
						__lowerCAmelCase:	Any   				=      semantic_loss_ignore_index





class    snake_case     (    __snake_case  ):
				SCREAMING_SNAKE_CASE_       :				Dict       				=  version.parse("""1.11"""  )

				@property
				def 							lowercase_					(     self							:    Optional[Any])->       Mapping[str, Mapping[int, str]]:



						'''simple docstring'''


						return OrderedDict(
						    [
						        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
						    ])




				@property
				def 							lowercase_					(     self							:    Any)->       float:



						'''simple docstring'''


						return 1e-4


