
import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer


if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation


lowerCamelCase_						     =					logging.get_logger(__name__)

lowerCamelCase_						     =					{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCamelCase_						     =					{
    '''vocab_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/vocab.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/vocab.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/vocab.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/vocab.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/merges.txt''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/merges.txt''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/merges.txt''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/merges.txt''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/tokenizer.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/tokenizer.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/tokenizer.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/tokenizer.json''',
    },
}

lowerCamelCase_						     =					{
    '''gpt2''': 10_24,
    '''gpt2-medium''': 10_24,
    '''gpt2-large''': 10_24,
    '''gpt2-xl''': 10_24,
    '''distilgpt2''': 10_24,
}




class      __A(    UpperCamelCase__			):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__         =      VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__         =      PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__         =      ['''input_ids''', '''attention_mask''']
  SCREAMING_SNAKE_CASE__         =      GPTaTokenizer







  def __init__(self	,      SCREAMING_SNAKE_CASE_=None	,      SCREAMING_SNAKE_CASE_=None	,      SCREAMING_SNAKE_CASE_=None	,      SCREAMING_SNAKE_CASE_="<|endoftext|>"	,      SCREAMING_SNAKE_CASE_="<|endoftext|>"	,      SCREAMING_SNAKE_CASE_="<|endoftext|>"	,      SCREAMING_SNAKE_CASE_=False	,      **SCREAMING_SNAKE_CASE_	,      ):
       super().__init__(
           UpperCamelCase_	,      UpperCamelCase_	,      tokenizer_file=UpperCamelCase_	,      unk_token=UpperCamelCase_	,      bos_token=UpperCamelCase_	,      eos_token=UpperCamelCase_	,      add_prefix_space=UpperCamelCase_	,      **UpperCamelCase_	,      )

       UpperCamelCase__				=    kwargs.pop("""add_bos_token"""	,      UpperCamelCase_						)

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

       UpperCamelCase__				=    add_prefix_space







  def 	UpperCAmelCase_ (self	,      *SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    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 	UpperCAmelCase_ (self	,      *SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    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 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):
       UpperCamelCase__				=    self._tokenizer.model.save(UpperCamelCase_	,      name=UpperCamelCase_						)
       return tuple(UpperCamelCase_						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    []
       for is_user, text in conversation.iter_texts():
            input_ids.extend(self.encode(UpperCamelCase_	,      add_special_tokens=UpperCamelCase_						) + [self.eos_token_id]						)

       if len(UpperCamelCase_						) > self.model_max_length:
            UpperCamelCase__				=    input_ids[-self.model_max_length :]
       return input_ids







import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowerCamelCase_						     =					logging.get_logger(__name__)




class      __A(    __lowerCamelCase			):

  """simple docstring"""







  def __init__(self	,      *SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						):
       warnings.warn(
           """The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
           """ Please use SegformerImageProcessor instead."""	,      SCREAMING_SNAKE_CASE_	,      )
       super().__init__(*SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						)





