
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

__lowerCAmelCase					:			List[Any]			      =		logging.get_logger(__name__)


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

__lowerCAmelCase					:			Optional[int]			      =		{
    "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"
    },
}

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


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


def     UpperCAmelCase_  (						__lowerCAmelCase	) ->						Dict:
    __lowercase		:			Optional[int]	    =       set()
    __lowercase		:			Tuple	    =       word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)	)
        __lowercase		:			str	    =       char
    return pairs





class 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			int        =    VOCAB_FILES_NAMES
      A__	:			Any        =    PRETRAINED_VOCAB_FILES_MAP
      A__	:			int        =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      A__	:			Dict        =    ['''input_ids''', '''attention_mask''']




      def __init__(      self		:       Tuple				,       _snake_case		:       List[Any]				,       _snake_case		:       Dict				,       _snake_case		:       Union[str, Any]="replace"				,       _snake_case		:       Tuple="<s>"				,       _snake_case		:       Optional[int]="</s>"				,       _snake_case		:       Optional[Any]="</s>"				,       _snake_case		:       str="<s>"				,       _snake_case		:       Dict="<unk>"				,       _snake_case		:       Union[str, Any]="<pad>"				,       _snake_case		:       Union[str, Any]="<mask>"				,       _snake_case		:       Optional[Any]=False				,       **_snake_case		:       int				,       ):
          __lowercase		:			Optional[int]	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else bos_token
          __lowercase		:			Optional[int]	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else eos_token
          __lowercase		:			List[Any]	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else sep_token
          __lowercase		:			Tuple	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else cls_token
          __lowercase		:			Dict	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else unk_token
          __lowercase		:			List[Any]	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else pad_token

          # Mask token behave like a normal word, i.e. include the space before it
          __lowercase		:			Optional[Any]	    =       AddedToken(_snake_case				,       lstrip=_snake_case				,       rstrip=_snake_case				) if isinstance(_snake_case				,       _snake_case				) else mask_token

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

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

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          __lowercase		:			Dict	    =       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 		snake_case_			(      self		:       List[str]				):
          return len(self.encoder				)




      def 		snake_case_			(      self		:       Optional[int]				):
          return dict(self.encoder				,       **self.added_tokens_encoder				)




      def 		snake_case_			(      self		:       str				,       _snake_case		:       int				):
          if token in self.cache:
              return self.cache[token]
          __lowercase		:			Optional[int]	    =       tuple(_snake_case				)
          __lowercase		:			Union[str, Any]	    =       get_pairs(_snake_case				)

          if not pairs:
              return token

          while True:
              __lowercase		:			List[str]	    =       min(_snake_case				,       key=lambda _snake_case				: self.bpe_ranks.get(_snake_case				,       float('''inf'''				)				)				)
              if bigram not in self.bpe_ranks:
                  break
              __lowercase    ,      __lowercase		:			Dict	    =       bigram
              __lowercase		:			Union[str, Any]	    =       []
              __lowercase		:			List[str]	    =       0
              while i < len(_snake_case				):
                  try:
                      __lowercase		:			Any	    =       word.index(_snake_case				,       _snake_case				)
                  except ValueError:
                      new_word.extend(word[i:]				)
                      break
                  else:
                      new_word.extend(word[i:j]				)
                      __lowercase		:			Dict	    =       j

                  if word[i] == first and i < len(_snake_case				) - 1 and word[i + 1] == second:
                      new_word.append(first + second				)
                      i += 2
                  else:
                      new_word.append(word[i]				)
                      i += 1
              __lowercase		:			Any	    =       tuple(_snake_case				)
              __lowercase		:			List[Any]	    =       new_word
              if len(_snake_case				) == 1:
                  break
              else:
                  __lowercase		:			Any	    =       get_pairs(_snake_case				)
          __lowercase		:			str	    =       ''' '''.join(_snake_case				)
          __lowercase		:			Tuple	    =       word
          return word




      def 		snake_case_			(      self		:       List[Any]				,       _snake_case		:       int				):
          __lowercase		:			List[str]	    =       []
          for token in re.findall(self.pat				,       _snake_case				):
              __lowercase		:			Optional[Any]	    =       ''''''.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(_snake_case				).split(''' '''				)				)
          return bpe_tokens




      def 		snake_case_			(      self		:       Dict				,       _snake_case		:       Union[str, Any]				):
          return self.encoder.get(_snake_case				,       self.encoder.get(self.unk_token				)				)




      def 		snake_case_			(      self		:       Dict				,       _snake_case		:       List[Any]				):
          return self.decoder.get(_snake_case				)




      def 		snake_case_			(      self		:       Any				,       _snake_case		:       Any				):
          __lowercase		:			List[str]	    =       ''''''.join(_snake_case				)
          __lowercase		:			List[Any]	    =       bytearray([self.byte_decoder[c] for c in text]				).decode('''utf-8'''				,       errors=self.errors				)
          return text




      def 		snake_case_			(      self		:       int				,       _snake_case		:       str				,       _snake_case		:       Optional[str] = None				):
          if not os.path.isdir(_snake_case				):
              logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
              return
          __lowercase		:			Any	    =       os.path.join(
              _snake_case				,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)
          __lowercase		:			Optional[Any]	    =       os.path.join(
              _snake_case				,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']				)

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

          __lowercase		:			Any	    =       0
          with open(_snake_case				,       '''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 _snake_case				: 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		:			List[Any]	    =       token_index
                  writer.write(''' '''.join(_snake_case				) + '''\n'''				)
                  index += 1

          return vocab_file, merge_file




      def 		snake_case_			(      self		:       str				,       _snake_case		:       List[int]				,       _snake_case		:       Optional[List[int]] = None				,       _snake_case		:       bool = False				):
          if already_has_special_tokens:
              return super().get_special_tokens_mask(
                  token_ids_a=_snake_case				,       token_ids_a=_snake_case				,       already_has_special_tokens=_snake_case				)

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




      def 		snake_case_			(      self		:       Union[str, Any]				,       _snake_case		:       List[int]				,       _snake_case		:       Optional[List[int]] = None				):
          __lowercase		:			int	    =       [self.sep_token_id]
          __lowercase		:			Tuple	    =       [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 		snake_case_			(      self		:       Dict				,       _snake_case		:       Optional[int]				,       _snake_case		:       Union[str, Any]=False				,       **_snake_case		:       int				):
          __lowercase		:			Tuple	    =       kwargs.pop('''add_prefix_space'''				,       self.add_prefix_space				)
          if (is_split_into_words or add_prefix_space) and (len(_snake_case				) > 0 and not text[0].isspace()):
              __lowercase		:			List[Any]	    =       ''' ''' + text
          return (text, kwargs)




      def 		snake_case_			(      self		:       Tuple				,       _snake_case		:       List[int]				,       _snake_case		:       Optional[List[int]] = None				):
          return token_ids_a + [self.eos_token_id]




      def 		snake_case_			(      self		:       int				,       _snake_case		:       "Conversation"				):
          __lowercase		:			Tuple	    =       []
          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(_snake_case				)

          __lowercase		:			Union[str, Any]	    =       '''  '''.join(_snake_case				)
          __lowercase		:			Tuple	    =       self.encode(_snake_case				)
          if len(_snake_case				) > self.model_max_length:
              __lowercase		:			str	    =       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




import warnings
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


__lowerCAmelCase					:			Union[str, Any]			      =		logging.get_logger(__name__)

__lowerCAmelCase					:			Optional[int]			      =		{
    "nvidia/segformer-b0-finetuned-ade-512-512": (
        "https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}


class 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			Dict        =    '''segformer'''




      def __init__(      self		:       Optional[Any]				,       _snake_case		:       List[str]=3				,       _snake_case		:       Union[str, Any]=4				,       _snake_case		:       str=[2, 2, 2, 2]				,       _snake_case		:       Dict=[8, 4, 2, 1]				,       _snake_case		:       List[Any]=[32, 64, 160, 256]				,       _snake_case		:       Dict=[7, 3, 3, 3]				,       _snake_case		:       List[Any]=[4, 2, 2, 2]				,       _snake_case		:       Tuple=[1, 2, 5, 8]				,       _snake_case		:       Optional[Any]=[4, 4, 4, 4]				,       _snake_case		:       Optional[int]="gelu"				,       _snake_case		:       Optional[int]=0.0				,       _snake_case		:       Optional[int]=0.0				,       _snake_case		:       int=0.1				,       _snake_case		:       Any=0.02				,       _snake_case		:       Optional[int]=0.1				,       _snake_case		:       Union[str, Any]=1E-6				,       _snake_case		:       Tuple=256				,       _snake_case		:       str=255				,       **_snake_case		:       Any				,       ):
          super().__init__(**_snake_case				)

          if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
              warnings.warn(
                  '''Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'''
                  ''' removed, as the behaviour will default to that of reshape_last_stage = True.'''				,       _snake_case				,       )

          __lowercase		:			Any	    =       num_channels
          __lowercase		:			Optional[Any]	    =       num_encoder_blocks
          __lowercase		:			List[str]	    =       depths
          __lowercase		:			str	    =       sr_ratios
          __lowercase		:			List[str]	    =       hidden_sizes
          __lowercase		:			List[str]	    =       patch_sizes
          __lowercase		:			Dict	    =       strides
          __lowercase		:			Optional[int]	    =       mlp_ratios
          __lowercase		:			List[str]	    =       num_attention_heads
          __lowercase		:			Optional[int]	    =       hidden_act
          __lowercase		:			List[Any]	    =       hidden_dropout_prob
          __lowercase		:			Optional[Any]	    =       attention_probs_dropout_prob
          __lowercase		:			List[Any]	    =       classifier_dropout_prob
          __lowercase		:			str	    =       initializer_range
          __lowercase		:			Optional[int]	    =       drop_path_rate
          __lowercase		:			List[str]	    =       layer_norm_eps
          __lowercase		:			List[str]	    =       decoder_hidden_size
          __lowercase		:			Union[str, Any]	    =       kwargs.get('''reshape_last_stage'''				,       _snake_case				)
          __lowercase		:			str	    =       semantic_loss_ignore_index






class 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			Union[str, Any]        =    version.parse('''1.11'''      )




      @property
      def 		snake_case_			(      self		:       Dict				):
          return OrderedDict(
              [
                  ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
              ]				)




      @property
      def 		snake_case_			(      self		:       int				):
          return 1E-4




      @property
      def 		snake_case_			(      self		:       List[Any]				):
          return 12


