code: 
  """simple docstring"""
  import copy
  import inspect
  
  from transformers.testing_utils import require_torch, torch_device
  from transformers.utils.backbone_utils import BackboneType
  
  
  
  
  @require_torch
  class   lowercase__							:
     __UpperCAmelCase       					=				()
     __UpperCAmelCase       					=				True
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Tuple:
        _lowerCamelCase  :				Tuple      =		self.config_class
  
        # test default config
        _lowerCamelCase  :				Tuple      =		config_class()
        self.assertIsNotNone(SCREAMING_SNAKE_CASE)
        _lowerCamelCase  :				int      =		["""stem"""] + [F'stage{idx}' for idx in range(1			,      len(config.depths) + 1)]
        self.assertEqual(config.stage_names			,      SCREAMING_SNAKE_CASE)
        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
        _lowerCamelCase  :				Optional[Any]      =		config_class(out_features=SCREAMING_SNAKE_CASE			,      out_indices=SCREAMING_SNAKE_CASE)
        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
        _lowerCamelCase  :				Union[str, Any]      =		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
        _lowerCamelCase  :				Union[str, Any]      =		config_class(out_features=["""stage1""", """stage3"""])
        self.assertEqual(config.out_features			,      ["""stage1""", """stage3"""])
        self.assertEqual(config.out_indices			,      [1, 3])
  
        # Only out_indices set
        _lowerCamelCase  :				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(SCREAMING_SNAKE_CASE):
           _lowerCamelCase  :				Optional[Any]      =		config_class(out_features=["""stage1""", """stage2"""]			,      out_indices=[0, 2])
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     List[str]:
        _lowerCamelCase      ,						_lowerCamelCase  :				Union[str, Any]      =		self.model_tester.prepare_config_and_inputs_for_common()
  
        for model_class in self.all_model_classes:
           _lowerCamelCase  :				int      =		model_class(SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				str      =		inspect.signature(model.forward)
           # signature.parameters is an OrderedDict => so arg_names order is deterministic
           _lowerCamelCase  :				int      =		[*signature.parameters.keys()]
           _lowerCamelCase  :				str      =		["""pixel_values"""]
           self.assertListEqual(arg_names[:1]			,      SCREAMING_SNAKE_CASE)
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     List[Any]:
        _lowerCamelCase      ,						_lowerCamelCase  :				str      =		self.model_tester.prepare_config_and_inputs_for_common()
  
        for model_class in self.all_model_classes:
           _lowerCamelCase  :				Any      =		model_class(SCREAMING_SNAKE_CASE)
           self.assertEqual(len(model.channels)			,      len(config.out_features))
           _lowerCamelCase  :				Tuple      =		model.num_features
           _lowerCamelCase  :				List[str]      =		[config.stage_names.index(SCREAMING_SNAKE_CASE) for feat in config.out_features]
           _lowerCamelCase  :				Optional[int]      =		[num_features[idx] for idx in out_indices]
           self.assertListEqual(model.channels			,      SCREAMING_SNAKE_CASE)
  
           _lowerCamelCase  :				List[str]      =		copy.deepcopy(SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				Optional[int]      =		None
           _lowerCamelCase  :				Tuple      =		model_class(SCREAMING_SNAKE_CASE)
           self.assertEqual(len(model.channels)			,      1)
           self.assertListEqual(model.channels			,      [num_features[-1]])
  
           _lowerCamelCase  :				str      =		copy.deepcopy(SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				Union[str, Any]      =		None
           _lowerCamelCase  :				Dict      =		model_class(SCREAMING_SNAKE_CASE)
           self.assertEqual(len(model.channels)			,      1)
           self.assertListEqual(model.channels			,      [num_features[-1]])
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Tuple:
        _lowerCamelCase      ,						_lowerCamelCase  :				Union[str, Any]      =		self.model_tester.prepare_config_and_inputs_for_common()
  
        for model_class in self.all_model_classes:
           _lowerCamelCase  :				Optional[int]      =		model_class(SCREAMING_SNAKE_CASE)
           model.to(SCREAMING_SNAKE_CASE)
           model.eval()
           _lowerCamelCase  :				Optional[int]      =		model(**SCREAMING_SNAKE_CASE)
  
           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
           _lowerCamelCase  :				int      =		copy.deepcopy(SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				List[Any]      =		None
           _lowerCamelCase  :				Tuple      =		model_class(SCREAMING_SNAKE_CASE)
           model.to(SCREAMING_SNAKE_CASE)
           model.eval()
           _lowerCamelCase  :				List[str]      =		model(**SCREAMING_SNAKE_CASE)
  
           self.assertEqual(len(result.feature_maps)			,      1)
           self.assertEqual(len(model.channels)			,      1)
  
           _lowerCamelCase  :				Tuple      =		copy.deepcopy(SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				Optional[int]      =		None
           _lowerCamelCase  :				Optional[int]      =		model_class(SCREAMING_SNAKE_CASE)
           model.to(SCREAMING_SNAKE_CASE)
           model.eval()
           _lowerCamelCase  :				Dict      =		model(**SCREAMING_SNAKE_CASE)
  
           self.assertEqual(len(result.feature_maps)			,      1)
           self.assertEqual(len(model.channels)			,      1)
  
           # Check backbone can be initialized with fresh weights
           _lowerCamelCase  :				Dict      =		copy.deepcopy(SCREAMING_SNAKE_CASE)
           _lowerCamelCase  :				Tuple      =		False
           _lowerCamelCase  :				Dict      =		model_class(SCREAMING_SNAKE_CASE)
           model.to(SCREAMING_SNAKE_CASE)
           model.eval()
           _lowerCamelCase  :				str      =		model(**SCREAMING_SNAKE_CASE)
  
  
  
  
  
     def 		UpperCamelCase_     (       self)     ->     Optional[int]:
        _lowerCamelCase      ,						_lowerCamelCase  :				Optional[int]      =		self.model_tester.prepare_config_and_inputs_for_common()
  
        for backbone_class in self.all_model_classes:
           _lowerCamelCase  :				Optional[int]      =		backbone_class(SCREAMING_SNAKE_CASE)
  
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """backbone_type"""))
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """stage_names"""))
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """num_features"""))
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """out_indices"""))
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """out_features"""))
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """out_feature_channels"""))
           self.assertTrue(hasattr(SCREAMING_SNAKE_CASE			,      """channels"""))
  
           self.assertIsInstance(backbone.backbone_type			,      SCREAMING_SNAKE_CASE)
           # 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 		UpperCamelCase_     (       self)     ->     int:
        _lowerCamelCase      ,						_lowerCamelCase  :				List[str]      =		self.model_tester.prepare_config_and_inputs_for_common()
        _lowerCamelCase  :				int      =		inputs_dict["""pixel_values"""].shape[0]
  
        for backbone_class in self.all_model_classes:
           _lowerCamelCase  :				str      =		backbone_class(SCREAMING_SNAKE_CASE)
           backbone.to(SCREAMING_SNAKE_CASE)
           backbone.eval()
  
           _lowerCamelCase  :				int      =		backbone(**SCREAMING_SNAKE_CASE)
  
           # Test default outputs and verify feature maps
           self.assertIsInstance(outputs.feature_maps			,      SCREAMING_SNAKE_CASE)
           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
           _lowerCamelCase  :				List[Any]      =		backbone(**SCREAMING_SNAKE_CASE			,      output_hidden_states=SCREAMING_SNAKE_CASE)
           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:
              _lowerCamelCase  :				int      =		backbone(**SCREAMING_SNAKE_CASE			,      output_attentions=SCREAMING_SNAKE_CASE)
              self.assertIsNotNone(outputs.attentions)
  
  
style_context: 
  
  
  """simple docstring"""
  def 							_snake_case			(      __snake_case       :			str	,   __snake_case       :			str	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _lowerCamelCase  :				Optional[Any]      =		list(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		list(__snake_case      )
     _lowerCamelCase  :				Union[str, Any]      =		len(__snake_case      )
     _lowerCamelCase  :				Optional[int]      =		len(__snake_case      )
  
     _lowerCamelCase  :				List[str]      =		[
         [0 for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
     ]
     _lowerCamelCase  :				List[Any]      =		[
         ["""0""" for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
     ]
  
     for i in range(1	,   len_source_seq + 1      ):
        _lowerCamelCase  :				Optional[Any]      =		i * delete_cost
        _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'
  
     for i in range(1	,   len_destination_seq + 1      ):
        _lowerCamelCase  :				Dict      =		i * insert_cost
        _lowerCamelCase  :				List[str]      =		F'I{destination_seq[i - 1]:c}'
  
     for i in range(1	,   len_source_seq + 1      ):
        for j in range(1	,   len_destination_seq + 1      ):
           if source_seq[i - 1] == destination_seq[j - 1]:
              _lowerCamelCase  :				Union[str, Any]      =		costs[i - 1][j - 1] + copy_cost
              _lowerCamelCase  :				Tuple      =		F'C{source_seq[i - 1]:c}'
           else:
              _lowerCamelCase  :				Tuple      =		costs[i - 1][j - 1] + replace_cost
              _lowerCamelCase  :				List[str]      =		F'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]      )
  
           if costs[i - 1][j] + delete_cost < costs[i][j]:
              _lowerCamelCase  :				Any      =		costs[i - 1][j] + delete_cost
              _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'
  
           if costs[i][j - 1] + insert_cost < costs[i][j]:
              _lowerCamelCase  :				Dict      =		costs[i][j - 1] + insert_cost
              _lowerCamelCase  :				Union[str, Any]      =		F'I{destination_seq[j - 1]:c}'
  
     return costs, ops
  
  def 							_snake_case			(      __snake_case       :			list[list[str]]	,   __snake_case       :			int	,   __snake_case       :			int      ):
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     if i == 0 and j == 0:
        return []
     else:
        if ops[i][j][0] == "C" or ops[i][j][0] == "R":
           _lowerCamelCase  :				List[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   j - 1      )
           seq.append(ops[i][j]      )
           return seq
        elif ops[i][j][0] == "D":
           _lowerCamelCase  :				Optional[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   __snake_case      )
           seq.append(ops[i][j]      )
           return seq
        else:
           _lowerCamelCase  :				str      =		assemble_transformation(__snake_case	,   __snake_case	,   j - 1      )
           seq.append(ops[i][j]      )
           return seq
  
  
  if __name__ == "__main__":
   UpperCAmelCase ,     UpperCAmelCase   =	compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)
  
   UpperCAmelCase   =	len(operations)
   UpperCAmelCase   =	len(operations[0])
   UpperCAmelCase   =	assemble_transformation(operations, m - 1, n - 1)
  
   UpperCAmelCase   =	list("""Python""")
   UpperCAmelCase   =	0
   UpperCAmelCase   =	0
  
   with open("""min_cost.txt""", """w""") as file:
    for op in sequence:
     print("""""".join(string))
  
     if op[0] == "C":
      file.write("""%-16s""" % """Copy %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost -= 1
     elif op[0] == "R":
      UpperCAmelCase   =	op[2]
  
      file.write("""%-16s""" % ("""Replace %c""" % op[1] + """ with """ + str(op[2])))
      file.write("""\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 1
     elif op[0] == "D":
      string.pop(i)
  
      file.write("""%-16s""" % """Delete %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 2
     else:
      string.insert(i, op[1])
  
      file.write("""%-16s""" % """Insert %c""" % op[1])
      file.write("""\t\t\t""" + """""".join(string))
      file.write("""\r\n""")
  
      cost += 2
  
     i += 1
  
    print("""""".join(string))
    print("""Cost: """, cost)
  
    file.write("""\r\nMinimum cost: """ + str(cost))
  
  