


"""simple docstring"""







import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


__lowercase    					=      """scheduler_config.json"""






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase       :							Tuple	=       1
    UpperCAmelCase       :							Tuple	=       2
    UpperCAmelCase       :							List[Any]	=       3
    UpperCAmelCase       :							Optional[Any]	=       4
    UpperCAmelCase       :							Any	=       5
    UpperCAmelCase       :							List[Any]	=       6
    UpperCAmelCase       :							Optional[Any]	=       7
    UpperCAmelCase       :							Optional[int]	=       8
    UpperCAmelCase       :							Optional[int]	=       9
    UpperCAmelCase       :							str	=       1_0
    UpperCAmelCase       :							Dict	=       1_1
    UpperCAmelCase       :							List[str]	=       1_2
    UpperCAmelCase       :							Union[str, Any]	=       1_3
    UpperCAmelCase       :							Tuple	=       1_4






@dataclass
class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase       :							torch.FloatTensor






class 						_A  :







    """simple docstring"""




    UpperCAmelCase       :							Optional[Any]	=       SCHEDULER_CONFIG_NAME
    UpperCAmelCase       :							Dict	=       []
    UpperCAmelCase       :							List[Any]	=       True






    @classmethod
    def 	__snake_case							(					cls				:    Union[str, Any]				, __UpperCAmelCase				:    Dict[str, Any] = None				, __UpperCAmelCase				:    Optional[str] = None				, __UpperCAmelCase				:    Dict=False				, **__UpperCAmelCase				:    Dict				, ):
      a							,		a							,		a						:		Optional[Any]      							=			cls.load_config(
          pretrained_model_name_or_path=__UpperCAmelCase				, subfolder=__UpperCAmelCase				, return_unused_kwargs=__UpperCAmelCase				, return_commit_hash=__UpperCAmelCase				, **__UpperCAmelCase				, )
      return cls.from_config(__UpperCAmelCase				, return_unused_kwargs=__UpperCAmelCase				, **__UpperCAmelCase)






    def 	__snake_case							(					self				:    List[str]				, __UpperCAmelCase				:    Union[str, os.PathLike]				, __UpperCAmelCase				:    bool = False				, **__UpperCAmelCase				:    str):
      self.save_config(save_directory=__UpperCAmelCase				, push_to_hub=__UpperCAmelCase				, **__UpperCAmelCase)






    @property
    def 	__snake_case							(					self				:    Optional[Any]):
      return self._get_compatibles()






    @classmethod
    def 	__snake_case							(					cls				:    Tuple):
      a						:		Dict      							=			list(set([cls.__name__] + cls._compatibles))
      a						:		Any      							=			importlib.import_module(__name__.split(".")[0])
      a						:		Dict      							=			[
          getattr(__UpperCAmelCase				, __UpperCAmelCase) for c in compatible_classes_str if hasattr(__UpperCAmelCase				, __UpperCAmelCase)
      ]
      return compatible_classes











from math import ceil, sqrt



def 			_lowerCAmelCase       (					__lowerCAmelCase = 1000000      )   ->					int:


				"""simple docstring"""

				snake_case__	:      Dict     		=	0

				for outer_width in range(3  ,  (limit // 4) + 2      ):
								if outer_width**2 > limit:
												snake_case__	:      Any     		=	max(ceil(sqrt(outer_width**2 - limit      )      )  ,  1      )
								else:
												snake_case__	:      int     		=	1
								if (outer_width - hole_width_lower_bound) % 2:
												hole_width_lower_bound += 1

								answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

				return answer


if __name__ == "__main__":
				print(f"""{solution() = }""")

