





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


__lowerCamelCase	:					Optional[int]			  =					"""scheduler_config.json"""



class  A__       (	__snake_case      ):
      _UpperCAmelCase     :int						   =       1
      _UpperCAmelCase     :int						   =       2
      _UpperCAmelCase     :str						   =       3
      _UpperCAmelCase     :Optional[Any]						   =       4
      _UpperCAmelCase     :List[Any]						   =       5
      _UpperCAmelCase     :int						   =       6
      _UpperCAmelCase     :Dict						   =       7
      _UpperCAmelCase     :Optional[Any]						   =       8
      _UpperCAmelCase     :int						   =       9
      _UpperCAmelCase     :Union[str, Any]						   =       1_0
      _UpperCAmelCase     :Optional[int]						   =       1_1
      _UpperCAmelCase     :int						   =       1_2
      _UpperCAmelCase     :int						   =       1_3
      _UpperCAmelCase     :str						   =       1_4



@dataclass
class  A__       (	__snake_case      ):
      _UpperCAmelCase     :torch.FloatTensor



class  A__       :
      _UpperCAmelCase     :Union[str, Any]						   =       SCHEDULER_CONFIG_NAME
      _UpperCAmelCase     :Any						   =       []
      _UpperCAmelCase     :Optional[int]						   =       True





      @classmethod
      def 	__UpperCamelCase(			cls	,							A_ = None	,							A_ = None	,							A_=False	,							**A_	,							):
       '''simple docstring'''




       UpperCamelCase     ,   UpperCamelCase     ,   UpperCamelCase     : Any	     =       cls.load_config(
           pretrained_model_name_or_path=A_	,							subfolder=A_	,							return_unused_kwargs=A_	,							return_commit_hash=A_	,							**A_	,							)
       return cls.from_config(A_	,							return_unused_kwargs=A_	,							**A_       )





      def 	__UpperCamelCase(			self	,							A_	,							A_ = False	,							**A_       ):
       '''simple docstring'''




       self.save_config(save_directory=A_	,							push_to_hub=A_	,							**A_       )





      @property
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       return self._get_compatibles()





      @classmethod
      def 	__UpperCamelCase(			cls       ):
       '''simple docstring'''




       UpperCamelCase     : Union[str, Any]	     =       list(set([cls.__name__] + cls._compatibles       )       )
       UpperCamelCase     : Optional[int]	     =       importlib.import_module(__name__.split("."       )[0]       )
       UpperCamelCase     : Dict	     =       [
           getattr(A_	,							A_       ) for c in compatible_classes_str if hasattr(A_	,							A_       )
       ]
       return compatible_classes







from __future__ import annotations



def 		A_    (					_lowerCAmelCase							,       _lowerCAmelCase					)						->			list[str]:
 if partitions <= 0:
  raise ValueError("partitions must be a positive number!"					)
 if partitions > number_of_bytes:
  raise ValueError("partitions can not > number_of_bytes!"					)
 UpperCamelCase     : str	     =       number_of_bytes // partitions
 UpperCamelCase     : List[Any]	     =       []
 for i in range(_lowerCAmelCase					):
  UpperCamelCase     : Optional[Any]	     =       i * bytes_per_partition + 1
  UpperCamelCase     : Any	     =       (
      number_of_bytes if i == partitions - 1 else (i + 1) * bytes_per_partition
  )
  allocation_list.append(F"""{start_bytes}-{end_bytes}"""					)
 return allocation_list


if __name__ == "__main__":
    import doctest

    doctest.testmod()
