





import argparse
import hashlib  # hashlib is only used inside the Test class
import struct



class 					A__   :





      def __init__( self       ,							A_   ):
       '''simple docstring'''




       UpperCamelCase	:					Any       	=   data
       UpperCamelCase	:					Union[str, Any]       	=   [0x6_7_4_5_2_3_0_1, 0xE_F_C_D_A_B_8_9, 0x9_8_B_A_D_C_F_E, 0x1_0_3_2_5_4_7_6, 0xC_3_D_2_E_1_F_0]





      @staticmethod
      def        __UpperCamelCase( A_       ,							A_   ):
       '''simple docstring'''




       return ((n << b) | (n >> (32 - b))) & 0xF_F_F_F_F_F_F_F





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					int       	=   b"\x80" + b"\x00" * (63 - (len(self.data   ) + 8) % 64)
       UpperCamelCase	:					List[str]       	=   self.data + padding + struct.pack(">Q"       ,							8 * len(self.data   )   )
       return padded_data





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       return [
           self.padded_data[i : i + 64] for i in range(0       ,							len(self.padded_data   )       ,							64   )
       ]





      def        __UpperCamelCase( self       ,							A_   ):
       '''simple docstring'''




       UpperCamelCase	:					Tuple       	=   list(struct.unpack(">16L"       ,							A_   )   ) + [0] * 64
       for i in range(16       ,							80   ):
        UpperCamelCase	:					Optional[int]       	=   self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16])       ,							1   )
       return w





      def        __UpperCamelCase( self   ):
       '''simple docstring'''




       UpperCamelCase	:					Any       	=   self.padding()
       UpperCamelCase	:					List[str]       	=   self.split_blocks()
       for block in self.blocks:
        UpperCamelCase	:					Tuple       	=   self.expand_block(A_   )
        UpperCamelCase	,    UpperCamelCase	,    UpperCamelCase	,    UpperCamelCase	,    UpperCamelCase	:					Union[str, Any]       	=   self.h
        for i in range(0       ,							80   ):
         if 0 <= i < 20:
          UpperCamelCase	:					Any       	=   (b & c) | ((~b) & d)
          UpperCamelCase	:					List[str]       	=   0x5_A_8_2_7_9_9_9
         elif 20 <= i < 40:
          UpperCamelCase	:					Tuple       	=   b ^ c ^ d
          UpperCamelCase	:					Optional[int]       	=   0x6_E_D_9_E_B_A_1
         elif 40 <= i < 60:
          UpperCamelCase	:					Optional[int]       	=   (b & c) | (b & d) | (c & d)
          UpperCamelCase	:					Optional[Any]       	=   0x8_F_1_B_B_C_D_C
         elif 60 <= i < 80:
          UpperCamelCase	:					List[str]       	=   b ^ c ^ d
          UpperCamelCase	:					List[Any]       	=   0xC_A_6_2_C_1_D_6
         UpperCamelCase	,    UpperCamelCase	,    UpperCamelCase	,    UpperCamelCase	,    UpperCamelCase	:					Union[str, Any]       	=   (
             self.rotate(A_       ,							5   ) + f + e + k + expanded_block[i] & 0xF_F_F_F_F_F_F_F,
             a,
             self.rotate(A_       ,							30   ),
             c,
             d,
         )
        UpperCamelCase	:					Tuple       	=   (
            self.h[0] + a & 0xF_F_F_F_F_F_F_F,
            self.h[1] + b & 0xF_F_F_F_F_F_F_F,
            self.h[2] + c & 0xF_F_F_F_F_F_F_F,
            self.h[3] + d & 0xF_F_F_F_F_F_F_F,
            self.h[4] + e & 0xF_F_F_F_F_F_F_F,
        )
       return ("{:08x}" * 5).format(*self.h   )



def 		A_				(     )						-> Any:
 UpperCamelCase	:					List[Any]       	=   b"Test String"
 assert SHAaHash(_lowerCAmelCase     ).final_hash() == hashlib.shaa(_lowerCAmelCase     ).hexdigest()  # noqa: S324



def 		A_				(     )						-> Any:
 UpperCamelCase	:					Tuple       	=   argparse.ArgumentParser(description="Process some strings or files"     )
 parser.add_argument(
     "--string"							,   dest="input_string"							,   default="Hello World!! Welcome to Cryptography"							,   help="Hash the string"							,   )
 parser.add_argument("--file"							,   dest="input_file"							,   help="Hash contents of a file"     )
 UpperCamelCase	:					Tuple       	=   parser.parse_args()
 UpperCamelCase	:					Union[str, Any]       	=   args.input_string
 # In any case hash input should be a bytestring
 if args.input_file:
  with open(args.input_file							,   "rb"     ) as f:
   UpperCamelCase	:					str       	=   f.read()
 else:
  UpperCamelCase	:					int       	=   bytes(_lowerCAmelCase							,   "utf-8"     )
 print(SHAaHash(_lowerCAmelCase     ).final_hash()     )


if __name__ == "__main__":
    main()
    import doctest

    doctest.testmod()

'''simple docstring'''




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


__SCREAMING_SNAKE_CASE       :     str     =  logging.get_logger(__name__)

class 	lowerCamelCase_	(snake_case__    ):
      '''simple docstring'''

      def __init__(       self						:				Optional[int]						,					A						:				Union[List[ControlNetModel], Tuple[ControlNetModel]]       ):
             super().__init__()
             _UpperCAmelCase     :  Optional[int]							      =    nn.ModuleList(A       )




      def      _A	(       self						:				Dict						,					A						:				torch.FloatTensor						,					A						:				Union[torch.Tensor, float, int]						,					A						:				torch.Tensor						,					A						:				List[torch.tensor]						,					A						:				List[float]						,					A						:				Optional[torch.Tensor] = None						,					A						:				Optional[torch.Tensor] = None						,					A						:				Optional[torch.Tensor] = None						,					A						:				Optional[Dict[str, Any]] = None						,					A						:				bool = False						,					A						:				bool = True						,					):
             for i, (image, scale, controlnet) in enumerate(zip(A						,					A						,					self.nets       )       ):
                    _UpperCAmelCase      ,  _UpperCAmelCase     :  str							      =    controlnet(
                        A						,					A						,					A						,					A						,					A						,					A						,					A						,					A						,					A						,					A						,					A						,					)

                    # merge samples
                    if i == 0:
                           _UpperCAmelCase      ,  _UpperCAmelCase     :  List[Any]							      =    down_samples, mid_sample
                    else:
                           _UpperCAmelCase     :  Optional[int]							      =    [
                               samples_prev + samples_curr
                               for samples_prev, samples_curr in zip(A						,					A       )
                           ]
                           mid_block_res_sample += mid_sample

             return down_block_res_samples, mid_block_res_sample




      def      _A	(       self						:				List[str]						,					A						:				Union[str, os.PathLike]						,					A						:				bool = True						,					A						:				Callable = None						,					A						:				bool = False						,					A						:				Optional[str] = None						,					):
             _UpperCAmelCase     :  str							      =    0
             _UpperCAmelCase     :  str							      =    save_directory
             for controlnet in self.nets:
                    controlnet.save_pretrained(
                        A						,					is_main_process=A						,					save_function=A						,					safe_serialization=A						,					variant=A						,					)

                    idx += 1
                    _UpperCAmelCase     :  Tuple							      =    model_path_to_save + F"""_{idx}"""





      @classmethod
      def      _A	(       cls						:				int						,					A						:				Optional[Union[str, os.PathLike]]						,					**A						:				Tuple       ):
             _UpperCAmelCase     :  str							      =    0
             _UpperCAmelCase     :  int							      =    []

             # 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`, ...
             _UpperCAmelCase     :  int							      =    pretrained_model_path
             while os.path.isdir(A       ):
                    _UpperCAmelCase     :  List[str]							      =    ControlNetModel.from_pretrained(A						,					**A       )
                    controlnets.append(A       )

                    idx += 1
                    _UpperCAmelCase     :  Dict							      =    pretrained_model_path + F"""_{idx}"""

             logger.info(F"""{len(A       )} controlnets loaded from {pretrained_model_path}."""       )

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

             return cls(A       )

