



'''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


__lowerCAmelCase									=   logging.get_logger(__name__)

class 	__magic_name__						(    _UpperCamelCase   ):







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







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

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

									return down_block_res_samples, mid_block_res_sample







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

											idx += 1
											_a     :      str        =							model_path_to_save + F"""_{idx}"""







							@classmethod
							def 							__lowercase			(							cls					:       str	,_UpperCAmelCase					:       Optional[Union[str, os.PathLike]]	,**_UpperCAmelCase					:       Optional[Any]		):
									_a     :      Any        =							0
									_a     :      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`, ...
									_a     :      str        =							pretrained_model_path
									while os.path.isdir(_UpperCAmelCase		):
											_a     :      int        =							ControlNetModel.from_pretrained(_UpperCAmelCase	,**_UpperCAmelCase		)
											controlnets.append(_UpperCAmelCase		)

											idx += 1
											_a     :      int        =							pretrained_model_path + F"""_{idx}"""

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

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

									return cls(_UpperCAmelCase		)









'''simple docstring'''

from __future__ import annotations

from collections.abc import Sequence
from typing import Literal



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_  )			->      str | Literal[False]:
		_a     :      Optional[int]        =							list(lowerCAmelCase_  )
		_a     :      Optional[Any]        =							list(lowerCAmelCase_  )
		_a     :      Union[str, Any]        =							0
		for i in range(len(lowerCAmelCase_  )  ):
				if lista[i] != lista[i]:
						count += 1
						_a     :      Optional[int]        =							'_'
		if count > 1:
				return False
		else:
				return "".join(lowerCAmelCase_  )



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      list[str]:
		_a     :      Optional[int]        =							[]
		while True:
				_a     :      Any        =							['$'] * len(lowerCAmelCase_  )
				_a     :      List[str]        =							[]
				for i in range(len(lowerCAmelCase_  )  ):
						for j in range(i + 1						,			len(lowerCAmelCase_  )  ):
								_a     :      Optional[int]        =							compare_string(binary[i]						,			binary[j]  )
								if k is False:
										_a     :      Optional[Any]        =							'*'
										_a     :      Optional[Any]        =							'*'
										temp.append('X'  )
				for i in range(len(lowerCAmelCase_  )  ):
						if checka[i] == "$":
								pi.append(binary[i]  )
				if len(lowerCAmelCase_  ) == 0:
						return pi
				_a     :      Any        =							list(set(lowerCAmelCase_  )  )



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_  )			->      list[str]:
		_a     :      int        =							[]
		for minterm in minterms:
				_a     :      Optional[int]        =							''
				for _ in range(lowerCAmelCase_  ):
						_a     :      Union[str, Any]        =							str(minterm % 2  ) + string
						minterm //= 2
				temp.append(lowerCAmelCase_  )
		return temp



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_  )			->      bool:
		_a     :      int        =							list(lowerCAmelCase_  )
		_a     :      Union[str, Any]        =							list(lowerCAmelCase_  )
		_a     :      str        =							0
		for i in range(len(lowerCAmelCase_  )  ):
				if lista[i] != lista[i]:
						count_n += 1
		return count_n == count



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_  )			->      list[str]:
		_a     :      List[Any]        =							[]
		_a     :      Optional[Any]        =							[0] * len(lowerCAmelCase_  )
		for i in range(len(chart[0]  )  ):
				_a     :      Union[str, Any]        =							0
				_a     :      int        =							-1
				for j in range(len(lowerCAmelCase_  )  ):
						if chart[j][i] == 1:
								count += 1
								_a     :      int        =							j
				if count == 1:
						_a     :      List[Any]        =							1
		for i in range(len(lowerCAmelCase_  )  ):
				if select[i] == 1:
						for j in range(len(chart[0]  )  ):
								if chart[i][j] == 1:
										for k in range(len(lowerCAmelCase_  )  ):
												_a     :      Any        =							0
						temp.append(prime_implicants[i]  )
		while True:
				_a     :      Union[str, Any]        =							0
				_a     :      List[Any]        =							-1
				_a     :      str        =							0
				for i in range(len(lowerCAmelCase_  )  ):
						_a     :      Union[str, Any]        =							chart[i].count(1  )
						if count_n > max_n:
								_a     :      Any        =							count_n
								_a     :      int        =							i

				if max_n == 0:
						return temp

				temp.append(prime_implicants[rem]  )

				for i in range(len(chart[0]  )  ):
						if chart[rem][i] == 1:
								for j in range(len(lowerCAmelCase_  )  ):
										_a     :      List[str]        =							0



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_  )			->      list[list[int]]:
		_a     :      int        =							[[0 for x in range(len(lowerCAmelCase_  )  )] for x in range(len(lowerCAmelCase_  )  )]
		for i in range(len(lowerCAmelCase_  )  ):
				_a     :      str        =							prime_implicants[i].count('_'  )
				for j in range(len(lowerCAmelCase_  )  ):
						if is_for_table(prime_implicants[i]						,			binary[j]						,			lowerCAmelCase_  ):
								_a     :      Optional[Any]        =							1

		return chart



def      __lowerCamelCase     (      )			->      None:
		_a     :      Optional[int]        =							int(input('Enter the no. of variables\n'  )  )
		_a     :      List[Any]        =							[
		    float(lowerCAmelCase_  )
		    for x in input(
		        'Enter the decimal representation of Minterms \'Spaces Separated\'\n'  ).split()
		]
		_a     :      List[str]        =							decimal_to_binary(lowerCAmelCase_						,			lowerCAmelCase_  )

		_a     :      Dict        =							check(lowerCAmelCase_  )
		print('Prime Implicants are:'  )
		print(lowerCAmelCase_  )
		_a     :      List[Any]        =							prime_implicant_chart(lowerCAmelCase_						,			lowerCAmelCase_  )

		_a     :      int        =							selection(lowerCAmelCase_						,			lowerCAmelCase_  )
		print('Essential Prime Implicants are:'  )
		print(lowerCAmelCase_  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()




