


'''simple docstring'''

from __future__ import annotations



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					list[list[int]]     ,		_UpperCamelCase   :					list[list[int]] )		->       list[int]:





   '''simple docstring'''







   assert len(_UpperCamelCase ) == len(_UpperCamelCase )

   UpperCamelCase__			    =    len(_UpperCamelCase )
   UpperCamelCase__			    =    list(range(_UpperCamelCase ) )
   UpperCamelCase__			    =    [-1] * n  # who the donor has donated to
   UpperCamelCase__			    =    [-1] * n  # who the recipient has received from
   UpperCamelCase__			    =    [0] * n

   while unmatched_donors:
      UpperCamelCase__			    =    unmatched_donors[0]
      UpperCamelCase__			    =    donor_pref[donor]
      UpperCamelCase__			    =    donor_preference[num_donations[donor]]
      num_donations[donor] += 1
      UpperCamelCase__			    =    recipient_pref[recipient]
      UpperCamelCase__			    =    rec_record[recipient]

      if prev_donor != -1:
         if rec_preference.index(_UpperCamelCase ) > rec_preference.index(_UpperCamelCase ):
            UpperCamelCase__			    =    donor
            UpperCamelCase__			    =    recipient
            unmatched_donors.append(_UpperCamelCase )
            unmatched_donors.remove(_UpperCamelCase )
      else:
         UpperCamelCase__			    =    donor
         UpperCamelCase__			    =    recipient
         unmatched_donors.remove(_UpperCamelCase )
   return donor_record



'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowercase:		Tuple    						=  {
    "configuration_imagegpt": ["IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ImageGPTConfig", "ImageGPTOnnxConfig"]
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase:		List[str]    						=  ["ImageGPTFeatureExtractor"]
       __lowercase:		Tuple    						=  ["ImageGPTImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowercase:		str    						=  [
           "IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "ImageGPTForCausalImageModeling",
           "ImageGPTForImageClassification",
           "ImageGPTModel",
           "ImageGPTPreTrainedModel",
           "load_tf_weights_in_imagegpt",
       ]


if TYPE_CHECKING:
       from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
              from .image_processing_imagegpt import ImageGPTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_imagegpt import (
                  IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  ImageGPTForCausalImageModeling,
                  ImageGPTForImageClassification,
                  ImageGPTModel,
                  ImageGPTPreTrainedModel,
                  load_tf_weights_in_imagegpt,
              )

else:
       import sys

       __lowercase:		List[str]    						=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)