


"""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 			SCREAMING_SNAKE_CASE_  :




							'''simple docstring'''





							__magic_name__					:     Optional[Any]				  =  ()
							__magic_name__					:     Dict				  =  True




							def        UpperCAmelCase (						self)   ->	List[str]:







								'''simple docstring'''




								snake_case__  :						Union[str, Any]		=      self.config_class

								# test default config
								snake_case__  :						Tuple		=      config_class()
								self.assertIsNotNone(lowerCamelCase__)
								snake_case__  :						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
								snake_case__  :						Optional[int]		=      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
								snake_case__  :						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
								snake_case__  :						Optional[int]		=      config_class(out_features=["stage1", "stage3"])
								self.assertEqual(config.out_features	,					["stage1", "stage3"])
								self.assertEqual(config.out_indices	,					[1, 3])

								# Only out_indices set
								snake_case__  :						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__):
									snake_case__  :						str		=      config_class(out_features=["stage1", "stage2"]	,					out_indices=[0, 2])




							def        UpperCAmelCase (						self)   ->	Optional[Any]:







								'''simple docstring'''




								snake_case__,					snake_case__  :						int		=      self.model_tester.prepare_config_and_inputs_for_common()

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




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







								'''simple docstring'''




								snake_case__,					snake_case__  :						Union[str, Any]		=      self.model_tester.prepare_config_and_inputs_for_common()

								for model_class in self.all_model_classes:
									snake_case__  :						Optional[int]		=      model_class(lowerCamelCase__)
									self.assertEqual(len(model.channels)	,					len(config.out_features))
									snake_case__  :						str		=      model.num_features
									snake_case__  :						int		=      [config.stage_names.index(lowerCamelCase__) for feat in config.out_features]
									snake_case__  :						Tuple		=      [num_features[idx] for idx in out_indices]
									self.assertListEqual(model.channels	,					lowerCamelCase__)

									snake_case__  :						str		=      copy.deepcopy(lowerCamelCase__)
									snake_case__  :						str		=      None
									snake_case__  :						List[str]		=      model_class(lowerCamelCase__)
									self.assertEqual(len(model.channels)	,					1)
									self.assertListEqual(model.channels	,					[num_features[-1]])

									snake_case__  :						int		=      copy.deepcopy(lowerCamelCase__)
									snake_case__  :						Tuple		=      None
									snake_case__  :						Optional[Any]		=      model_class(lowerCamelCase__)
									self.assertEqual(len(model.channels)	,					1)
									self.assertListEqual(model.channels	,					[num_features[-1]])




							def        UpperCAmelCase (						self)   ->	str:







								'''simple docstring'''




								snake_case__,					snake_case__  :						Any		=      self.model_tester.prepare_config_and_inputs_for_common()

								for model_class in self.all_model_classes:
									snake_case__  :						Dict		=      model_class(lowerCamelCase__)
									model.to(lowerCamelCase__)
									model.eval()
									snake_case__  :						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
									snake_case__  :						Any		=      copy.deepcopy(lowerCamelCase__)
									snake_case__  :						str		=      None
									snake_case__  :						str		=      model_class(lowerCamelCase__)
									model.to(lowerCamelCase__)
									model.eval()
									snake_case__  :						Dict		=      model(**lowerCamelCase__)

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

									snake_case__  :						Optional[Any]		=      copy.deepcopy(lowerCamelCase__)
									snake_case__  :						Optional[Any]		=      None
									snake_case__  :						int		=      model_class(lowerCamelCase__)
									model.to(lowerCamelCase__)
									model.eval()
									snake_case__  :						Any		=      model(**lowerCamelCase__)

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

									# Check backbone can be initialized with fresh weights
									snake_case__  :						List[Any]		=      copy.deepcopy(lowerCamelCase__)
									snake_case__  :						Optional[Any]		=      False
									snake_case__  :						Optional[Any]		=      model_class(lowerCamelCase__)
									model.to(lowerCamelCase__)
									model.eval()
									snake_case__  :						Dict		=      model(**lowerCamelCase__)




							def        UpperCAmelCase (						self)   ->	Union[str, Any]:







								'''simple docstring'''




								snake_case__,					snake_case__  :						int		=      self.model_tester.prepare_config_and_inputs_for_common()

								for backbone_class in self.all_model_classes:
									snake_case__  :						List[Any]		=      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        UpperCAmelCase (						self)   ->	Optional[int]:







								'''simple docstring'''




								snake_case__,					snake_case__  :						str		=      self.model_tester.prepare_config_and_inputs_for_common()
								snake_case__  :						Any		=      inputs_dict["pixel_values"].shape[0]

								for backbone_class in self.all_model_classes:
									snake_case__  :						str		=      backbone_class(lowerCamelCase__)
									backbone.to(lowerCamelCase__)
									backbone.eval()

									snake_case__  :						Union[str, Any]		=      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
									snake_case__  :						Dict		=      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:
										snake_case__  :						Tuple		=      backbone(**lowerCamelCase__	,					output_attentions=lowerCamelCase__)
										self.assertIsNotNone(outputs.attentions)









"""simple docstring"""






def 			A__		(					_UpperCAmelCase    :      str	)							->	list:

	'''simple docstring'''


	snake_case__  :						Any		=      []
	snake_case__  :						List[Any]		=      1

	for i in range(len(_UpperCAmelCase	)	):
		if i + 1 < len(_UpperCAmelCase	) and text[i] == text[i + 1]:
			count += 1
		else:
			encoded.append((text[i], count)	)
			snake_case__  :						Dict		=      1

	return encoded



def 			A__		(					_UpperCAmelCase    :      list	)							->	str:

	'''simple docstring'''


	return "".join(char * length for char, length in encoded	)


if __name__ == "__main__":
					from doctest import testmod

					testmod(name="""run_length_encode""", verbose=True)
					testmod(name="""run_length_decode""", verbose=True)





