




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 (       __magic_name__ ):

			"""simple docstring"""







			snake_case_   		=       1
			snake_case_   		=       2
			snake_case_   		=       3
			snake_case_   		=       4
			snake_case_   		=       5







@dataclass
class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







			snake_case_   		=       42







class     __lowerCAmelCase :

			"""simple docstring"""







			snake_case_   		=       SCHEDULER_CONFIG_NAME
			snake_case_   		=       ['''dtype''']
			snake_case_   		=       []
			snake_case_   		=       True


			@classmethod
			def       lowercase_    (      cls			,						lowerCamelCase__ = None			,						lowerCamelCase__ = None			,						lowerCamelCase__=False			,						**lowerCamelCase__			,						)    ->      Dict:



							'''simple docstring'''
							__lowerCamelCase       ,						__lowerCamelCase		       =    cls.load_config(
							    pretrained_model_name_or_path=lowerCamelCase__			,						subfolder=lowerCamelCase__			,						return_unused_kwargs=lowerCamelCase__			,						**lowerCamelCase__			,						)
							__lowerCamelCase       ,						__lowerCamelCase		       =    cls.from_config(lowerCamelCase__			,						return_unused_kwargs=lowerCamelCase__			,						**lowerCamelCase__							)

							if hasattr(lowerCamelCase__			,						'create_state'							) and getattr(lowerCamelCase__			,						'has_state'			,						lowerCamelCase__							):
											__lowerCamelCase		       =    scheduler.create_state()

							if return_unused_kwargs:
											return scheduler, state, unused_kwargs

							return scheduler, state


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = False			,						**lowerCamelCase__							)    ->      Tuple:



							'''simple docstring'''
							self.save_config(save_directory=lowerCamelCase__			,						push_to_hub=lowerCamelCase__			,						**lowerCamelCase__							)


			@property
			def       lowercase_    (      self							)    ->      int:



							'''simple docstring'''
							return self._get_compatibles()






			@classmethod
			def       lowercase_    (      cls							)    ->      Union[str, Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    list(set([cls.__name__] + cls._compatibles							)							)
							__lowerCamelCase		       =    importlib.import_module(__name__.split('.'							)[0]							)
							__lowerCamelCase		       =    [
							    getattr(lowerCamelCase__			,						lowerCamelCase__							) for c in compatible_classes_str if hasattr(lowerCamelCase__			,						lowerCamelCase__							)
							]
							return compatible_classes







def 			lowerCamelCase_		(       UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      Tuple[int]      )     ->       jnp.ndarray:





				"""simple docstring"""


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







def 			lowerCamelCase_		(       UpperCamelCase__				:      int ,     UpperCamelCase__				:      str=0.9_99 ,     UpperCamelCase__				:      str=jnp.floataa      )     ->       jnp.ndarray:





				"""simple docstring"""


				def alpha_bar(UpperCamelCase__				:      List[str]      ):
								return math.cos((time_step + 0.0_08) / 1.0_08 * math.pi / 2      ) ** 2

				__lowerCamelCase		       =    []
				for i in range(UpperCamelCase__      ):
								__lowerCamelCase		       =    i / num_diffusion_timesteps
								__lowerCamelCase		       =    (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     __lowerCAmelCase :

			"""simple docstring"""







			snake_case_   		=       42
			snake_case_   		=       42
			snake_case_   		=       42


			@classmethod
			def       lowercase_    (      cls			,						lowerCamelCase__							)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    scheduler.config

							if config.trained_betas is not None:
											__lowerCamelCase		       =    jnp.asarray(config.trained_betas			,						dtype=scheduler.dtype							)
							elif config.beta_schedule == "linear":
											__lowerCamelCase		       =    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		       =    (
											    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		       =    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		       =    1.0 - betas

							__lowerCamelCase		       =    jnp.cumprod(lowerCamelCase__			,						axis=0							)

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







def 			lowerCamelCase_		(       UpperCamelCase__				:      CommonSchedulerState ,     UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      jnp.ndarray      )     ->       int:





				"""simple docstring"""


				__lowerCamelCase		       =    state.alphas_cumprod

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

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

				return sqrt_alpha_prod, sqrt_one_minus_alpha_prod







def 			lowerCamelCase_		(       UpperCamelCase__				:      CommonSchedulerState ,     UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      jnp.ndarray      )     ->       Optional[int]:





				"""simple docstring"""


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







def 			lowerCamelCase_		(       UpperCamelCase__				:      CommonSchedulerState ,     UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      jnp.ndarray ,     UpperCamelCase__				:      jnp.ndarray      )     ->       List[str]:





				"""simple docstring"""


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








from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__A        =    10







def 			lowerCamelCase_		(       UpperCamelCase__				:      int ,     UpperCamelCase__				:      int ,     UpperCamelCase__				:      list[int] ,     UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				for i in range(UpperCamelCase__ ,     UpperCamelCase__      ):
								if array[i] == target:
												return i
				return -1







def 			lowerCamelCase_		(       UpperCamelCase__				:      list[int] ,     UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				__lowerCamelCase		       =    0
				__lowerCamelCase		       =    len(UpperCamelCase__      )
				while left <= right:
								if right - left < precision:
												return lin_search(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )

								__lowerCamelCase		       =    (left + right) // 3 + 1
								__lowerCamelCase		       =    2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												__lowerCamelCase		       =    one_third - 1
								elif array[two_third] < target:
												__lowerCamelCase		       =    two_third + 1

								else:
												__lowerCamelCase		       =    one_third + 1
												__lowerCamelCase		       =    two_third - 1
				else:
								return -1







def 			lowerCamelCase_		(       UpperCamelCase__				:      int ,     UpperCamelCase__				:      int ,     UpperCamelCase__				:      list[int] ,     UpperCamelCase__				:      int      )     ->       int:





				"""simple docstring"""


				if left < right:
								if right - left < precision:
												return lin_search(UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )
								__lowerCamelCase		       =    (left + right) // 3 + 1
								__lowerCamelCase		       =    2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												return rec_ternary_search(UpperCamelCase__ ,     one_third - 1 ,     UpperCamelCase__ ,     UpperCamelCase__      )
								elif array[two_third] < target:
												return rec_ternary_search(two_third + 1 ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__      )
								else:
												return rec_ternary_search(one_third + 1 ,     two_third - 1 ,     UpperCamelCase__ ,     UpperCamelCase__      )
				else:
								return -1


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					__A        =    input("Enter numbers separated by comma:\n").strip()
					__A        =    [int(item.strip()) for item in user_input.split(",")]
					assert collection == sorted(collection), f"List must be ordered.\n{collection}."
					__A        =    int(input("Enter the number to be found in the list:\n").strip())
					__A        =    ite_ternary_search(collection, target)
					__A        =    rec_ternary_search(0, len(collection) - 1, collection, target)
					if resulta != -1:
										print(f'''Iterative search: {target} found at positions: {resulta}''')
										print(f'''Recursive search: {target} found at positions: {resulta}''')
					else:
										print("Not found")


