


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__					,     lowerCamelCase__	:       int					=						controlnet(
                       __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   __lowerCamelCase      ,   )

                   # merge samples
                   if i == 0:
                         lowerCamelCase__					,     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 sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
    print("Googling.....")
    A   :					str	=      "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
    A   :					Optional[int]	=      requests.get(url, headers={"UserAgent": UserAgent().random})
    # res.raise_for_status()
    with open("project1a.html", "wb") as out_file:  # only for knowing the class
        for data in res.iter_content(10000):
            out_file.write(data)
    A   :					int	=      BeautifulSoup(res.text, "html.parser")
    A   :					Any	=      list(soup.select(".eZt8xd"))[:5]

    print(len(links))
    for link in links:
        if link.text == "Maps":
            webbrowser.open(link.get("href"))
        else:
            webbrowser.open(f'https://google.com{link.get("href")}')


