





from __future__ import annotations

import time

import numpy as np

_UpperCAmelCase       : Dict			     =       [8, 5, 9, 7]
_UpperCAmelCase       : List[str]			     =       [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
_UpperCAmelCase       : int			     =       [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]

class      lowerCAmelCase							:
 def __init__(   self						:   Any    ,  UpperCAmelCase						:   list[int]    ,  UpperCAmelCase						:   list[list[int]]    ,  UpperCAmelCase						:   list[list[int]]    ,  )    ->			None:
     lowerCamelCase__					:   Union[str, Any]      				=	claim_vector
     lowerCamelCase__					:   str      				=	allocated_resources_table
     lowerCamelCase__					:   int      				=	maximum_claim_table
 def   A_			(   self						:   List[str]			)    ->			list[int]:
     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						:   Dict			)    ->			list[int]:
     return np.array(self.__claim_vector			) - np.array(
         self.__processes_resource_summation()			)
 def   A_			(   self						:   str			)    ->			list[list[int]]:
     return [
         list(np.array(self.__maximum_claim_table[i]			) - np.array(UpperCAmelCase			)			)
         for i, allocated_resource in enumerate(self.__allocated_resources_table			)
     ]
 def   A_			(   self						:   List[Any]			)    ->			dict[int, list[int]]:
     return {self.__need().index(UpperCAmelCase			): i for i in self.__need()}
 def   A_			(   self						:   Optional[Any]    ,  **UpperCAmelCase						:   Dict			)    ->			None:
     lowerCamelCase__					:   Any      				=	self.__need()
     lowerCamelCase__					:   Union[str, Any]      				=	self.__allocated_resources_table
     lowerCamelCase__					:   int      				=	self.__available_resources()
     lowerCamelCase__					:   Dict      				=	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:
         lowerCamelCase__					:   Optional[int]      				=	False
         for each_need in need_list:
             lowerCamelCase__					:   Dict      				=	True
             for index, need in enumerate(UpperCAmelCase			):
                 if need > available_resources[index]:
                     lowerCamelCase__					:   Optional[Any]      				=	False
                     break
             if execution:
                 lowerCamelCase__					:   Dict      				=	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:
                         lowerCamelCase__					:   Any      				=	original_need_index
                 print(F"""Process {process_number + 1} is executing."""			)
                 # remove the process run from stack
                 need_list.remove(UpperCAmelCase			)
                 # update available/freed resources stack
                 lowerCamelCase__					:   List[Any]      				=	np.array(UpperCAmelCase			) + np.array(
                     alloc_resources_table[process_number]			)
                 print(
                     'Updated available resource stack for processes: '
                     + ' '.join([str(UpperCAmelCase			) 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						:   Tuple			)    ->			Union[str, Any]:
     print(' ' * 9 + 'Allocated Resource Table'			)
     for item in self.__allocated_resources_table:
         print(
             F"""P{self.__allocated_resources_table.index(UpperCAmelCase			) + 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(UpperCAmelCase			) + 1}"""
             + ' '.join(F"""{it:>8}""" for it in item			)
             + '\n'			)
     print(
         'Current Usage by Active Processes: '
         + ' '.join(str(UpperCAmelCase			) for x in self.__claim_vector			)			)
     print(
         'Initial Available Resources:       '
         + ' '.join(str(UpperCAmelCase			) for x in self.__available_resources()			)			)
     time.sleep(1			)


if __name__ == "__main__":
    import doctest

    doctest.testmod()












from ...configuration_utils import PretrainedConfig
from ...utils import logging


_UpperCAmelCase       : Dict			     =       logging.get_logger(__name__)

_UpperCAmelCase       : Union[str, Any]			     =       {
    """naver-clova-ix/donut-base""": """https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json""",
    # See all Donut models at https://huggingface.co/models?filter=donut-swin
}

class      lowerCAmelCase							(      __UpperCamelCase    ):
 UpperCAmelCase__									=	"""donut-swin"""

 UpperCAmelCase__									=	{
     """num_attention_heads""": """num_heads""",
     """num_hidden_layers""": """num_layers""",
 }
 def __init__(   self						:   Tuple    ,  UpperCAmelCase						:   List[str]=224    ,  UpperCAmelCase						:   Optional[Any]=4    ,  UpperCAmelCase						:   Union[str, Any]=3    ,  UpperCAmelCase						:   Union[str, Any]=96    ,  UpperCAmelCase						:   int=[2, 2, 6, 2]    ,  UpperCAmelCase						:   Dict=[3, 6, 12, 24]    ,  UpperCAmelCase						:   Any=7    ,  UpperCAmelCase						:   Optional[int]=4.0    ,  UpperCAmelCase						:   List[Any]=True    ,  UpperCAmelCase						:   Any=0.0    ,  UpperCAmelCase						:   Optional[Any]=0.0    ,  UpperCAmelCase						:   int=0.1    ,  UpperCAmelCase						:   List[str]="gelu"    ,  UpperCAmelCase						:   List[str]=False    ,  UpperCAmelCase						:   str=0.0_2    ,  UpperCAmelCase						:   str=1e-5    ,  **UpperCAmelCase						:   Tuple    ,  )    ->			int:
     super().__init__(**UpperCAmelCase			)

     lowerCamelCase__					:   Optional[Any]      				=	image_size
     lowerCamelCase__					:   Optional[int]      				=	patch_size
     lowerCamelCase__					:   int      				=	num_channels
     lowerCamelCase__					:   int      				=	embed_dim
     lowerCamelCase__					:   Optional[Any]      				=	depths
     lowerCamelCase__					:   Optional[int]      				=	len(UpperCAmelCase			)
     lowerCamelCase__					:   Optional[int]      				=	num_heads
     lowerCamelCase__					:   Tuple      				=	window_size
     lowerCamelCase__					:   Dict      				=	mlp_ratio
     lowerCamelCase__					:   str      				=	qkv_bias
     lowerCamelCase__					:   Tuple      				=	hidden_dropout_prob
     lowerCamelCase__					:   str      				=	attention_probs_dropout_prob
     lowerCamelCase__					:   str      				=	drop_path_rate
     lowerCamelCase__					:   int      				=	hidden_act
     lowerCamelCase__					:   str      				=	use_absolute_embeddings
     lowerCamelCase__					:   List[Any]      				=	layer_norm_eps
     lowerCamelCase__					:   Optional[Any]      				=	initializer_range
     # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
     # this indicates the channel dimension after the last stage of the model
     lowerCamelCase__					:   Optional[int]      				=	int(embed_dim * 2 ** (len(UpperCAmelCase			) - 1)			)





