from dataclasses import dataclass
from typing import Optional, Tuple, Union

import flax
import jax.numpy as jnp
from jax import random

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin


@flax.struct.dataclass
class   lowercase      :
							# setable values
							lowercase__  :    Optional[int]									=							None
							lowercase__  :    Optional[jnp.ndarray]									=							None
							lowercase__  :    Optional[jnp.ndarray]									=							None  # sigma(t_i)




							@classmethod
							def 		__snake_case(  cls				:   int )   ->			List[Any]:



												'''simple docstring'''

												return cls()



@dataclass
class   lowercase      (       a       ):
							lowercase__  :    jnp.ndarray
							lowercase__  :    jnp.ndarray
							lowercase__  :    KarrasVeSchedulerState



class   lowercase      (       a			,    a       ):




							@property
							def 		__snake_case(  self				:   str )   ->			List[str]:



												'''simple docstring'''

												return True




							@register_to_config
							def __init__(  self				:   Union[str, Any]		,							_UpperCamelCase				:   float = 0.0_2		,							_UpperCamelCase				:   float = 100		,							_UpperCamelCase				:   float = 1.0_0_7		,							_UpperCamelCase				:   float = 80		,							_UpperCamelCase				:   float = 0.0_5		,							_UpperCamelCase				:   float = 50		,							)   ->			Union[str, Any]:



												'''simple docstring'''

												pass




							def 		__snake_case(  self				:   int )   ->			Union[str, Any]:



												'''simple docstring'''

												return KarrasVeSchedulerState.create()




							def 		__snake_case(  self				:   Optional[Any]		,							_UpperCamelCase				:   KarrasVeSchedulerState		,							_UpperCamelCase				:   int		,							_UpperCamelCase				:   Tuple = () )   ->			KarrasVeSchedulerState:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =    jnp.arange(0		,							_UpperCamelCase )[::-1].copy()
												SCREAMING_SNAKE_CASE           =    [
												    (
												        self.config.sigma_max**2
												        * (self.config.sigma_min**2 / self.config.sigma_max**2) ** (i / (num_inference_steps - 1))
												    )
												    for i in timesteps
												]

												return state.replace(
												    num_inference_steps=_UpperCamelCase		,							schedule=jnp.array(_UpperCamelCase		,							dtype=jnp.floataa )		,							timesteps=_UpperCamelCase		,							)




							def 		__snake_case(  self				:   Tuple		,							_UpperCamelCase				:   KarrasVeSchedulerState		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   float		,							_UpperCamelCase				:   random.KeyArray		,							)   ->			Tuple[jnp.ndarray, float]:



												'''simple docstring'''

												if self.config.s_min <= sigma <= self.config.s_max:
																	SCREAMING_SNAKE_CASE           =    min(self.config.s_churn / state.num_inference_steps		,							2**0.5 - 1 )
												else:
																	SCREAMING_SNAKE_CASE           =    0

												# sample eps ~ N(0, S_noise^2 * I)
												SCREAMING_SNAKE_CASE           =    random.split(_UpperCamelCase		,							num=1 )
												SCREAMING_SNAKE_CASE           =    self.config.s_noise * random.normal(key=_UpperCamelCase		,							shape=sample.shape )
												SCREAMING_SNAKE_CASE           =    sigma + gamma * sigma
												SCREAMING_SNAKE_CASE           =    sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps)

												return sample_hat, sigma_hat




							def 		__snake_case(  self				:   Optional[Any]		,							_UpperCamelCase				:   KarrasVeSchedulerState		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   float		,							_UpperCamelCase				:   float		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   bool = True		,							)   ->			Union[FlaxKarrasVeOutput, Tuple]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =    sample_hat + sigma_hat * model_output
												SCREAMING_SNAKE_CASE           =    (sample_hat - pred_original_sample) / sigma_hat
												SCREAMING_SNAKE_CASE           =    sample_hat + (sigma_prev - sigma_hat) * derivative

												if not return_dict:
																	return (sample_prev, derivative, state)

												return FlaxKarrasVeOutput(prev_sample=_UpperCamelCase		,							derivative=_UpperCamelCase		,							state=_UpperCamelCase )




							def 		__snake_case(  self				:   List[str]		,							_UpperCamelCase				:   KarrasVeSchedulerState		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   float		,							_UpperCamelCase				:   float		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   jnp.ndarray		,							_UpperCamelCase				:   bool = True		,							)   ->			Union[FlaxKarrasVeOutput, Tuple]:



												'''simple docstring'''

												SCREAMING_SNAKE_CASE           =    sample_prev + sigma_prev * model_output
												SCREAMING_SNAKE_CASE           =    (sample_prev - pred_original_sample) / sigma_prev
												SCREAMING_SNAKE_CASE           =    sample_hat + (sigma_prev - sigma_hat) * (0.5 * derivative + 0.5 * derivative_corr)

												if not return_dict:
																	return (sample_prev, derivative, state)

												return FlaxKarrasVeOutput(prev_sample=_UpperCamelCase		,							derivative=_UpperCamelCase		,							state=_UpperCamelCase )





							def 		__snake_case(  self				:   int		,							_UpperCamelCase				:   KarrasVeSchedulerState		,							_UpperCamelCase				:   Optional[Any]		,							_UpperCamelCase				:   str		,							_UpperCamelCase				:   Dict )   ->			int:



												'''simple docstring'''

												raise NotImplementedError()





def 		__lowerCamelCase							(UpperCAmelCase__       :							str ,	UpperCAmelCase__       :							str = " "					):
					SCREAMING_SNAKE_CASE           =    []

					SCREAMING_SNAKE_CASE           =    0
					for index, char in enumerate(UpperCAmelCase__					):
										if char == separator:
															split_words.append(string[last_index:index]					)
															SCREAMING_SNAKE_CASE           =    index + 1
										elif index + 1 == len(UpperCAmelCase__					):
															split_words.append(string[last_index : index + 1]					)
					return split_words


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

							testmod()




