


import argparse
import json

import numpy
import torch

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging


logging.set_verbosity_info()






def   _lowercase(					__a				:						str    ,     __a				:						int     ):
							# Load checkpoint
							a__      =torch.load(__a    ,     map_location='cpu'     )

							a__      =chkpt['model']

							# We have the base model one level deeper than the original XLM repository
							a__      ={}
							for k, v in state_dict.items():
														if "pred_layer" in k:
																					a__      =v
														else:
																					a__      =v

							a__      =chkpt['params']
							a__      ={n: v for n, v in config.items() if not isinstance(__a    ,     (torch.FloatTensor, numpy.ndarray)     )}

							a__      =chkpt['dico_word2id']
							a__      ={s + '</w>' if s.find('@@'     ) == -1 and i > 13 else s.replace('@@'    ,     ''     ): i for s, i in vocab.items()}

							# Save pytorch-model
							a__      =pytorch_dump_folder_path + '/' + WEIGHTS_NAME
							a__      =pytorch_dump_folder_path + '/' + CONFIG_NAME
							a__      =pytorch_dump_folder_path + '/' + VOCAB_FILES_NAMES['vocab_file']

							print(f"""Save PyTorch model to {pytorch_weights_dump_path}"""     )
							torch.save(__a    ,     __a     )

							print(f"""Save configuration file to {pytorch_config_dump_path}"""     )
							with open(__a    ,     'w'    ,     encoding='utf-8'     ) as f:
														f.write(json.dumps(__a    ,     indent=2     ) + '\n'     )

							print(f"""Save vocab file to {pytorch_config_dump_path}"""     )
							with open(__a    ,     'w'    ,     encoding='utf-8'     ) as f:
														f.write(json.dumps(__a    ,     indent=2     ) + '\n'     )


if __name__ == "__main__":
	_lowerCAmelCase:						str   				=       argparse.ArgumentParser()
	# Required parameters
	parser.add_argument(
	    '--xlm_checkpoint_path', default=None, type=str, required=True, help='Path the official PyTorch dump.'
	)
	parser.add_argument(
	    '--pytorch_dump_folder_path', default=None, type=str, required=True, help='Path to the output PyTorch model.'
	)
	_lowerCAmelCase:						int   				=       parser.parse_args()
	convert_xlm_checkpoint_to_pytorch(args.xlm_checkpoint_path, args.pytorch_dump_folder_path)





import os
from datetime import datetime as dt

from github import Github


lowerCamelCase__							:						int							     =   [
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """enhancement""",
    """new pipeline/model""",
    """new scheduler""",
    """wip""",
]







def SCREAMING_SNAKE_CASE	(			)    ->				Optional[Any]:
  snake_case__						= Github(os.environ['''GITHUB_TOKEN''']				)
  snake_case__						= g.get_repo('''huggingface/diffusers'''				)
  snake_case__						= repo.get_issues(state='''open'''				)

  for issue in open_issues:
    snake_case__						= sorted(issue.get_comments()							,   key=lambda __lowerCAmelCase				: i.created_at							,   reverse=__lowerCAmelCase				)
    snake_case__						= comments[0] if len(__lowerCAmelCase				) > 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()				)
    ):
      # Closes the issue after 7 days of inactivity since the Stalebot notification.
      issue.edit(state='''closed'''				)
    elif (
        "stale" in issue.get_labels()
        and last_comment is not None
        and last_comment.user.login != "github-actions[bot]"
    ):
      # Opens the issue if someone other than Stalebot commented.
      issue.edit(state='''open'''				)
      issue.remove_from_labels('''stale'''				)
    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()				)
    ):
      # Post a Stalebot notification after 23 days of inactivity.
      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/diffusers/blob/main/CONTRIBUTING.md) '''
          '''are likely to be ignored.'''				)
      issue.add_to_labels('''stale'''				)


if __name__ == "__main__":
   main()

