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_  :



	"""simple docstring"""





	UpperCAmelCase_  :					List[Any]   =				None
	UpperCAmelCase_  :					Any   =				None
	UpperCAmelCase_  :					str   =				None  # sigma(t_i)


	@classmethod
	def 			SCREAMING_SNAKE_CASE_				(							cls				)						->Optional[Any]:
								return cls()




@dataclass
class    lowercase_  (  __A						):



	"""simple docstring"""





	UpperCAmelCase_  :					List[Any]   =				42
	UpperCAmelCase_  :					Dict   =				42
	UpperCAmelCase_  :					Any   =				42




class    lowercase_  (  __A      ,     __A						):



	"""simple docstring"""





	@property
	def 			SCREAMING_SNAKE_CASE_				(							self				)						->str:
								return True


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


	def 			SCREAMING_SNAKE_CASE_				(							self				)						->Tuple:
								return KarrasVeSchedulerState.create()


	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE = ()				)						->KarrasVeSchedulerState:
								lowerCAmelCase			=		jnp.arange(0		,			lowerCAmelCase_				)[::-1].copy()
								lowerCAmelCase			=		[
								    (
								        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=lowerCAmelCase_		,			schedule=jnp.array(lowerCAmelCase_		,			dtype=jnp.floataa				)		,			timesteps=lowerCAmelCase_		,			)


	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			)						->Tuple[jnp.ndarray, float]:
								if self.config.s_min <= sigma <= self.config.s_max:
															lowerCAmelCase			=		min(self.config.s_churn / state.num_inference_steps		,			2**0.5 - 1				)
								else:
															lowerCAmelCase			=		0

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

								return sample_hat, sigma_hat


	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE = True		,			)						->Union[FlaxKarrasVeOutput, Tuple]:
								lowerCAmelCase			=		sample_hat + sigma_hat * model_output
								lowerCAmelCase			=		(sample_hat - pred_original_sample) / sigma_hat
								lowerCAmelCase			=		sample_hat + (sigma_prev - sigma_hat) * derivative

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

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


	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE = True		,			)						->Union[FlaxKarrasVeOutput, Tuple]:
								lowerCAmelCase			=		sample_prev + sigma_prev * model_output
								lowerCAmelCase			=		(sample_prev - pred_original_sample) / sigma_prev
								lowerCAmelCase			=		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=lowerCAmelCase_		,			derivative=lowerCAmelCase_		,			state=lowerCAmelCase_				)




	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE				)						->Dict:
								raise NotImplementedError()











"""simple docstring"""
def 				snake_case      (   A__	,A__	,A__	,A__	,A__						):
			if index == number_of_items:
						return 0
			UpperCAmelCase_     : str			     =					0
			UpperCAmelCase_     : Dict			     =					0
			UpperCAmelCase_     : Tuple			     =					knapsack(A__	,A__	,A__	,A__	,index + 1						)
			if weights[index] <= max_weight:
						UpperCAmelCase_     : Union[str, Any]			     =					values[index] + knapsack(
						    A__	,A__	,A__	,max_weight - weights[index]	,index + 1						)
			return max(A__	,A__						)


if __name__ == "__main__":
			import doctest

			doctest.testmod()



