from __future__ import annotations

import time

import numpy as np

A_					    =      [8, 5, 9, 7]
A_					    =      [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
A_					    =      [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]






class      __lowercase					:

						def __init__(	self				:      List[str]							,							__lowerCamelCase				:      list[int]							,							__lowerCamelCase				:      list[list[int]]							,							__lowerCamelCase				:      list[list[int]]							,							)							->		int:


									'''simple docstring'''

									lowercase							=		claim_vector
									lowercase							=		allocated_resources_table
									lowercase							=		maximum_claim_table

						def        __a		(	self				:      Tuple   )							->		Dict:


									'''simple docstring'''

									return [
									    sum(p_item[i] for p_item in self.__allocated_resources_table   )
									    for i in range(len(self.__allocated_resources_table[0]   )   )
									]

						def        __a		(	self				:      int   )							->		Tuple:


									'''simple docstring'''

									return np.array(self.__claim_vector   ) - np.array(
									    self.__processes_resource_summation()   )

						def        __a		(	self				:      Dict   )							->		Optional[Any]:


									'''simple docstring'''

									return [
									    list(np.array(self.__maximum_claim_table[i]   ) - np.array(_a   )   )
									    for i, allocated_resource in enumerate(self.__allocated_resources_table   )
									]

						def        __a		(	self				:      Optional[int]   )							->		List[Any]:


									'''simple docstring'''

									return {self.__need().index(_a   ): i for i in self.__need()}

						def        __a		(	self				:      Optional[int]							,							**__lowerCamelCase				:      int   )							->		List[Any]:


									'''simple docstring'''

									lowercase							=		self.__need()
									lowercase							=		self.__allocated_resources_table
									lowercase							=		self.__available_resources()
									lowercase							=		self.__need_index_manager()
									for kw, val in kwargs.items():
												if kw and val is True:
															self.__pretty_data()
									print('''_''' * 50 + '''\n'''   )
									while need_list:
												lowercase							=		False
												for each_need in need_list:
															lowercase							=		True
															for index, need in enumerate(_a   ):
																		if need > available_resources[index]:
																					lowercase							=		False
																					break
															if execution:
																		lowercase							=		True
																		# get the original index of the process from ind_ctrl db
																		for original_need_index, need_clone in need_index_manager.items():
																					if each_need == need_clone:
																								lowercase							=		original_need_index
																		print(f'Process {process_number + 1} is executing.'   )
																		# remove the process run from stack
																		need_list.remove(_a   )
																		# update available/freed resources stack
																		lowercase							=		np.array(_a   ) + np.array(
																		    alloc_resources_table[process_number]   )
																		print(
																		    '''Updated available resource stack for processes: '''
																		    + ''' '''.join([str(_a   ) for x in available_resources]   )   )
																		break
												if safe:
															print('''The process is in a safe state.\n'''   )
												else:
															print('''System in unsafe state. Aborting...\n'''   )
															break



						def        __a		(	self				:      Dict   )							->		List[str]:


									'''simple docstring'''

									print(''' ''' * 9 + '''Allocated Resource Table'''   )
									for item in self.__allocated_resources_table:
												print(
												    f'P{self.__allocated_resources_table.index(_a   ) + 1}'
												    + ''' '''.join(f'{it:>8}' for it in item   )
												    + '''\n'''   )
									print(''' ''' * 9 + '''System Resource Table'''   )
									for item in self.__maximum_claim_table:
												print(
												    f'P{self.__maximum_claim_table.index(_a   ) + 1}'
												    + ''' '''.join(f'{it:>8}' for it in item   )
												    + '''\n'''   )
									print(
									    '''Current Usage by Active Processes: '''
									    + ''' '''.join(str(_a   ) for x in self.__claim_vector   )   )
									print(
									    '''Initial Available Resources:       '''
									    + ''' '''.join(str(_a   ) for x in self.__available_resources()   )   )
									time.sleep(1   )


if __name__ == "__main__":
						import doctest

						doctest.testmod()






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					 =     None
						lowercase					 =     None
						lowercase					 =     None  # sigma(t_i)

						@classmethod
						def        __a		(	cls				:      List[str]   )							->		Dict:


									'''simple docstring'''

									return cls()






@dataclass
class      __lowercase					(    _A    ):
						lowercase					 =     42
						lowercase					 =     42
						lowercase					 =     42






class      __lowercase					(    _A       ,     _A    ):

						@property
						def        __a		(	self				:      Union[str, Any]   )							->		Optional[Any]:


									'''simple docstring'''

									return True

						@register_to_config
						def __init__(	self				:      int							,							__lowerCamelCase				:      float = 0.02							,							__lowerCamelCase				:      float = 1_00							,							__lowerCamelCase				:      float = 1.007							,							__lowerCamelCase				:      float = 80							,							__lowerCamelCase				:      float = 0.05							,							__lowerCamelCase				:      float = 50							,							)							->		List[Any]:


									'''simple docstring'''

									pass

						def        __a		(	self				:      Dict   )							->		Optional[int]:


									'''simple docstring'''

									return KarrasVeSchedulerState.create()

						def        __a		(	self				:      str							,							__lowerCamelCase				:      KarrasVeSchedulerState							,							__lowerCamelCase				:      int							,							__lowerCamelCase				:      Tuple = ()   )							->		KarrasVeSchedulerState:


									'''simple docstring'''

									lowercase							=		jnp.arange(0							,							__lowerCamelCase   )[::-1].copy()
									lowercase							=		[
									    (
									        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        __a		(	self				:      Optional[Any]							,							__lowerCamelCase				:      KarrasVeSchedulerState							,							__lowerCamelCase				:      jnp.ndarray							,							__lowerCamelCase				:      float							,							__lowerCamelCase				:      random.KeyArray							,							)							->		Tuple[jnp.ndarray, float]:


									'''simple docstring'''

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

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

									return sample_hat, sigma_hat

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


									'''simple docstring'''

									lowercase							=		sample_hat + sigma_hat * model_output
									lowercase							=		(sample_hat - pred_original_sample) / sigma_hat
									lowercase							=		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        __a		(	self				:      str							,							__lowerCamelCase				:      KarrasVeSchedulerState							,							__lowerCamelCase				:      jnp.ndarray							,							__lowerCamelCase				:      float							,							__lowerCamelCase				:      float							,							__lowerCamelCase				:      jnp.ndarray							,							__lowerCamelCase				:      jnp.ndarray							,							__lowerCamelCase				:      jnp.ndarray							,							__lowerCamelCase				:      bool = True							,							)							->		Union[FlaxKarrasVeOutput, Tuple]:


									'''simple docstring'''

									lowercase							=		sample_prev + sigma_prev * model_output
									lowercase							=		(sample_prev - pred_original_sample) / sigma_prev
									lowercase							=		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        __a		(	self				:      int							,							__lowerCamelCase				:      KarrasVeSchedulerState							,							__lowerCamelCase				:      str							,							__lowerCamelCase				:      str							,							__lowerCamelCase				:      Dict   )							->		Tuple:


									'''simple docstring'''

									raise NotImplementedError()





