




'''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							:       List[str]						=			logging.get_logger(__name__)




class 			_snake_case		(     lowercase_							):




			def __init__( self    ,							a__							)    ->    Dict:

										'''simple docstring'''




										super().__init__()
										snake_case_      =				nn.ModuleList(a__							)




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__ = None    ,							a__ = None    ,							a__ = None    ,							a__ = None    ,							a__ = False    ,							a__ = True    ,							)    ->    Union[ControlNetOutput, Tuple]:

										'''simple docstring'''




										for i, (image, scale, controlnet) in enumerate(zip(a__    ,							a__    ,							self.nets							)							):
																	snake_case_ ,				snake_case_      =				controlnet(
																	    a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							a__    ,							)

																	# merge samples
																	if i == 0:
																								snake_case_ ,				snake_case_      =				down_samples, mid_sample
																	else:
																								snake_case_      =				[
																								    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        lowerCAmelCase__    ( self    ,							a__    ,							a__ = True    ,							a__ = None    ,							a__ = False    ,							a__ = None    ,							)    ->    List[str]:

										'''simple docstring'''




										snake_case_      =				0
										snake_case_      =				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
																	snake_case_      =				model_path_to_save + F'_{idx}'




			@classmethod
			def        lowerCAmelCase__    ( cls    ,							a__    ,							**a__							)    ->    Union[str, Any]:

										'''simple docstring'''




										snake_case_      =				0
										snake_case_      =				[]

										# 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`, ...
										snake_case_      =				pretrained_model_path
										while os.path.isdir(a__							):
																	snake_case_      =				ControlNetModel.from_pretrained(a__    ,							**a__							)
																	controlnets.append(a__							)

																	idx += 1
																	snake_case_      =				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__							)










'''simple docstring'''





def 					UpperCamelCase_(     snake_case							:	list[int]							,    snake_case							:	int					):

							'''simple docstring'''






							snake_case_      =				len(snake_case					)
							snake_case_      =				[[False] * (required_sum + 1) for _ in range(arr_len + 1					)]

							# for each arr value, a sum of zero(0) can be formed by not taking any element
							# hence True/1
							for i in range(arr_len + 1					):
														snake_case_      =				True

							# sum is not zero and set is empty then false
							for i in range(1							,    required_sum + 1					):
														snake_case_      =				False

							for i in range(1							,    arr_len + 1					):
														for j in range(1							,    required_sum + 1					):
																					if arr[i - 1] > j:
																												snake_case_      =				subset[i - 1][j]
																					if arr[i - 1] <= j:
																												snake_case_      =				subset[i - 1][j] or subset[i - 1][j - arr[i - 1]]

							return subset[arr_len][required_sum]


if __name__ == "__main__":
		import doctest

		doctest.testmod()




