





"""simple docstring"""





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

import flax
import jax.numpy as jnp

from ..utils import BaseOutput


__A											=						"""scheduler_config.json"""






class    _lowerCAmelCase  (	a			):
       """simple docstring"""




       __magic_name__	:str						    =   1
       __magic_name__	:Optional[Any]						    =   2
       __magic_name__	:Optional[Any]						    =   3
       __magic_name__	:List[Any]						    =   4
       __magic_name__	:int						    =   5






@dataclass
class    _lowerCAmelCase  (	a			):
       """simple docstring"""




       __magic_name__	:jnp.ndarray






class    _lowerCAmelCase  :
       """simple docstring"""




       __magic_name__	:Tuple						    =   SCHEDULER_CONFIG_NAME
       __magic_name__	:Dict						    =   ["""dtype"""]
       __magic_name__	:str						    =   []
       __magic_name__	:Tuple						    =   True






       @classmethod
       def 	snake_case		(       cls       ,					__UpperCAmelCase = None       ,					__UpperCAmelCase = None       ,					__UpperCAmelCase=False       ,					**__UpperCAmelCase       ,					):



         '''simple docstring'''

         lowerCAmelCase__				,							lowerCAmelCase__     :List[str]											=				cls.load_config(
             pretrained_model_name_or_path=__UpperCAmelCase       ,					subfolder=__UpperCAmelCase       ,					return_unused_kwargs=__UpperCAmelCase       ,					**__UpperCAmelCase       ,					)
         lowerCAmelCase__				,							lowerCAmelCase__     :Optional[int]											=				cls.from_config(__UpperCAmelCase       ,					return_unused_kwargs=__UpperCAmelCase       ,					**__UpperCAmelCase )

         if hasattr(__UpperCAmelCase       ,					'create_state' ) and getattr(__UpperCAmelCase       ,					'has_state'       ,					__UpperCAmelCase ):
           lowerCAmelCase__     :Optional[Any]											=				scheduler.create_state()

         if return_unused_kwargs:
           return scheduler, state, unused_kwargs

         return scheduler, state






       def 	snake_case		(       self       ,					__UpperCAmelCase       ,					__UpperCAmelCase = False       ,					**__UpperCAmelCase ):



         '''simple docstring'''

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






       @property
       def 	snake_case		(       self ):



         '''simple docstring'''

         return self._get_compatibles()






       @classmethod
       def 	snake_case		(       cls ):



         '''simple docstring'''

         lowerCAmelCase__     :Tuple											=				list(set([cls.__name__] + cls._compatibles ) )
         lowerCAmelCase__     :Any											=				importlib.import_module(__name__.split('.' )[0] )
         lowerCAmelCase__     :Union[str, Any]											=				[
             getattr(__UpperCAmelCase       ,					__UpperCAmelCase ) for c in compatible_classes_str if hasattr(__UpperCAmelCase       ,					__UpperCAmelCase )
         ]
         return compatible_classes






def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->jnp.ndarray:





  """simple docstring"""


  assert len(_SCREAMING_SNAKE_CASE     ) >= x.ndim
  return jnp.broadcast_to(x.reshape(x.shape + (1,) * (len(_SCREAMING_SNAKE_CASE     ) - x.ndim)     )	,  _SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE=0.9_9_9	,  _SCREAMING_SNAKE_CASE=jnp.floataa     )   ->jnp.ndarray:





  """simple docstring"""


  def alpha_bar(_SCREAMING_SNAKE_CASE     ):
    return math.cos((time_step + 0.0_0_8) / 1.0_0_8 * math.pi / 2     ) ** 2

  lowerCAmelCase__     :Tuple											=				[]
  for i in range(_SCREAMING_SNAKE_CASE     ):
    lowerCAmelCase__     :Optional[int]											=				i / num_diffusion_timesteps
    lowerCAmelCase__     :List[Any]											=				(i + 1) / num_diffusion_timesteps
    betas.append(min(1 - alpha_bar(_SCREAMING_SNAKE_CASE     ) / alpha_bar(_SCREAMING_SNAKE_CASE     )	,  _SCREAMING_SNAKE_CASE     )     )
  return jnp.array(_SCREAMING_SNAKE_CASE	,  dtype=_SCREAMING_SNAKE_CASE     )






@flax.struct.dataclass
class    _lowerCAmelCase  :
       """simple docstring"""




       __magic_name__	:jnp.ndarray
       __magic_name__	:jnp.ndarray
       __magic_name__	:jnp.ndarray






       @classmethod
       def 	snake_case		(       cls       ,					__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				scheduler.config

         if config.trained_betas is not None:
           lowerCAmelCase__     :Union[str, Any]											=				jnp.asarray(config.trained_betas       ,					dtype=scheduler.dtype )
         elif config.beta_schedule == "linear":
           lowerCAmelCase__     :Tuple											=				jnp.linspace(config.beta_start       ,					config.beta_end       ,					config.num_train_timesteps       ,					dtype=scheduler.dtype )
         elif config.beta_schedule == "scaled_linear":
           # this schedule is very specific to the latent diffusion model.
           lowerCAmelCase__     :Tuple											=				(
               jnp.linspace(
                   config.beta_start**0.5       ,					config.beta_end**0.5       ,					config.num_train_timesteps       ,					dtype=scheduler.dtype )
               ** 2
           )
         elif config.beta_schedule == "squaredcos_cap_v2":
           # Glide cosine schedule
           lowerCAmelCase__     :str											=				betas_for_alpha_bar(config.num_train_timesteps       ,					dtype=scheduler.dtype )
         else:
           raise NotImplementedError(
               F"beta_schedule {config.beta_schedule} is not implemented for scheduler {scheduler.__class__.__name__}" )

         lowerCAmelCase__     :Optional[Any]											=				1.0 - betas

         lowerCAmelCase__     :Union[str, Any]											=				jnp.cumprod(__UpperCAmelCase       ,					axis=0 )

         return cls(
             alphas=__UpperCAmelCase       ,					betas=__UpperCAmelCase       ,					alphas_cumprod=__UpperCAmelCase       ,					)






def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Dict:





  """simple docstring"""


  lowerCAmelCase__     :List[Any]											=				state.alphas_cumprod

  lowerCAmelCase__     :Union[str, Any]											=				alphas_cumprod[timesteps] ** 0.5
  lowerCAmelCase__     :Dict											=				sqrt_alpha_prod.flatten()
  lowerCAmelCase__     :Any											=				broadcast_to_shape_from_left(_SCREAMING_SNAKE_CASE	,  original_samples.shape     )

  lowerCAmelCase__     :Optional[Any]											=				(1 - alphas_cumprod[timesteps]) ** 0.5
  lowerCAmelCase__     :Optional[int]											=				sqrt_one_minus_alpha_prod.flatten()
  lowerCAmelCase__     :Optional[int]											=				broadcast_to_shape_from_left(_SCREAMING_SNAKE_CASE	,  original_samples.shape     )

  return sqrt_alpha_prod, sqrt_one_minus_alpha_prod
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Optional[int]:





  """simple docstring"""


  lowerCAmelCase__				,							lowerCAmelCase__     :str											=				get_sqrt_alpha_prod(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__     :Optional[int]											=				sqrt_alpha_prod * original_samples + sqrt_one_minus_alpha_prod * noise
  return noisy_samples




def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  lowerCAmelCase__				,							lowerCAmelCase__     :Tuple											=				get_sqrt_alpha_prod(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__     :Tuple											=				sqrt_alpha_prod * noise - sqrt_one_minus_alpha_prod * sample
  return velocity







"""simple docstring"""





def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  lowerCAmelCase__     :List[Any]											=				int(_SCREAMING_SNAKE_CASE     )
  if decimal in (0, 1):  # Exit cases for the recursion
    return str(_SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__				,							lowerCAmelCase__     :int											=				divmod(_SCREAMING_SNAKE_CASE	,  2     )
  return binary_recursive(_SCREAMING_SNAKE_CASE     ) + str(_SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  lowerCAmelCase__     :str											=				str(_SCREAMING_SNAKE_CASE     ).strip()
  if not number:
    raise ValueError('No input value was provided'     )
  lowerCAmelCase__     :Dict											=				'-' if number.startswith('-'     ) else ''
  lowerCAmelCase__     :int											=				number.lstrip('-'     )
  if not number.isnumeric():
    raise ValueError('Input value is not an integer'     )
  return F"{negative}0b{binary_recursive(int(_SCREAMING_SNAKE_CASE     )     )}"


if __name__ == "__main__":
  from doctest import testmod

  testmod()
