


import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union

import torch
from torch import nn

from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging


A   :					Optional[Any]	=      logging.get_logger(__name__)







class     _lowercase				(							lowercase__):


       """simple docstring"""




       def __init__(     self							:    Dict      ,   __lowerCamelCase							:    Union[List[ControlNetModel], Tuple[ControlNetModel]] ):


             '''simple docstring'''



             super().__init__()
             lowerCamelCase__	:       List[str]					=						nn.ModuleList(__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    int      ,   __lowerCamelCase							:    torch.FloatTensor      ,   __lowerCamelCase							:    Union[torch.Tensor, float, int]      ,   __lowerCamelCase							:    torch.Tensor      ,   __lowerCamelCase							:    List[torch.tensor]      ,   __lowerCamelCase							:    List[float]      ,   __lowerCamelCase							:    Optional[torch.Tensor] = None      ,   __lowerCamelCase							:    Optional[torch.Tensor] = None      ,   __lowerCamelCase							:    Optional[torch.Tensor] = None      ,   __lowerCamelCase							:    Optional[Dict[str, Any]] = None      ,   __lowerCamelCase							:    bool = False      ,   __lowerCamelCase							:    bool = True      ,   ):


             '''simple docstring'''



             for i, (image, scale, controlnet) in enumerate(zip(__lowerCamelCase      ,   __lowerCamelCase      ,   self.nets ) ):
                   lowerCamelCase__	:       int					=						controlnet(
                       __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   )

                   # merge samples
                   if i == 0:
                         lowerCamelCase__	:       Union[str, Any]					=						down_samples, mid_sample
                   else:
                         lowerCamelCase__	:       Tuple					=						[
                             samples_prev + samples_curr
                             for samples_prev, samples_curr in zip(__lowerCamelCase      ,   __lowerCamelCase )
                         ]
                         mid_block_res_sample += mid_sample

             return down_block_res_samples, mid_block_res_sample





       def 		lowerCAmelCase  (     self							:    Union[str, Any]      ,   __lowerCamelCase							:    Union[str, os.PathLike]      ,   __lowerCamelCase							:    bool = True      ,   __lowerCamelCase							:    Callable = None      ,   __lowerCamelCase							:    bool = False      ,   __lowerCamelCase							:    Optional[str] = None      ,   ):


             '''simple docstring'''



             lowerCamelCase__	:       Any					=						0
             lowerCamelCase__	:       Tuple					=						save_directory
             for controlnet in self.nets:
                   controlnet.save_pretrained(
                       __lowerCamelCase      ,   is_main_process=__lowerCamelCase      ,   save_function=__lowerCamelCase      ,   safe_serialization=__lowerCamelCase      ,   variant=__lowerCamelCase      ,   )

                   idx += 1
                   lowerCamelCase__	:       Optional[Any]					=						model_path_to_save + f"_{idx}"





       @classmethod
       def 		lowerCAmelCase  (     cls							:    Dict      ,   __lowerCamelCase							:    Optional[Union[str, os.PathLike]]      ,   **__lowerCamelCase							:    Optional[int] ):


             '''simple docstring'''



             lowerCamelCase__	:       Optional[int]					=						0
             lowerCamelCase__	:       List[str]					=						[]

             # load controlnet and append to list until no controlnet directory exists anymore
             # first controlnet has to be saved under `./mydirectory/controlnet` to be compliant with `DiffusionPipeline.from_prertained`
             # second, third, ... controlnets have to be saved under `./mydirectory/controlnet_1`, `./mydirectory/controlnet_2`, ...
             lowerCamelCase__	:       int					=						pretrained_model_path
             while os.path.isdir(__lowerCamelCase ):
                   lowerCamelCase__	:       int					=						ControlNetModel.from_pretrained(__lowerCamelCase      ,   **__lowerCamelCase )
                   controlnets.append(__lowerCamelCase )

                   idx += 1
                   lowerCamelCase__	:       int					=						pretrained_model_path + f"_{idx}"

             logger.info(f"{len(__lowerCamelCase )} controlnets loaded from {pretrained_model_path}." )

             if len(__lowerCamelCase ) == 0:
                   raise ValueError(
                       f"No ControlNets found under {os.path.dirname(__lowerCamelCase )}. Expected at least {pretrained_model_path + '_0'}." )

             return cls(__lowerCamelCase )






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()


