




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


_UpperCAmelCase	:						Optional[Any]			=     logging.get_logger(__name__)




class    __lowerCAmelCase       (							lowerCAmelCase):






       def __init__(   self:					str       ,					_lowerCAmelCase:					Union[List[ControlNetModel], Tuple[ControlNetModel]]				):
         super().__init__()
         lowercase    :int      	=						nn.ModuleList(_lowerCAmelCase				)






       def 					SCREAMING_SNAKE_CASE    (   self:					List[str]       ,					_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       ,					):
         for i, (image, scale, controlnet) in enumerate(zip(_lowerCAmelCase       ,					_lowerCAmelCase       ,					self.nets				)				):
           lowercase	,    lowercase    :List[str]      	=						controlnet(
               _lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					_lowerCAmelCase       ,					)

           # merge samples
           if i == 0:
             lowercase	,    lowercase    :List[str]      	=						down_samples, mid_sample
           else:
             lowercase    :List[str]      	=						[
                 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 					SCREAMING_SNAKE_CASE    (   self:					List[Any]       ,					_lowerCAmelCase:					Union[str, os.PathLike]       ,					_lowerCAmelCase:					bool = True       ,					_lowerCAmelCase:					Callable = None       ,					_lowerCAmelCase:					bool = False       ,					_lowerCAmelCase:					Optional[str] = None       ,					):
         lowercase    :List[str]      	=						0
         lowercase    :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
           lowercase    :Dict      	=						model_path_to_save + F"_{idx}"






       @classmethod
       def 					SCREAMING_SNAKE_CASE    (   cls:					str       ,					_lowerCAmelCase:					Optional[Union[str, os.PathLike]]       ,					**_lowerCAmelCase:					Union[str, Any]				):
         lowercase    :int      	=						0
         lowercase    :Union[str, Any]      	=						[]

         # 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`, ...
         lowercase    :int      	=						pretrained_model_path
         while os.path.isdir(_lowerCAmelCase				):
           lowercase    :Optional[Any]      	=						ControlNetModel.from_pretrained(_lowerCAmelCase       ,					**_lowerCAmelCase				)
           controlnets.append(_lowerCAmelCase				)

           idx += 1
           lowercase    :str      	=						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				)









def       UpperCAmelCase__  (     lowerCamelCase,			lowerCamelCase = False   ):
  if n == 2:
    return True
  if not n % 2 or n < 2:
    return False
  if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
    return False
  if n > 3317044064679887385961981 and not allow_probable:
    raise ValueError(
        "Warning: upper bound of deterministic test is exceeded. "
        "Pass allow_probable=True to allow probabilistic test. "
        "A return value of True indicates a probable prime."   )
  # array bounds provided by analysis
  lowercase    :Optional[Any]      	=						[
      2047,
      1373653,
      25326001,
      3215031751,
      2152302898747,
      3474749660383,
      341550071728321,
      1,
      3825123056546413051,
      1,
      1,
      318665857834031151167461,
      3317044064679887385961981,
  ]

  lowercase    :List[Any]      	=						[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
  for idx, _p in enumerate(lowerCamelCase,			1   ):
    if n < _p:
      # then we have our last prime to check
      lowercase    :Tuple      	=						primes[:idx]
      break
  lowercase	,    lowercase    :str      	=						n - 1, 0
  # break up n -1 into a power of 2 (s) and
  # remaining odd component
  # essentially, solve for d * 2 ** s == n - 1
  while d % 2 == 0:
    d //= 2
    s += 1
  for prime in plist:
    lowercase    :Tuple      	=						False
    for r in range(lowerCamelCase   ):
      lowercase    :Any      	=						pow(lowerCamelCase,			d * 2**r,			lowerCamelCase   )
      # see article for analysis explanation for m
      if (r == 0 and m == 1) or ((m + 1) % n == 0):
        lowercase    :Any      	=						True
        # this loop will not determine compositeness
        break
    if pr:
      continue
    # if pr is False, then the above loop never evaluated to true,
    # and the n MUST be composite
    return False
  return True



def       UpperCAmelCase__  (     ):
  assert not miller_rabin(561   )
  assert miller_rabin(563   )
  # 2047

  assert not miller_rabin(838201   )
  assert miller_rabin(838207   )
  # 1_373_653

  assert not miller_rabin(17316001   )
  assert miller_rabin(17316017   )
  # 25_326_001

  assert not miller_rabin(3078386641   )
  assert miller_rabin(3078386653   )
  # 3_215_031_751

  assert not miller_rabin(1713045574801   )
  assert miller_rabin(1713045574819   )
  # 2_152_302_898_747

  assert not miller_rabin(2779799728307   )
  assert miller_rabin(2779799728327   )
  # 3_474_749_660_383

  assert not miller_rabin(113850023909441   )
  assert miller_rabin(113850023909527   )
  # 341_550_071_728_321

  assert not miller_rabin(1275041018848804351   )
  assert miller_rabin(1275041018848804391   )
  # 3_825_123_056_546_413_051

  assert not miller_rabin(79666464458507787791867   )
  assert miller_rabin(79666464458507787791951   )
  # 318_665_857_834_031_151_167_461

  assert not miller_rabin(552840677446647897660333   )
  assert miller_rabin(552840677446647897660359   )
  # 3_317_044_064_679_887_385_961_981
  # upper limit for probabilistic test


if __name__ == "__main__":
     test_miller_rabin()



