




"""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__   :
						_a        =  ()
						_a        =  True


						def 					__lowercase	(							self			:     str   ):
										lowerCAmelCase		=			self.config_class

										# test default config
										lowerCAmelCase		=			config_class()
										self.assertIsNotNone(__SCREAMING_SNAKE_CASE   )
										lowerCAmelCase		=			["""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		=			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		=			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		=			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		=			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		=			config_class(out_features=["""stage1""", """stage2"""]  ,  out_indices=[0, 2]   )


						def 					__lowercase	(							self			:     List[Any]   ):
										lowerCAmelCase	,  lowerCAmelCase		=			self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
														lowerCAmelCase		=			model_class(__SCREAMING_SNAKE_CASE   )
														lowerCAmelCase		=			inspect.signature(model.forward   )
														# signature.parameters is an OrderedDict => so arg_names order is deterministic
														lowerCAmelCase		=			[*signature.parameters.keys()]
														lowerCAmelCase		=			["""pixel_values"""]
														self.assertListEqual(arg_names[:1]  ,  __SCREAMING_SNAKE_CASE   )


						def 					__lowercase	(							self			:     Optional[int]   ):
										lowerCAmelCase	,  lowerCAmelCase		=			self.model_tester.prepare_config_and_inputs_for_common()

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

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

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


						def 					__lowercase	(							self			:     Tuple   ):
										lowerCAmelCase	,  lowerCAmelCase		=			self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
														lowerCAmelCase		=			model_class(__SCREAMING_SNAKE_CASE   )
														model.to(__SCREAMING_SNAKE_CASE   )
														model.eval()
														lowerCAmelCase		=			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		=			copy.deepcopy(__SCREAMING_SNAKE_CASE   )
														lowerCAmelCase		=			None
														lowerCAmelCase		=			model_class(__SCREAMING_SNAKE_CASE   )
														model.to(__SCREAMING_SNAKE_CASE   )
														model.eval()
														lowerCAmelCase		=			model(**__SCREAMING_SNAKE_CASE   )

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

														lowerCAmelCase		=			copy.deepcopy(__SCREAMING_SNAKE_CASE   )
														lowerCAmelCase		=			None
														lowerCAmelCase		=			model_class(__SCREAMING_SNAKE_CASE   )
														model.to(__SCREAMING_SNAKE_CASE   )
														model.eval()
														lowerCAmelCase		=			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		=			copy.deepcopy(__SCREAMING_SNAKE_CASE   )
														lowerCAmelCase		=			False
														lowerCAmelCase		=			model_class(__SCREAMING_SNAKE_CASE   )
														model.to(__SCREAMING_SNAKE_CASE   )
														model.eval()
														lowerCAmelCase		=			model(**__SCREAMING_SNAKE_CASE   )


						def 					__lowercase	(							self			:     Optional[Any]   ):
										lowerCAmelCase	,  lowerCAmelCase		=			self.model_tester.prepare_config_and_inputs_for_common()

										for backbone_class in self.all_model_classes:
														lowerCAmelCase		=			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 					__lowercase	(							self			:     Dict   ):
										lowerCAmelCase	,  lowerCAmelCase		=			self.model_tester.prepare_config_and_inputs_for_common()
										lowerCAmelCase		=			inputs_dict["""pixel_values"""].shape[0]

										for backbone_class in self.all_model_classes:
														lowerCAmelCase		=			backbone_class(__SCREAMING_SNAKE_CASE   )
														backbone.to(__SCREAMING_SNAKE_CASE   )
														backbone.eval()

														lowerCAmelCase		=			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		=			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		=			backbone(**__SCREAMING_SNAKE_CASE  ,  output_attentions=__SCREAMING_SNAKE_CASE   )
																		self.assertIsNotNone(outputs.attentions   )











"""simple docstring"""







def 							lowercase   (snake_case__				:	list	)       ->					bool:


				'''simple docstring'''






				if not isinstance(snake_case__ ,    snake_case__	):
								raise ValueError("""Input series is not valid, valid series - [2, 4, 8]"""	)
				if len(snake_case__	) == 0:
								raise ValueError("""Input list must be a non empty list"""	)
				if len(snake_case__	) == 1:
								return True
				try:
								lowerCAmelCase		=			series[1] / series[0]
								for index in range(len(snake_case__	) - 1	):
												if series[index + 1] / series[index] != common_ratio:
																return False
				except ZeroDivisionError:
								return False
				return True





def 							lowercase   (snake_case__				:	list	)       ->					float:


				'''simple docstring'''






				if not isinstance(snake_case__ ,    snake_case__	):
								raise ValueError("""Input series is not valid, valid series - [2, 4, 8]"""	)
				if len(snake_case__	) == 0:
								raise ValueError("""Input list must be a non empty list"""	)
				lowerCAmelCase		=			1
				for value in series:
								answer *= value
				return pow(snake_case__ ,    1 / len(snake_case__	)	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()





