import copy
import inspect

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




@require_torch
class        lowercase_  :



	"""simple docstring"""





	UpperCAmelCase_  : int       =    ()
	UpperCAmelCase_  : List[Any]       =    True


	def       SCREAMING_SNAKE_CASE_    (							self    )						->Optional[int]:
								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       SCREAMING_SNAKE_CASE_    (							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    )
															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       SCREAMING_SNAKE_CASE_    (							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       SCREAMING_SNAKE_CASE_    (							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    )
															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       SCREAMING_SNAKE_CASE_    (							self    )						->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       SCREAMING_SNAKE_CASE_    (							self    )						->Optional[Any]:
								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    )




import warnings

from .generation import FlaxGenerationMixin




class        lowercase_  (  UpperCamelCase_						):



	"""simple docstring"""





	warnings.warn(
	    """Importing `FlaxGenerationMixin` from `src/transformers/generation_flax_utils.py` is deprecated and will """
	    """be removed in Transformers v5. Import as `from transformers import FlaxGenerationMixin` instead."""				,					UpperCamelCase_				,					)



