


"""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__       :							Optional[Any]        =  'scheduler_config.json'




class 				UpperCamelCase_			(				__lowercase):

	"""simple docstring"""





	snake_case__       :						List[Any]					      =    1
	snake_case__       :						Tuple					      =    2
	snake_case__       :						Dict					      =    3
	snake_case__       :						Tuple					      =    4
	snake_case__       :						Tuple					      =    5




@dataclass
class 				UpperCamelCase_			(				__lowercase):

	"""simple docstring"""





	snake_case__       :						jnp.ndarray




class 				UpperCamelCase_			:

	"""simple docstring"""





	snake_case__       :						Tuple					      =    SCHEDULER_CONFIG_NAME
	snake_case__       :						Union[str, Any]					      =    ['''dtype''']
	snake_case__       :						Union[str, Any]					      =    []
	snake_case__       :						Any					      =    True




	@classmethod
	def 						UpperCAmelCase_   (				cls    :       Union[str, Any]    ,    UpperCAmelCase__    :       Dict[str, Any] = None    ,    UpperCAmelCase__    :       Optional[str] = None    ,    UpperCAmelCase__    :       Dict=False    ,    **UpperCAmelCase__    :       Any    ,    ) ->			Optional[int]:
						__SCREAMING_SNAKE_CASE		     =       cls.load_config(
						    pretrained_model_name_or_path=__a    ,    subfolder=__a    ,    return_unused_kwargs=__a    ,    **__a    ,    )
						__SCREAMING_SNAKE_CASE		     =       cls.from_config(__a    ,    return_unused_kwargs=__a    ,    **__a     )

						if hasattr(__a    ,    "create_state"     ) and getattr(__a    ,    "has_state"    ,    __a     ):
											__SCREAMING_SNAKE_CASE		     =       scheduler.create_state()

						if return_unused_kwargs:
											return scheduler, state, unused_kwargs

						return scheduler, state




	def 						UpperCAmelCase_   (				self    :       List[Any]    ,    UpperCAmelCase__    :       Union[str, os.PathLike]    ,    UpperCAmelCase__    :       bool = False    ,    **UpperCAmelCase__    :       int     ) ->			Optional[Any]:
						self.save_config(save_directory=__a    ,    push_to_hub=__a    ,    **__a     )




	@property
	def 						UpperCAmelCase_   (				self    :       str     ) ->			int:
						return self._get_compatibles()




	@classmethod
	def 						UpperCAmelCase_   (				cls    :       int     ) ->			Union[str, Any]:
						__SCREAMING_SNAKE_CASE		     =       list(set([cls.__name__] + cls._compatibles     )     )
						__SCREAMING_SNAKE_CASE		     =       importlib.import_module(__name__.split("."     )[0]     )
						__SCREAMING_SNAKE_CASE		     =       [
						    getattr(__a    ,    __a     ) for c in compatible_classes_str if hasattr(__a    ,    __a     )
						]
						return compatible_classes




def      UpperCAmelCase__ (lowerCAmelCase_						,		lowerCAmelCase_     ):




					'''simple docstring'''


					assert len(UpperCamelCase__     ) >= x.ndim
					return jnp.broadcast_to(x.reshape(x.shape + (1,) * (len(UpperCamelCase__     ) - x.ndim)     )						,		UpperCamelCase__     )




def      UpperCAmelCase__ (lowerCAmelCase_						,		lowerCAmelCase_=0.999						,		lowerCAmelCase_=jnp.floataa     ):




					'''simple docstring'''


					def alpha_bar(lowerCAmelCase_     ):
										return math.cos((time_step + 0.008) / 1.008 * math.pi / 2     ) ** 2

					__SCREAMING_SNAKE_CASE		     =       []
					for i in range(UpperCamelCase__     ):
										__SCREAMING_SNAKE_CASE		     =       i / num_diffusion_timesteps
										__SCREAMING_SNAKE_CASE		     =       (i + 1) / num_diffusion_timesteps
										betas.append(min(1 - alpha_bar(UpperCamelCase__     ) / alpha_bar(UpperCamelCase__     )						,		UpperCamelCase__     )     )
					return jnp.array(UpperCamelCase__						,		dtype=UpperCamelCase__     )




@flax.struct.dataclass
class 				UpperCamelCase_			:

	"""simple docstring"""





	snake_case__       :						jnp.ndarray
	snake_case__       :						jnp.ndarray
	snake_case__       :						jnp.ndarray




	@classmethod
	def 						UpperCAmelCase_   (				cls    :       Optional[Any]    ,    UpperCAmelCase__    :       List[str]     ) ->			Optional[Any]:
						__SCREAMING_SNAKE_CASE		     =       scheduler.config

						if config.trained_betas is not None:
											__SCREAMING_SNAKE_CASE		     =       jnp.asarray(config.trained_betas    ,    dtype=scheduler.dtype     )
						elif config.beta_schedule == "linear":
											__SCREAMING_SNAKE_CASE		     =       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.
											__SCREAMING_SNAKE_CASE		     =       (
											    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
											__SCREAMING_SNAKE_CASE		     =       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__}"""     )

						__SCREAMING_SNAKE_CASE		     =       1.0 - betas

						__SCREAMING_SNAKE_CASE		     =       jnp.cumprod(__a    ,    axis=0     )

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




def      UpperCAmelCase__ (lowerCAmelCase_						,		lowerCAmelCase_						,		lowerCAmelCase_						,		lowerCAmelCase_     ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE		     =       state.alphas_cumprod

					__SCREAMING_SNAKE_CASE		     =       alphas_cumprod[timesteps] ** 0.5
					__SCREAMING_SNAKE_CASE		     =       sqrt_alpha_prod.flatten()
					__SCREAMING_SNAKE_CASE		     =       broadcast_to_shape_from_left(UpperCamelCase__						,		original_samples.shape     )

					__SCREAMING_SNAKE_CASE		     =       (1 - alphas_cumprod[timesteps]) ** 0.5
					__SCREAMING_SNAKE_CASE		     =       sqrt_one_minus_alpha_prod.flatten()
					__SCREAMING_SNAKE_CASE		     =       broadcast_to_shape_from_left(UpperCamelCase__						,		original_samples.shape     )

					return sqrt_alpha_prod, sqrt_one_minus_alpha_prod




def      UpperCAmelCase__ (lowerCAmelCase_						,		lowerCAmelCase_						,		lowerCAmelCase_						,		lowerCAmelCase_     ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE		     =       get_sqrt_alpha_prod(UpperCamelCase__						,		UpperCamelCase__						,		UpperCamelCase__						,		UpperCamelCase__     )
					__SCREAMING_SNAKE_CASE		     =       sqrt_alpha_prod * original_samples + sqrt_one_minus_alpha_prod * noise
					return noisy_samples




def      UpperCAmelCase__ (lowerCAmelCase_						,		lowerCAmelCase_						,		lowerCAmelCase_						,		lowerCAmelCase_     ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE		     =       get_sqrt_alpha_prod(UpperCamelCase__						,		UpperCamelCase__						,		UpperCamelCase__						,		UpperCamelCase__     )
					__SCREAMING_SNAKE_CASE		     =       sqrt_alpha_prod * noise - sqrt_one_minus_alpha_prod * sample
					return velocity




"""simple docstring"""







from __future__ import annotations

import math




class 				UpperCamelCase_			:

	"""simple docstring"""





	def __init__(				self    :       Union[str, Any]    ,    UpperCAmelCase__    :       int     ) ->			None:
						__SCREAMING_SNAKE_CASE		     =       size
						# approximate the overall size of segment tree with given value
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]
						# create array to store lazy update
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]
						__SCREAMING_SNAKE_CASE		     =       [0 for i in range(0    ,    4 * size     )]  # flag for lazy update




	def 						UpperCAmelCase_   (				self    :       str    ,    UpperCAmelCase__    :       int     ) ->			int:
						return idx * 2




	def 						UpperCAmelCase_   (				self    :       Any    ,    UpperCAmelCase__    :       int     ) ->			int:
						return idx * 2 + 1




	def 						UpperCAmelCase_   (				self    :       List[Any]    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       list[int]     ) ->			None:
						if left_element == right_element:
											__SCREAMING_SNAKE_CASE		     =       a[left_element - 1]
						else:
											__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
											self.build(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
											self.build(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
											__SCREAMING_SNAKE_CASE		     =       max(
											    self.segment_tree[self.left(UpperCAmelCase__     )]    ,    self.segment_tree[self.right(UpperCAmelCase__     )]     )




	def 						UpperCAmelCase_   (				self    :       Tuple    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int     ) ->			bool:
						if self.flag[idx] is True:
											__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
											__SCREAMING_SNAKE_CASE		     =       False
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True

						if right_element < a or left_element > b:
											return True
						if left_element >= a and right_element <= b:
											__SCREAMING_SNAKE_CASE		     =       val
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       val
																__SCREAMING_SNAKE_CASE		     =       val
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True
											return True
						__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
						self.update(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						self.update(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       max(
						    self.segment_tree[self.left(UpperCAmelCase__     )]    ,    self.segment_tree[self.right(UpperCAmelCase__     )]     )
						return True




	def 						UpperCAmelCase_   (				self    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int    ,    UpperCAmelCase__    :       int     ) ->			int | float:
						if self.flag[idx] is True:
											__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
											__SCREAMING_SNAKE_CASE		     =       False
											if left_element != right_element:
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       self.lazy[idx]
																__SCREAMING_SNAKE_CASE		     =       True
																__SCREAMING_SNAKE_CASE		     =       True
						if right_element < a or left_element > b:
											return -math.inf
						if left_element >= a and right_element <= b:
											return self.segment_tree[idx]
						__SCREAMING_SNAKE_CASE		     =       (left_element + right_element) // 2
						__SCREAMING_SNAKE_CASE		     =       self.query(self.left(UpperCAmelCase__     )    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						__SCREAMING_SNAKE_CASE		     =       self.query(self.right(UpperCAmelCase__     )    ,    mid + 1    ,    UpperCAmelCase__    ,    UpperCAmelCase__    ,    UpperCAmelCase__     )
						return max(UpperCAmelCase__    ,    UpperCAmelCase__     )




	def __str__(				self    :       int     ) ->			str:
						return str([self.query(1    ,    1    ,    self.size    ,    UpperCAmelCase__    ,    UpperCAmelCase__     ) for i in range(1    ,    self.size + 1     )]     )


if __name__ == "__main__":
		a__       :							Tuple        =  [1, 2, -4, 7, 3, -5, 6, 1_1, -2_0, 9, 1_4, 1_5, 5, 2, -8]
		a__       :							Dict        =  1_5
		a__       :							int        =  SegmentTree(size)
		segt.build(1, 1, size, A)
		print(segt.query(1, 1, size, 4, 6))
		print(segt.query(1, 1, size, 7, 1_1))
		print(segt.query(1, 1, size, 7, 1_2))
		segt.update(1, 1, size, 1, 3, 1_1_1)
		print(segt.query(1, 1, size, 1, 1_5))
		segt.update(1, 1, size, 7, 8, 2_3_5)
		print(segt)
