
import copy
import inspect

from transformers.testing_utils import require_torch, torch_device
from transformers.utils.backbone_utils import BackboneType






@require_torch
class UpperCAmelCase     :





   '''simple docstring'''
   __UpperCamelCase	:					Tuple				       =					()
   __UpperCamelCase	:					Optional[Any]				       =					True


   def 				__magic_name__       (      self  :							Tuple  ):

      """simple docstring"""
      _A:						Optional[int]	    = self.config_class

      # test default config
      _A:						Optional[int]	    = config_class()
      self.assertIsNotNone(lowerCAmelCase_  )
      _A:						List[str]	    = ['''stem'''] + [F"""stage{idx}""" for idx in range(1    ,    len(config.depths  ) + 1  )]
      self.assertEqual(config.stage_names    ,    lowerCAmelCase_  )
      self.assertTrue(set(config.out_features  ).issubset(set(config.stage_names  )  )  )

      # Test out_features and out_indices are correctly set
      # out_features and out_indices both None
      _A:						Tuple	    = config_class(out_features=lowerCAmelCase_    ,    out_indices=lowerCAmelCase_  )
      self.assertEqual(config.out_features    ,    [config.stage_names[-1]]  )
      self.assertEqual(config.out_indices    ,    [len(config.stage_names  ) - 1]  )

      # out_features and out_indices both set
      _A:						str	    = config_class(out_features=['''stem''', '''stage1''']    ,    out_indices=[0, 1]  )
      self.assertEqual(config.out_features    ,    ['''stem''', '''stage1''']  )
      self.assertEqual(config.out_indices    ,    [0, 1]  )

      # Only out_features set
      _A:						Dict	    = config_class(out_features=['''stage1''', '''stage3''']  )
      self.assertEqual(config.out_features    ,    ['''stage1''', '''stage3''']  )
      self.assertEqual(config.out_indices    ,    [1, 3]  )

      # Only out_indices set
      _A:						Union[str, Any]	    = config_class(out_indices=[0, 2]  )
      self.assertEqual(config.out_features    ,    [config.stage_names[0], config.stage_names[2]]  )
      self.assertEqual(config.out_indices    ,    [0, 2]  )

      # Error raised when out_indices do not correspond to out_features
      with self.assertRaises(lowerCAmelCase_  ):
         _A:						Optional[int]	    = config_class(out_features=['''stage1''', '''stage2''']    ,    out_indices=[0, 2]  )


   def 				__magic_name__       (      self  :							Any  ):

      """simple docstring"""
      _A    ,						_A:						List[Any]	    = self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
         _A:						int	    = model_class(lowerCAmelCase_  )
         _A:						Dict	    = inspect.signature(model.forward  )
         # signature.parameters is an OrderedDict => so arg_names order is deterministic
         _A:						Any	    = [*signature.parameters.keys()]
         _A:						Union[str, Any]	    = ['''pixel_values''']
         self.assertListEqual(arg_names[:1]    ,    lowerCAmelCase_  )


   def 				__magic_name__       (      self  :							int  ):

      """simple docstring"""
      _A    ,						_A:						Tuple	    = self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
         _A:						Optional[Any]	    = model_class(lowerCAmelCase_  )
         self.assertEqual(len(model.channels  )    ,    len(config.out_features  )  )
         _A:						Union[str, Any]	    = model.num_features
         _A:						List[Any]	    = [config.stage_names.index(lowerCAmelCase_  ) for feat in config.out_features]
         _A:						Union[str, Any]	    = [num_features[idx] for idx in out_indices]
         self.assertListEqual(model.channels    ,    lowerCAmelCase_  )

         _A:						Optional[Any]	    = copy.deepcopy(lowerCAmelCase_  )
         _A:						Optional[Any]	    = None
         _A:						List[str]	    = model_class(lowerCAmelCase_  )
         self.assertEqual(len(model.channels  )    ,    1  )
         self.assertListEqual(model.channels    ,    [num_features[-1]]  )

         _A:						Tuple	    = copy.deepcopy(lowerCAmelCase_  )
         _A:						Tuple	    = None
         _A:						Tuple	    = model_class(lowerCAmelCase_  )
         self.assertEqual(len(model.channels  )    ,    1  )
         self.assertListEqual(model.channels    ,    [num_features[-1]]  )


   def 				__magic_name__       (      self  :							List[str]  ):

      """simple docstring"""
      _A    ,						_A:						Any	    = self.model_tester.prepare_config_and_inputs_for_common()

      for model_class in self.all_model_classes:
         _A:						List[str]	    = model_class(lowerCAmelCase_  )
         model.to(lowerCAmelCase_  )
         model.eval()
         _A:						Union[str, Any]	    = model(**lowerCAmelCase_  )

         self.assertEqual(len(result.feature_maps  )    ,    len(config.out_features  )  )
         self.assertEqual(len(model.channels  )    ,    len(config.out_features  )  )
         self.assertEqual(len(result.feature_maps  )    ,    len(config.out_indices  )  )
         self.assertEqual(len(model.channels  )    ,    len(config.out_indices  )  )

         # Check output of last stage is taken if out_features=None, out_indices=None
         _A:						List[Any]	    = copy.deepcopy(lowerCAmelCase_  )
         _A:						Any	    = None
         _A:						List[Any]	    = model_class(lowerCAmelCase_  )
         model.to(lowerCAmelCase_  )
         model.eval()
         _A:						Union[str, Any]	    = model(**lowerCAmelCase_  )

         self.assertEqual(len(result.feature_maps  )    ,    1  )
         self.assertEqual(len(model.channels  )    ,    1  )

         _A:						Optional[Any]	    = copy.deepcopy(lowerCAmelCase_  )
         _A:						Optional[Any]	    = None
         _A:						Any	    = model_class(lowerCAmelCase_  )
         model.to(lowerCAmelCase_  )
         model.eval()
         _A:						Union[str, Any]	    = model(**lowerCAmelCase_  )

         self.assertEqual(len(result.feature_maps  )    ,    1  )
         self.assertEqual(len(model.channels  )    ,    1  )

         # Check backbone can be initialized with fresh weights
         _A:						Union[str, Any]	    = copy.deepcopy(lowerCAmelCase_  )
         _A:						Any	    = False
         _A:						Dict	    = model_class(lowerCAmelCase_  )
         model.to(lowerCAmelCase_  )
         model.eval()
         _A:						Any	    = model(**lowerCAmelCase_  )


   def 				__magic_name__       (      self  :							Tuple  ):

      """simple docstring"""
      _A    ,						_A:						Optional[int]	    = self.model_tester.prepare_config_and_inputs_for_common()

      for backbone_class in self.all_model_classes:
         _A:						int	    = backbone_class(lowerCAmelCase_  )

         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''backbone_type'''  )  )
         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''stage_names'''  )  )
         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''num_features'''  )  )
         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''out_indices'''  )  )
         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''out_features'''  )  )
         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''out_feature_channels'''  )  )
         self.assertTrue(hasattr(lowerCAmelCase_    ,    '''channels'''  )  )

         self.assertIsInstance(backbone.backbone_type    ,    lowerCAmelCase_  )
         # Verify num_features has been initialized in the backbone init
         self.assertIsNotNone(backbone.num_features  )
         self.assertTrue(len(backbone.channels  ) == len(backbone.out_indices  )  )
         self.assertTrue(len(backbone.stage_names  ) == len(backbone.num_features  )  )
         self.assertTrue(len(backbone.channels  ) <= len(backbone.num_features  )  )
         self.assertTrue(len(backbone.out_feature_channels  ) == len(backbone.stage_names  )  )


   def 				__magic_name__       (      self  :							Any  ):

      """simple docstring"""
      _A    ,						_A:						Optional[Any]	    = self.model_tester.prepare_config_and_inputs_for_common()
      _A:						Optional[Any]	    = inputs_dict['''pixel_values'''].shape[0]

      for backbone_class in self.all_model_classes:
         _A:						List[str]	    = backbone_class(lowerCAmelCase_  )
         backbone.to(lowerCAmelCase_  )
         backbone.eval()

         _A:						List[str]	    = backbone(**lowerCAmelCase_  )

         # Test default outputs and verify feature maps
         self.assertIsInstance(outputs.feature_maps    ,    lowerCAmelCase_  )
         self.assertTrue(len(outputs.feature_maps  ) == len(backbone.channels  )  )
         for feature_map, n_channels in zip(outputs.feature_maps    ,    backbone.channels  ):
            self.assertTrue(feature_map.shape[:2]    ,    (batch_size, n_channels)  )
         self.assertIsNone(outputs.hidden_states  )
         self.assertIsNone(outputs.attentions  )

         # Test output_hidden_states=True
         _A:						Optional[int]	    = backbone(**lowerCAmelCase_    ,    output_hidden_states=lowerCAmelCase_  )
         self.assertIsNotNone(outputs.hidden_states  )
         self.assertTrue(len(outputs.hidden_states  )    ,    len(backbone.stage_names  )  )
         for hidden_state, n_channels in zip(outputs.hidden_states    ,    backbone.channels  ):
            self.assertTrue(hidden_state.shape[:2]    ,    (batch_size, n_channels)  )

         # Test output_attentions=True
         if self.has_attentions:
            _A:						Union[str, Any]	    = backbone(**lowerCAmelCase_    ,    output_attentions=lowerCAmelCase_  )
            self.assertIsNotNone(outputs.attentions  )





from __future__ import annotations






def 						lowerCamelCase__							(      a	,	a   )   ->     Union[str, Any]:
   _A:						Any	    = 0
   _A:						str	    = len(a   ) - 1
   while left <= right:
      _A:						Any	    = (left + right) // 2
      if left == right:
         if sorted_list[middle] < item:
            _A:						Union[str, Any]	    = middle + 1
         break
      elif sorted_list[middle] < item:
         _A:						Optional[Any]	    = middle + 1
      else:
         _A:						str	    = middle - 1
   sorted_list.insert(a	,	a   )
   return sorted_list






def 						lowerCamelCase__							(      a	,	a   )   ->     int:
   _A:						List[Any]	    = []
   while left and right:
      if left[0][0] < right[0][0]:
         result.append(left.pop(0   )   )
      else:
         result.append(right.pop(0   )   )
   return result + left + right






def 						lowerCamelCase__							(      a   )   ->     List[Any]:
   _A:						Dict	    = len(a   )
   if length <= 1:
      return list_ad
   _A:						str	    = length // 2
   return merge(sortlist_ad(list_ad[:middle]   )	,	sortlist_ad(list_ad[middle:]   )   )






def 						lowerCamelCase__							(      a   )   ->     list[int]:

   if len(a   ) <= 1:
      return collection
   _A:						str	    = []
   _A:						Tuple	    = False
   for i in range(0	,	len(a   )	,	2   ):
      if i == len(a   ) - 1:
         _A:						Dict	    = True
      else:
         if collection[i] < collection[i + 1]:
            two_paired_list.append([collection[i], collection[i + 1]]   )
         else:
            two_paired_list.append([collection[i + 1], collection[i]]   )
   _A:						List[Any]	    = sortlist_ad(a   )
   _A:						Union[str, Any]	    = [i[0] for i in sorted_list_ad]
   result.append(sorted_list_ad[-1][1]   )
   if has_last_odd_item:
      _A:						List[Any]	    = collection[-1]
      _A:						Optional[Any]	    = binary_search_insertion(a	,	a   )
   _A:						Optional[int]	    = False
   for i in range(len(a   ) - 1   ):
      if result[i] == collection[-1] and has_last_odd_item:
         _A:						Tuple	    = True
      _A:						Optional[Any]	    = sorted_list_ad[i][1]
      # If last_odd_item is inserted before the item's index,
      # you should forward index one more.
      if is_last_odd_item_inserted_before_this_index:
         _A:						int	    = result[: i + 2] + binary_search_insertion(result[i + 2 :]	,	a   )
      else:
         _A:						Union[str, Any]	    = result[: i + 1] + binary_search_insertion(result[i + 1 :]	,	a   )

   return result


if __name__ == "__main__":
   UpperCAmelCase__	:  List[str]      =   input('Enter numbers separated by a comma:\n').strip()
   UpperCAmelCase__	:  List[Any]      =   [int(item) for item in user_input.split(',')]
   print(merge_insertion_sort(unsorted))



