


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


A   :					Any	=      logging.get_logger(__name__)

A   :					Optional[int]	=      {
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}







class     _lowercase				(							_SCREAMING_SNAKE_CASE):


       """simple docstring"""




       A__      		=    "swinv2"

       A__      		=    {
           "num_attention_heads": "num_heads",
           "num_hidden_layers": "num_layers",
       }





       def __init__(     self							:    int      ,   __lowerCamelCase							:    Any=224      ,   __lowerCamelCase							:    str=4      ,   __lowerCamelCase							:    Any=3      ,   __lowerCamelCase							:    Dict=96      ,   __lowerCamelCase							:    Optional[Any]=[2, 2, 6, 2]      ,   __lowerCamelCase							:    int=[3, 6, 12, 24]      ,   __lowerCamelCase							:    Optional[int]=7      ,   __lowerCamelCase							:    str=4.0      ,   __lowerCamelCase							:    Dict=True      ,   __lowerCamelCase							:    Optional[int]=0.0      ,   __lowerCamelCase							:    Union[str, Any]=0.0      ,   __lowerCamelCase							:    List[Any]=0.1      ,   __lowerCamelCase							:    List[str]="gelu"      ,   __lowerCamelCase							:    Union[str, Any]=False      ,   __lowerCamelCase							:    List[str]=0.0_2      ,   __lowerCamelCase							:    Dict=1E-5      ,   __lowerCamelCase							:    List[Any]=32      ,   **__lowerCamelCase							:    Dict      ,   ):


             '''simple docstring'''



             super().__init__(**A_ )

             lowerCamelCase__	:       List[str]					=						image_size
             lowerCamelCase__	:       Optional[Any]					=						patch_size
             lowerCamelCase__	:       List[Any]					=						num_channels
             lowerCamelCase__	:       Optional[Any]					=						embed_dim
             lowerCamelCase__	:       Any					=						depths
             lowerCamelCase__	:       str					=						len(A_ )
             lowerCamelCase__	:       str					=						num_heads
             lowerCamelCase__	:       Dict					=						window_size
             lowerCamelCase__	:       Tuple					=						mlp_ratio
             lowerCamelCase__	:       List[str]					=						qkv_bias
             lowerCamelCase__	:       Dict					=						hidden_dropout_prob
             lowerCamelCase__	:       Optional[int]					=						attention_probs_dropout_prob
             lowerCamelCase__	:       Tuple					=						drop_path_rate
             lowerCamelCase__	:       List[str]					=						hidden_act
             lowerCamelCase__	:       Union[str, Any]					=						use_absolute_embeddings
             lowerCamelCase__	:       List[str]					=						layer_norm_eps
             lowerCamelCase__	:       Union[str, Any]					=						initializer_range
             lowerCamelCase__	:       Tuple					=						encoder_stride
             # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
             # this indicates the channel dimension after the last stage of the model
             lowerCamelCase__	:       List[Any]					=						int(embed_dim * 2 ** (len(A_ ) - 1) )
             lowerCamelCase__	:       str					=						(0, 0, 0, 0)






import os
from datetime import datetime as dt

from github import Github


A   :					Union[str, Any]	=      [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "enhancement",
    "new pipeline/model",
    "new scheduler",
    "wip",
]

def    lowercase_	(	):

      """simple docstring"""




      lowerCamelCase__	:       Optional[int]					=						Github(os.environ["GITHUB_TOKEN"]		)
      lowerCamelCase__	:       str					=						g.get_repo("huggingface/diffusers"		)
      lowerCamelCase__	:       Optional[int]					=						repo.get_issues(state="open"		)

      for issue in open_issues:
            lowerCamelCase__	:       str					=						sorted(issue.get_comments()					,      key=lambda _A		: i.created_at					,      reverse=_A		)
            lowerCamelCase__	:       str					=						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()		)
            ):
                  # 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()


