
'''simple docstring'''



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

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


UpperCamelCase__      :		str       							=  logging.get_logger(__name__)

UpperCamelCase__      :		List[Any]       							=  {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

UpperCamelCase__      :		Dict       							=  {
    "tokenizer_file": {
        "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json",
    },
}

UpperCamelCase__      :		List[Any]       							=  {
    "gpt-neox-20b": 2_048,
}

class    _a				(_lowerCamelCase):





       """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']






       def __init__(							self       ,							A__=None       ,							A__=None       ,							A__=None       ,							A__="<|endoftext|>"       ,							A__="<|endoftext|>"       ,							A__="<|endoftext|>"       ,							A__=False       ,							**A__       ,							)    ->			List[Any]:
          super().__init__(
              A__       ,							A__       ,							tokenizer_file=A__       ,							unk_token=A__       ,							bos_token=A__       ,							eos_token=A__       ,							add_prefix_space=A__       ,							**A__       ,							)

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

          _SCREAMING_SNAKE_CASE            =				add_prefix_space






       def        UpperCamelCase				(							self       ,							A__       ,							A__ = None      )    ->			Tuple[str]:
          _SCREAMING_SNAKE_CASE            =				self._tokenizer.model.save(A__       ,							name=A__      )
          return tuple(A__      )






       def        UpperCamelCase				(							self       ,							A__      )    ->			List[int]:
          _SCREAMING_SNAKE_CASE            =				[]
          for is_user, text in conversation.iter_texts():
             input_ids.extend(self.encode(A__       ,							add_special_tokens=A__      ) + [self.eos_token_id]      )

          if len(A__      ) > self.model_max_length:
             _SCREAMING_SNAKE_CASE            =				input_ids[-self.model_max_length :]
          return input_ids








'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available


UpperCamelCase__      :		int       							=  {"tokenization_herbert": ["HerbertTokenizer"]}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase__      :		Tuple       							=  ["HerbertTokenizerFast"]


if TYPE_CHECKING:
     from .tokenization_herbert import HerbertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_herbert_fast import HerbertTokenizerFast

else:
     import sys

     UpperCamelCase__      :		Tuple       							=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






