
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'''







  a__   	=		()
  a__   	=		True
  def 							_lowercase							(			self      :			Optional[Any]   )      ->     str:







    """simple docstring"""






    __magic_name__    					=	self.config_class

    # test default config
    __magic_name__    					=	config_class()
    self.assertIsNotNone(UpperCamelCase__   )
    __magic_name__    					=	["""stem"""] + [F'''stage{idx}''' for idx in range(1      ,							len(config.depths   ) + 1   )]
    self.assertEqual(config.stage_names      ,							UpperCamelCase__   )
    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
    __magic_name__    					=	config_class(out_features=UpperCamelCase__      ,							out_indices=UpperCamelCase__   )
    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
    __magic_name__    					=	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
    __magic_name__    					=	config_class(out_features=["""stage1""", """stage3"""]   )
    self.assertEqual(config.out_features      ,							["""stage1""", """stage3"""]   )
    self.assertEqual(config.out_indices      ,							[1, 3]   )

    # Only out_indices set
    __magic_name__    					=	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(UpperCamelCase__   ):
      __magic_name__    					=	config_class(out_features=["""stage1""", """stage2"""]      ,							out_indices=[0, 2]   )
  def 							_lowercase							(			self      :			Tuple   )      ->     Optional[int]:







    """simple docstring"""






    __magic_name__					,   __magic_name__    					=	self.model_tester.prepare_config_and_inputs_for_common()

    for model_class in self.all_model_classes:
      __magic_name__    					=	model_class(UpperCamelCase__   )
      __magic_name__    					=	inspect.signature(model.forward   )
      # signature.parameters is an OrderedDict => so arg_names order is deterministic
      __magic_name__    					=	[*signature.parameters.keys()]
      __magic_name__    					=	["""pixel_values"""]
      self.assertListEqual(arg_names[:1]      ,							UpperCamelCase__   )
  def 							_lowercase							(			self      :			Dict   )      ->     Any:







    """simple docstring"""






    __magic_name__					,   __magic_name__    					=	self.model_tester.prepare_config_and_inputs_for_common()

    for model_class in self.all_model_classes:
      __magic_name__    					=	model_class(UpperCamelCase__   )
      self.assertEqual(len(model.channels   )      ,							len(config.out_features   )   )
      __magic_name__    					=	model.num_features
      __magic_name__    					=	[config.stage_names.index(UpperCamelCase__   ) for feat in config.out_features]
      __magic_name__    					=	[num_features[idx] for idx in out_indices]
      self.assertListEqual(model.channels      ,							UpperCamelCase__   )

      __magic_name__    					=	copy.deepcopy(UpperCamelCase__   )
      __magic_name__    					=	None
      __magic_name__    					=	model_class(UpperCamelCase__   )
      self.assertEqual(len(model.channels   )      ,							1   )
      self.assertListEqual(model.channels      ,							[num_features[-1]]   )

      __magic_name__    					=	copy.deepcopy(UpperCamelCase__   )
      __magic_name__    					=	None
      __magic_name__    					=	model_class(UpperCamelCase__   )
      self.assertEqual(len(model.channels   )      ,							1   )
      self.assertListEqual(model.channels      ,							[num_features[-1]]   )
  def 							_lowercase							(			self      :			Optional[int]   )      ->     Any:







    """simple docstring"""






    __magic_name__					,   __magic_name__    					=	self.model_tester.prepare_config_and_inputs_for_common()

    for model_class in self.all_model_classes:
      __magic_name__    					=	model_class(UpperCamelCase__   )
      model.to(UpperCamelCase__   )
      model.eval()
      __magic_name__    					=	model(**UpperCamelCase__   )

      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
      __magic_name__    					=	copy.deepcopy(UpperCamelCase__   )
      __magic_name__    					=	None
      __magic_name__    					=	model_class(UpperCamelCase__   )
      model.to(UpperCamelCase__   )
      model.eval()
      __magic_name__    					=	model(**UpperCamelCase__   )

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

      __magic_name__    					=	copy.deepcopy(UpperCamelCase__   )
      __magic_name__    					=	None
      __magic_name__    					=	model_class(UpperCamelCase__   )
      model.to(UpperCamelCase__   )
      model.eval()
      __magic_name__    					=	model(**UpperCamelCase__   )

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

      # Check backbone can be initialized with fresh weights
      __magic_name__    					=	copy.deepcopy(UpperCamelCase__   )
      __magic_name__    					=	False
      __magic_name__    					=	model_class(UpperCamelCase__   )
      model.to(UpperCamelCase__   )
      model.eval()
      __magic_name__    					=	model(**UpperCamelCase__   )
  def 							_lowercase							(			self      :			Optional[Any]   )      ->     Optional[Any]:







    """simple docstring"""






    __magic_name__					,   __magic_name__    					=	self.model_tester.prepare_config_and_inputs_for_common()

    for backbone_class in self.all_model_classes:
      __magic_name__    					=	backbone_class(UpperCamelCase__   )

      self.assertTrue(hasattr(UpperCamelCase__      ,							"""backbone_type"""   )   )
      self.assertTrue(hasattr(UpperCamelCase__      ,							"""stage_names"""   )   )
      self.assertTrue(hasattr(UpperCamelCase__      ,							"""num_features"""   )   )
      self.assertTrue(hasattr(UpperCamelCase__      ,							"""out_indices"""   )   )
      self.assertTrue(hasattr(UpperCamelCase__      ,							"""out_features"""   )   )
      self.assertTrue(hasattr(UpperCamelCase__      ,							"""out_feature_channels"""   )   )
      self.assertTrue(hasattr(UpperCamelCase__      ,							"""channels"""   )   )

      self.assertIsInstance(backbone.backbone_type      ,							UpperCamelCase__   )
      # 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 							_lowercase							(			self      :			Union[str, Any]   )      ->     Tuple:







    """simple docstring"""






    __magic_name__					,   __magic_name__    					=	self.model_tester.prepare_config_and_inputs_for_common()
    __magic_name__    					=	inputs_dict["""pixel_values"""].shape[0]

    for backbone_class in self.all_model_classes:
      __magic_name__    					=	backbone_class(UpperCamelCase__   )
      backbone.to(UpperCamelCase__   )
      backbone.eval()

      __magic_name__    					=	backbone(**UpperCamelCase__   )

      # Test default outputs and verify feature maps
      self.assertIsInstance(outputs.feature_maps      ,							UpperCamelCase__   )
      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
      __magic_name__    					=	backbone(**UpperCamelCase__      ,							output_hidden_states=UpperCamelCase__   )
      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:
        __magic_name__    					=	backbone(**UpperCamelCase__      ,							output_attentions=UpperCamelCase__   )
        self.assertIsNotNone(outputs.attentions   )



class 	UpperCAmelCase_      :


  '''simple docstring'''







  def __init__(			self      :			Tuple      ,							UpperCamelCase__      :			Dict=None   )      ->     List[str]:







    """simple docstring"""






    __magic_name__    					=	data
    __magic_name__    					=	None





  def __repr__(			self      :			Optional[int]   )      ->     Optional[int]:







    """simple docstring"""






    __magic_name__    					=	""""""
    __magic_name__    					=	self
    while temp:
      string_rep += F'''<{temp.data}> ---> '''
      __magic_name__    					=	temp.next
    string_rep += "<END>"
    return string_rep







def a__   (	A_ ):






  '''simple docstring'''





  if not elements_list:
    raise Exception("""The Elements List is empty""" )

  # Set first element as Head
  __magic_name__    					=	Node(elements_list[0] )
  __magic_name__    					=	head
  # Loop through elements from position 1
  for data in elements_list[1:]:
    __magic_name__    					=	Node(A_ )
    __magic_name__    					=	current.next
  return head


__lowerCAmelCase      :					Union[str, Any]   	=       [1, 3, 5, 32, 44, 12, 43]
print(F'''List: {list_data}''')
print('Creating Linked List from List.')
__lowerCAmelCase      :					Optional[Any]   	=       make_linked_list(list_data)
print('Linked List:')





print(linked_list)

