
"""simple docstring"""




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


UpperCAmelCase__      :    str    							= logging.get_logger(__name__)

UpperCAmelCase__      :    int    							= {
    'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
        'https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}



class 	lowerCAmelCase_						(a__  ):


				"""simple docstring"""



				__UpperCamelCase      :						Optional[Any]					       =   '''trajectory_transformer'''
				__UpperCamelCase      :						str					       =   ['''past_key_values''']
				__UpperCamelCase      :						Optional[Any]					       =   {
				    '''hidden_size''': '''n_embd''',
				    '''num_attention_heads''': '''n_head''',
				    '''num_hidden_layers''': '''n_layer''',
				}



				def __init__(self   ,       SCREAMING_SNAKE_CASE__=1_00   ,       SCREAMING_SNAKE_CASE__=5   ,       SCREAMING_SNAKE_CASE__=1   ,       SCREAMING_SNAKE_CASE__=1   ,       SCREAMING_SNAKE_CASE__=2_49   ,       SCREAMING_SNAKE_CASE__=6   ,       SCREAMING_SNAKE_CASE__=17   ,       SCREAMING_SNAKE_CASE__=25   ,       SCREAMING_SNAKE_CASE__=4   ,       SCREAMING_SNAKE_CASE__=4   ,       SCREAMING_SNAKE_CASE__=1_28   ,       SCREAMING_SNAKE_CASE__=0.1   ,       SCREAMING_SNAKE_CASE__=0.1   ,       SCREAMING_SNAKE_CASE__=0.1   ,       SCREAMING_SNAKE_CASE__=0.0006   ,       SCREAMING_SNAKE_CASE__=5_12   ,       SCREAMING_SNAKE_CASE__=0.02   ,       SCREAMING_SNAKE_CASE__=1E-12   ,       SCREAMING_SNAKE_CASE__=1   ,       SCREAMING_SNAKE_CASE__=True   ,       SCREAMING_SNAKE_CASE__=1   ,       SCREAMING_SNAKE_CASE__=5_02_56   ,       SCREAMING_SNAKE_CASE__=5_02_56   ,       **SCREAMING_SNAKE_CASE__   ,       )					->		str:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   vocab_size
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   action_weight
											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   reward_weight
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   value_weight
											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   max_position_embeddings
											SCREAMING_SNAKE_CASE__						:       Dict           =   block_size
											SCREAMING_SNAKE_CASE__						:       Tuple           =   action_dim
											SCREAMING_SNAKE_CASE__						:       List[str]           =   observation_dim
											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   transition_dim
											SCREAMING_SNAKE_CASE__						:       List[str]           =   learning_rate
											SCREAMING_SNAKE_CASE__						:       Dict           =   n_layer
											SCREAMING_SNAKE_CASE__						:       Dict           =   n_head
											SCREAMING_SNAKE_CASE__						:       Union[str, Any]           =   n_embd
											SCREAMING_SNAKE_CASE__						:       str           =   embd_pdrop
											SCREAMING_SNAKE_CASE__						:       int           =   attn_pdrop
											SCREAMING_SNAKE_CASE__						:       Any           =   resid_pdrop
											SCREAMING_SNAKE_CASE__						:       Optional[Any]           =   initializer_range
											SCREAMING_SNAKE_CASE__						:       str           =   layer_norm_eps
											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   kaiming_initializer_range
											SCREAMING_SNAKE_CASE__						:       int           =   use_cache
											super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__   ,       bos_token_id=SCREAMING_SNAKE_CASE__   ,       eos_token_id=SCREAMING_SNAKE_CASE__   ,       **SCREAMING_SNAKE_CASE__    )











'''simple docstring'''




import os
from datetime import datetime as dt

from github import Github


__SCREAMING_SNAKE_CASE     :str       =				[
    '''good first issue''',
    '''feature request''',
    '''wip''',
]
def 	UpperCAmelCase_							(					)		->       Optional[Any]:


     '''simple docstring'''



     _UpperCAmelCase     							=   Github(os.environ["GITHUB_TOKEN"]       )
     _UpperCAmelCase     							=   g.get_repo("huggingface/accelerate"       )
     _UpperCAmelCase     							=   repo.get_issues(state="open"       )

     for issue in open_issues:
          _UpperCAmelCase     							=   sorted([comment for comment in issue.get_comments()]			,     key=lambda __lowercase       : i.created_at			,     reverse=__lowercase       )
          _UpperCAmelCase     							=   comments[0] if len(__lowercase       ) > 0 else None
          _UpperCAmelCase     							=   dt.utcnow()
          _UpperCAmelCase     							=   (current_time - issue.updated_at).days
          _UpperCAmelCase     							=   (current_time - issue.created_at).days
          if (
              last_comment is not None
              and last_comment.user.login == "github-actions[bot]"
              and days_since_updated > 7
              and days_since_creation >= 30
              and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()       )
          ):
               # Close issue since it has been 7 days of inactivity since bot mention.
               issue.edit(state="closed"       )
          elif (
              days_since_updated > 23
              and days_since_creation >= 30
              and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()       )
          ):
               # Add stale comment
               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/accelerate/blob/main/CONTRIBUTING.md) "
                   "are likely to be ignored."       )


if __name__ == "__main__":
  main()




