





from datetime import datetime as dt
import os

from github import Github


__UpperCAmelCase	:       int    	=							[
    "good first issue",
    "good second issue",
    "good difficult issue",
    "feature request",
    "new model",
    "wip",
]







def       A__							(   )       ->   str:
  __snake_case:						Dict			  =						Github(os.environ["""GITHUB_TOKEN"""])
  __snake_case:						Any			  =						g.get_repo("""huggingface/transformers""")
  __snake_case:						Any			  =						repo.get_issues(state="""open""")

  for issue in open_issues:
    __snake_case:						Union[str, Any]			  =						sorted([comment for comment in issue.get_comments()] , key=lambda SCREAMING_SNAKE_CASE__: i.created_at , reverse=A__)
    __snake_case:						Union[str, Any]			  =						comments[0] if len(A__) > 0 else None
    if (
        last_comment is not None
        and last_comment.user.login == "github-actions[bot]"
        and (dt.utcnow() - issue.updated_at).days > 7
        and (dt.utcnow() - issue.created_at).days >= 30
        and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels())
    ):
      # print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
      issue.edit(state="""closed""")
    elif (
        (dt.utcnow() - issue.updated_at).days > 23
        and (dt.utcnow() - issue.created_at).days >= 30
        and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels())
    ):
      # print(f"Would add stale comment to {issue.number}")
      issue.create_comment(
          """This issue has been automatically marked as stale because it has not had """
          """recent activity. If you think this still needs to be addressed """
          """please comment on this thread.\n\nPlease note that issues that do not follow the """
          """[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) """
          """are likely to be ignored.""")


if __name__ == "__main__":
      main()













from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase	:       str    	=							logging.get_logger(__name__)

__UpperCAmelCase	:       int    	=							{
    "RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json",
    "RWKV/rwkv-4-430m-pile": "https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json",
    "RWKV/rwkv-4-1b5-pile": "https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json",
    "RWKV/rwkv-4-3b-pile": "https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json",
    "RWKV/rwkv-4-7b-pile": "https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json",
    "RWKV/rwkv-4-14b-pile": "https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json",
    "RWKV/rwkv-raven-1b5": "https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json",
    "RWKV/rwkv-raven-3b": "https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json",
    "RWKV/rwkv-raven-7b": "https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json",
    "RWKV/rwkv-raven-14b": "https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json",
}







class    __snake_case	(							__lowerCamelCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					"""rwkv"""
       lowerCAmelCase__						=					{"""max_position_embeddings""": """context_length"""}




       def __init__(  self			:   Dict							,    A			:   List[Any]=50_277							,    A			:   List[Any]=1_024							,    A			:   Union[str, Any]=4_096							,    A			:   Tuple=32							,    A			:   List[Any]=None							,    A			:   Tuple=None							,    A			:   Tuple=1E-5							,    A			:   int=0							,    A			:   Optional[int]=0							,    A			:   Dict=6							,    A			:   Dict=False							,    A			:   int=True							,    **A			:   List[Any]							,    ):
         __snake_case:						Tuple			  =						vocab_size
         __snake_case:						Any			  =						context_length
         __snake_case:						Dict			  =						hidden_size
         __snake_case:						Dict			  =						num_hidden_layers
         __snake_case:						Union[str, Any]			  =						attention_hidden_size if attention_hidden_size is not None else hidden_size
         __snake_case:						str			  =						intermediate_size if intermediate_size is not None else 4 * hidden_size
         __snake_case:						Any			  =						layer_norm_epsilon
         __snake_case:						int			  =						rescale_every
         __snake_case:						str			  =						use_cache

         __snake_case:						Dict			  =						bos_token_id
         __snake_case:						Union[str, Any]			  =						eos_token_id

         super().__init__(
             tie_word_embeddings=A							,    bos_token_id=A							,    eos_token_id=A							,    **A		)






