



"""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


_lowercase : Any      						=						logging.get_logger(__name__)

class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_   ):


					'''simple docstring'''





					def __init__(       self							:  str,  lowerCamelCase							:  Union[List[ControlNetModel], Tuple[ControlNetModel]]     )->					List[str]:
								super().__init__()
								lowerCamelCase__		:		int			=nn.ModuleList(lowerCamelCase     )



					def 		snake_case       (       self							:  Optional[Any],  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,  )->					Union[ControlNetOutput, Tuple]:
								for i, (image, scale, controlnet) in enumerate(zip(lowerCamelCase,  lowerCamelCase,  self.nets     )     ):
											lowerCamelCase__	,   lowerCamelCase__		:		Union[str, Any]			=controlnet(
											    lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  lowerCamelCase,  )

											# merge samples
											if i == 0:
														lowerCamelCase__	,   lowerCamelCase__		:		Tuple			=down_samples, mid_sample
											else:
														lowerCamelCase__		:		Optional[int]			=[
														    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 		snake_case       (       self							:  str,  lowerCamelCase							:  Union[str, os.PathLike],  lowerCamelCase							:  bool = True,  lowerCamelCase							:  Callable = None,  lowerCamelCase							:  bool = False,  lowerCamelCase							:  Optional[str] = None,  )->					Dict:
								lowerCamelCase__		:		Dict			=0
								lowerCamelCase__		:		Any			=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 		snake_case       (       cls							:  Any,  lowerCamelCase							:  Optional[Union[str, os.PathLike]],  **lowerCamelCase							:  Optional[Any]     )->					Tuple:
								lowerCamelCase__		:		str			=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__		:		List[str]			=pretrained_model_path
								while os.path.isdir(lowerCamelCase     ):
											lowerCamelCase__		:		Tuple			=ControlNetModel.from_pretrained(lowerCamelCase,  **lowerCamelCase     )
											controlnets.append(lowerCamelCase     )

											idx += 1
											lowerCamelCase__		:		Union[str, Any]			=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     )









"""simple docstring"""






def      snake_case__   (		):
			"""simple docstring"""
			return [list(range(1000 - i							,		-1000 - i							,		-1	)	) for i in range(1000	)]


_lowercase : str      						=						generate_large_matrix()
_lowercase : str      						=						(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			assert all(row == sorted(__lowerCamelCase							,		reverse=__lowerCamelCase	) for row in grid	)
			assert all(list(__lowerCamelCase	) == sorted(__lowerCamelCase							,		reverse=__lowerCamelCase	) for col in zip(*__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    list[int]	):
			"""simple docstring"""
			lowerCamelCase__		:		int			=0
			lowerCamelCase__		:		Optional[int]			=len(__lowerCamelCase	) - 1

			# Edge cases such as no values or all numbers are negative.
			if not array or array[0] < 0:
						return 0

			while right + 1 > left:
						lowerCamelCase__		:		List[str]			=(left + right) // 2
						lowerCamelCase__		:		Union[str, Any]			=array[mid]

						# Num must be negative and the index must be greater than or equal to 0.
						if num < 0 and array[mid - 1] >= 0:
									return mid

						if num >= 0:
									lowerCamelCase__		:		Union[str, Any]			=mid + 1
						else:
									lowerCamelCase__		:		Dict			=mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
			return len(__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			lowerCamelCase__		:		Union[str, Any]			=0
			lowerCamelCase__		:		str			=len(grid[0]	)

			for i in range(len(__lowerCamelCase	)	):
						lowerCamelCase__		:		Any			=find_negative_index(grid[i][:bound]	)
						total += bound
			return (len(__lowerCamelCase	) * len(grid[0]	)) - total






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			return len([number for row in grid for number in row if number < 0]	)






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			lowerCamelCase__		:		Tuple			=0
			for row in grid:
						for i, number in enumerate(__lowerCamelCase	):
									if number < 0:
												total += len(__lowerCamelCase	) - i
												break
			return total






def      snake_case__   (		):
			"""simple docstring"""
			from timeit import timeit

			print('''Running benchmarks'''	)
			lowerCamelCase__		:		List[str]			=(
			    '''from __main__ import count_negatives_binary_search, '''
			    '''count_negatives_brute_force, count_negatives_brute_force_with_break, grid'''
			)
			for func in (
			    "count_negatives_binary_search",  # took 0.7727 seconds
			    "count_negatives_brute_force_with_break",  # took 4.6505 seconds
			    "count_negatives_brute_force",  # took 12.8160 seconds
			):
						lowerCamelCase__		:		Union[str, Any]			=timeit(f'''{func}(grid=grid)'''							,		setup=__lowerCamelCase							,		number=500	)
						print(f'''{func}() took {time:0.4f} seconds'''	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()




