





from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
      from ... import FeatureExtractionMixin, TensorType

_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'openai/imagegpt-small': '',
    'openai/imagegpt-medium': '',
    'openai/imagegpt-large': '',
}






class        snake_case_    (		__lowercase						):
  A_      							=   'imagegpt'
  A_      							=   ['past_key_values']
  A_      							=   {
      'hidden_size': 'n_embd',
      'max_position_embeddings': 'n_positions',
      'num_attention_heads': 'n_head',
      'num_hidden_layers': 'n_layer',
  }






  def __init__(							self			:					Tuple       ,  _snake_case			:					int=512 + 1       ,  _snake_case			:					List[str]=32 * 32       ,  _snake_case			:					Tuple=512       ,  _snake_case			:					Union[str, Any]=24       ,  _snake_case			:					Tuple=8       ,  _snake_case			:					Union[str, Any]=None       ,  _snake_case			:					Union[str, Any]="quick_gelu"       ,  _snake_case			:					Tuple=0.1       ,  _snake_case			:					str=0.1       ,  _snake_case			:					Any=0.1       ,  _snake_case			:					Dict=1E-5       ,  _snake_case			:					Dict=0.02       ,  _snake_case			:					Optional[int]=True       ,  _snake_case			:					Union[str, Any]=True       ,  _snake_case			:					Union[str, Any]=False       ,  _snake_case			:					Optional[Any]=False       ,  _snake_case			:					int=False       ,  **_snake_case			:					Union[str, Any]       ,  )->int:






   '''simple docstring'''

   __lowerCAmelCase					:	Union[str, Any]      =       vocab_size
   __lowerCAmelCase					:	str      =       n_positions
   __lowerCAmelCase					:	Any      =       n_embd
   __lowerCAmelCase					:	List[str]      =       n_layer
   __lowerCAmelCase					:	int      =       n_head
   __lowerCAmelCase					:	Union[str, Any]      =       n_inner
   __lowerCAmelCase					:	List[Any]      =       activation_function
   __lowerCAmelCase					:	Optional[Any]      =       resid_pdrop
   __lowerCAmelCase					:	Union[str, Any]      =       embd_pdrop
   __lowerCAmelCase					:	Optional[int]      =       attn_pdrop
   __lowerCAmelCase					:	List[str]      =       layer_norm_epsilon
   __lowerCAmelCase					:	int      =       initializer_range
   __lowerCAmelCase					:	List[str]      =       scale_attn_weights
   __lowerCAmelCase					:	str      =       use_cache
   __lowerCAmelCase					:	Optional[Any]      =       scale_attn_by_inverse_layer_idx
   __lowerCAmelCase					:	int      =       reorder_and_upcast_attn
   __lowerCAmelCase					:	Any      =       tie_word_embeddings

   super().__init__(tie_word_embeddings=_snake_case       ,  **_snake_case      )






class        snake_case_    (		__lowercase						):






  @property
  def 				UpperCAmelCase__						(							self			:					Optional[Any]      )->Mapping[str, Mapping[int, str]]:






   '''simple docstring'''

   return OrderedDict(
       [
           ("""input_ids""", {0: """batch""", 1: """sequence"""}),
       ]      )






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]       ,  _snake_case			:					"FeatureExtractionMixin"       ,  _snake_case			:					int = 1       ,  _snake_case			:					int = -1       ,  _snake_case			:					bool = False       ,  _snake_case			:					Optional["TensorType"] = None       ,  _snake_case			:					int = 3       ,  _snake_case			:					int = 32       ,  _snake_case			:					int = 32       ,  )->Mapping[str, Any]:






   '''simple docstring'''

   __lowerCAmelCase					:	Any      =       self._generate_dummy_images(_snake_case       ,  _snake_case       ,  _snake_case       ,  _snake_case      )
   __lowerCAmelCase					:	Optional[Any]      =       dict(preprocessor(images=_snake_case       ,  return_tensors=_snake_case      )      )

   return inputs






from __future__ import annotations

import time

import numpy as np

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






class        snake_case_    :






  def __init__(							self			:					Union[str, Any]       ,  _snake_case			:					list[int]       ,  _snake_case			:					list[list[int]]       ,  _snake_case			:					list[list[int]]       ,  )->None:






   '''simple docstring'''

   __lowerCAmelCase					:	str      =       claim_vector
   __lowerCAmelCase					:	List[Any]      =       allocated_resources_table
   __lowerCAmelCase					:	str      =       maximum_claim_table






  def 				UpperCAmelCase__						(							self			:					Tuple      )->list[int]:






   '''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 				UpperCAmelCase__						(							self			:					int      )->list[int]:






   '''simple docstring'''

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






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->list[list[int]]:






   '''simple docstring'''

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






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]      )->dict[int, list[int]]:






   '''simple docstring'''

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






  def 				UpperCAmelCase__						(							self			:					Dict       ,  **_snake_case			:					Optional[Any]      )->None:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[int]      =       self.__need()
   __lowerCAmelCase					:	Any      =       self.__allocated_resources_table
   __lowerCAmelCase					:	List[Any]      =       self.__available_resources()
   __lowerCAmelCase					:	Optional[Any]      =       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[Any]      =       False
    for each_need in need_list:
     __lowerCAmelCase					:	Optional[int]      =       True
     for index, need in enumerate(_snake_case      ):
      if need > available_resources[index]:
       __lowerCAmelCase					:	int      =       False
       break
     if execution:
      __lowerCAmelCase					:	int      =       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(_snake_case      )
      # update available/freed resources stack
      __lowerCAmelCase					:	int      =       np.array(_snake_case      ) + np.array(
          alloc_resources_table[process_number]      )
      print(
          """Updated available resource stack for processes: """
          + """ """.join([str(_snake_case      ) 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 				UpperCAmelCase__						(							self			:					List[Any]      )->int:






   '''simple docstring'''

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


if __name__ == "__main__":
      import doctest

      doctest.testmod()