





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


__A     =    logging.get_logger(__name__)

__A     =    {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

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

__A     =    {
    "gpt-neox-20b": 2048,
}



class        _SCREAMING_SNAKE_CASE						(     __lowerCAmelCase   ):







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

	def __init__(self    :       Any	,			UpperCAmelCase_    :       Optional[int]=None	,			UpperCAmelCase_    :       List[str]=None	,			UpperCAmelCase_    :       List[Any]=None	,			UpperCAmelCase_    :       str="<|endoftext|>"	,			UpperCAmelCase_    :       Union[str, Any]="<|endoftext|>"	,			UpperCAmelCase_    :       Any="<|endoftext|>"	,			UpperCAmelCase_    :       Tuple=False	,			**UpperCAmelCase_    :       Tuple	,			)	->List[str]:



			'''simple docstring'''



			super().__init__(
			    lowerCamelCase__	,			lowerCamelCase__	,			tokenizer_file=lowerCamelCase__	,			unk_token=lowerCamelCase__	,			bos_token=lowerCamelCase__	,			eos_token=lowerCamelCase__	,			add_prefix_space=lowerCamelCase__	,			**lowerCamelCase__	,			)

			lowerCamelCase__:				int        =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
			if pre_tok_state.get("add_prefix_space"	,			lowerCamelCase__) != add_prefix_space:
					lowerCamelCase__:				Any        =getattr(lowerCamelCase__	,			pre_tok_state.pop("type"))
					lowerCamelCase__:				str        =add_prefix_space
					lowerCamelCase__:				str        =pre_tok_class(**lowerCamelCase__)

			lowerCamelCase__:				Dict        =add_prefix_space

	def 							SCREAMING_SNAKE_CASE_ (self    :       List[str]	,			UpperCAmelCase_    :       str	,			UpperCAmelCase_    :       Optional[str] = None)	->Tuple[str]:



			'''simple docstring'''



			lowerCamelCase__:				Tuple        =self._tokenizer.model.save(lowerCamelCase__	,			name=lowerCamelCase__)
			return tuple(lowerCamelCase__)







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



			'''simple docstring'''



			lowerCamelCase__:				List[Any]        =[]
			for is_user, text in conversation.iter_texts():
					input_ids.extend(self.encode(lowerCamelCase__	,			add_special_tokens=lowerCamelCase__) + [self.eos_token_id])

			if len(lowerCamelCase__) > self.model_max_length:
					lowerCamelCase__:				List[Any]        =input_ids[-self.model_max_length :]
			return input_ids








import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__A     =    "src/transformers"


# This is to make sure the transformers module imported is the one in the repo.
__A     =    direct_transformers_import(PATH_TO_TRANSFORMERS)

__A     =    transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
__A     =    re.compile(R"\[(.+?)\]\((https://huggingface\.co/.+?)\)")


__A     =    {
    "DecisionTransformerConfig",
    "EncoderDecoderConfig",
    "MusicgenConfig",
    "RagConfig",
    "SpeechEncoderDecoderConfig",
    "TimmBackboneConfig",
    "VisionEncoderDecoderConfig",
    "VisionTextDualEncoderConfig",
    "LlamaConfig",
}





def 					lowerCAmelCase_			(	__a		)					->		Optional[int]:







  """simple docstring"""





  lowerCamelCase__:				List[Any]        =None

  # source code of `config_class`
  lowerCamelCase__:				List[Any]        =inspect.getsource(__a		)
  lowerCamelCase__:				str        =_re_checkpoint.findall(__a		)

  # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
  # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
  for ckpt_name, ckpt_link in checkpoints:
    # allow the link to end with `/`
    if ckpt_link.endswith("/"		):
      lowerCamelCase__:				str        =ckpt_link[:-1]

    # verify the checkpoint name corresponds to the checkpoint link
    lowerCamelCase__:				Optional[int]        =F"""https://huggingface.co/{ckpt_name}"""
    if ckpt_link == ckpt_link_from_name:
      lowerCamelCase__:				List[Any]        =ckpt_name
      break

  return checkpoint





def 					lowerCAmelCase_			(	)					->		Tuple:







  """simple docstring"""





  lowerCamelCase__:				Union[str, Any]        =[]

  for config_class in list(CONFIG_MAPPING.values()		):
    # Skip deprecated models
    if "models.deprecated" in config_class.__module__:
      continue
    lowerCamelCase__:				List[Any]        =get_checkpoint_from_config_class(__a		)

    lowerCamelCase__:				Tuple        =config_class.__name__
    if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
      configs_without_checkpoint.append(__a		)

  if len(__a		) > 0:
    lowerCamelCase__:				List[str]        ="\n".join(sorted(__a		)		)
    raise ValueError(F"""The following configurations don't contain any valid checkpoint:\n{message}"""		)


if __name__ == "__main__":
     check_config_docstrings_have_checkpoints()

