


"""simple docstring"""
import inspect
import unittest

from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available

from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor


if is_flax_available():
			import jax
			import jax.numpy as jnp

			from transformers.models.regnet.modeling_flax_regnet import FlaxRegNetForImageClassification, FlaxRegNetModel

if is_vision_available():
			from PIL import Image

			from transformers import AutoImageProcessor



class 			_UpperCAmelCase (							unittest.TestCase				):






		'''simple docstring'''

		def __init__(self				,       a_				,       a_=3				,       a_=32				,       a_=3				,       a_=10				,       a_=[10, 20, 30, 40]				,       a_=[1, 1, 2, 1]				,       a_=True				,       a_=True				,       a_="relu"				,       a_=3				,       a_=None				,       ):





			'''simple docstring'''

			__snake_case	:						Any						=				parent
			__snake_case	:						Optional[Any]						=				batch_size
			__snake_case	:						Optional[int]						=				image_size
			__snake_case	:						str						=				num_channels
			__snake_case	:						List[Any]						=				embeddings_size
			__snake_case	:						Any						=				hidden_sizes
			__snake_case	:						List[Any]						=				depths
			__snake_case	:						List[Any]						=				is_training
			__snake_case	:						List[Any]						=				use_labels
			__snake_case	:						Dict						=				hidden_act
			__snake_case	:						List[Any]						=				num_labels
			__snake_case	:						int						=				scope
			__snake_case	:						List[str]						=				len(lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Optional[Any]						=				floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]					)

			__snake_case	:						Union[str, Any]						=				self.get_config()

			return config, pixel_values



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			return RegNetConfig(
			    num_channels=self.num_channels				,       embeddings_size=self.embeddings_size				,       hidden_sizes=self.hidden_sizes				,       depths=self.depths				,       hidden_act=self.hidden_act				,       num_labels=self.num_labels				,       image_size=self.image_size				,       )



		def 				SCREAMING_SNAKE_CASE  (self				,       a_				,       a_					):





			'''simple docstring'''

			__snake_case	:						Union[str, Any]						=				FlaxRegNetModel(config=lowercase_					)
			__snake_case	:						Any						=				model(lowercase_					)

			# Output shape (b, c, h, w)
			self.parent.assertEqual(
			    result.last_hidden_state.shape				,       (self.batch_size, self.hidden_sizes[-1], self.image_size // 32, self.image_size // 32)				,       )



		def 				SCREAMING_SNAKE_CASE  (self				,       a_				,       a_					):





			'''simple docstring'''

			__snake_case	:						Any						=				self.num_labels
			__snake_case	:						List[Any]						=				FlaxRegNetForImageClassification(config=lowercase_					)
			__snake_case	:						Optional[int]						=				model(lowercase_					)
			self.parent.assertEqual(result.logits.shape				,       (self.batch_size, self.num_labels)					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Union[str, Any]						=				self.prepare_config_and_inputs()
			__snake_case	:						List[str]						=				config_and_inputs
			__snake_case	:						int						=				{'pixel_values': pixel_values}
			return config, inputs_dict



@require_flax
class 			_UpperCAmelCase (							UpperCamelCase_,				unittest.TestCase				):






		'''simple docstring'''

		lowerCamelCase__				=(FlaxRegNetModel, FlaxRegNetForImageClassification) if is_flax_available() else ()

		lowerCamelCase__				=False
		lowerCamelCase__				=False
		lowerCamelCase__				=False



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						str						=				FlaxRegNetModelTester(self					)
			__snake_case	:						List[str]						=				ConfigTester(self				,       config_class=lowercase_				,       has_text_modality=lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			self.create_and_test_config_common_properties()
			self.config_tester.create_and_test_config_to_json_string()
			self.config_tester.create_and_test_config_to_json_file()
			self.config_tester.create_and_test_config_from_and_save_pretrained()
			self.config_tester.create_and_test_config_with_num_labels()
			self.config_tester.check_config_can_be_init_without_params()
			self.config_tester.check_config_arguments_init()



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			return



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Tuple						=				self.model_tester.prepare_config_and_inputs()
			self.model_tester.create_and_check_model(*lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Union[str, Any]						=				self.model_tester.prepare_config_and_inputs()
			self.model_tester.create_and_check_for_image_classification(*lowercase_					)



		@unittest.skip(reason='''RegNet does not use inputs_embeds'''					)
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			pass



		@unittest.skip(reason='''RegNet does not support input and output embeddings'''					)
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			pass



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						str						=				self.model_tester.prepare_config_and_inputs_for_common()

			for model_class in self.all_model_classes:
				__snake_case	:						List[str]						=				model_class(lowercase_					)
				__snake_case	:						Tuple						=				inspect.signature(model.__call__					)
				# signature.parameters is an OrderedDict => so arg_names order is deterministic
				__snake_case	:						List[str]						=				[*signature.parameters.keys()]

				__snake_case	:						str						=				['pixel_values']
				self.assertListEqual(arg_names[:1]				,       lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			def check_hidden_states_output(a_				,       a_				,       a_					):
				__snake_case	:						Optional[Any]						=				model_class(lowercase_					)

				__snake_case	:						List[str]						=				model(**self._prepare_for_class(lowercase_				,       lowercase_					)					)

				__snake_case	:						int						=				outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

				__snake_case	:						Optional[Any]						=				self.model_tester.num_stages
				self.assertEqual(len(lowercase_					)				,       expected_num_stages + 1					)

			__snake_case	:						List[str]						=				self.model_tester.prepare_config_and_inputs_for_common()

			for model_class in self.all_model_classes:
				__snake_case	:						Any						=				True
				check_hidden_states_output(lowercase_				,       lowercase_				,       lowercase_					)

				# check that output_hidden_states also work using config
				del inputs_dict["output_hidden_states"]
				__snake_case	:						Optional[int]						=				True

				check_hidden_states_output(lowercase_				,       lowercase_				,       lowercase_					)



		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						Any						=				self.model_tester.prepare_config_and_inputs_for_common()

			for model_class in self.all_model_classes:
				with self.subTest(model_class.__name__					):
					__snake_case	:						Optional[Any]						=				self._prepare_for_class(lowercase_				,       lowercase_					)
					__snake_case	:						Optional[Any]						=				model_class(lowercase_					)

					@jax.jit
					def model_jitted(a_				,       **a_					):
						return model(pixel_values=lowercase_				,       **lowercase_					)

					with self.subTest('''JIT Enabled'''					):
						__snake_case	:						Any						=				model_jitted(**lowercase_					).to_tuple()

					with self.subTest('''JIT Disabled'''					):
						with jax.disable_jit():
							__snake_case	:						Union[str, Any]						=				model_jitted(**lowercase_					).to_tuple()

					self.assertEqual(len(lowercase_					)				,       len(lowercase_					)					)
					for jitted_output, output in zip(lowercase_				,       lowercase_					):
						self.assertEqual(jitted_output.shape				,       output.shape					)






def 		lowercase							(     )     ->int:
	"""simple docstring"""





	__snake_case	:						Any						=				Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''     )
	return image



@require_flax
class 			_UpperCAmelCase (							unittest.TestCase				):






		'''simple docstring'''

		@cached_property
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			return AutoImageProcessor.from_pretrained('''facebook/regnet-y-040'''					) if is_vision_available() else None



		@slow
		def 				SCREAMING_SNAKE_CASE  (self					):





			'''simple docstring'''

			__snake_case	:						List[str]						=				FlaxRegNetForImageClassification.from_pretrained('''facebook/regnet-y-040'''					)

			__snake_case	:						List[Any]						=				self.default_image_processor
			__snake_case	:						Optional[int]						=				prepare_img()
			__snake_case	:						int						=				image_processor(images=lowercase_				,       return_tensors='''np'''					)

			__snake_case	:						Optional[int]						=				model(**lowercase_					)

			# verify the logits
			__snake_case	:						List[str]						=				(1, 10_00)
			self.assertEqual(outputs.logits.shape				,       lowercase_					)

			__snake_case	:						Dict						=				jnp.array([-0.4180, -1.5051, -3.4836]					)

			self.assertTrue(jnp.allclose(outputs.logits[0, :3]				,       lowercase_				,       atol=1E-4					)					)









# using dfs for finding eulerian path traversal




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Any		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      Optional[int]=None     ):
       '''simple docstring'''





       _lowerCamelCase       :		Optional[Any]		=(path or []) + [u]
       for v in graph[u]:
              if visited_edge[u][v] is False:
                     _lowerCamelCase	,     _lowerCamelCase       :		Dict		=True, True
                     _lowerCamelCase       :		Optional[Any]		=dfs(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       return path




def 	a_      (    SCREAMING_SNAKE_CASE__					:      List[str]		,			SCREAMING_SNAKE_CASE__					:      Optional[Any]     ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		=0
       _lowerCamelCase       :		Union[str, Any]		=-1
       for i in range(SCREAMING_SNAKE_CASE__     ):
              if i not in graph.keys():
                     continue
              if len(graph[i]     ) % 2 == 1:
                     odd_degree_nodes += 1
                     _lowerCamelCase       :		Tuple		=i
       if odd_degree_nodes == 0:
              return 1, odd_node
       if odd_degree_nodes == 2:
              return 2, odd_node
       return 3, odd_node




def 	a_      (    SCREAMING_SNAKE_CASE__					:      Union[str, Any]		,			SCREAMING_SNAKE_CASE__					:      Any     ):
       '''simple docstring'''





       _lowerCamelCase       :		Tuple		=[[False for _ in range(max_node + 1     )] for _ in range(max_node + 1     )]
       _lowerCamelCase	,     _lowerCamelCase       :		Optional[int]		=check_circuit_or_path(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       if check == 3:
              print('graph is not Eulerian'     )
              print('no path'     )
              return
       _lowerCamelCase       :		Any		=1
       if check == 2:
              _lowerCamelCase       :		Tuple		=odd_node
              print('graph has a Euler path'     )
       if check == 1:
              print('graph has a Euler cycle'     )
       _lowerCamelCase       :		int		=dfs(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       print(SCREAMING_SNAKE_CASE__     )




def 	a_      (    ):
       '''simple docstring'''





       _lowerCamelCase       :		Union[str, Any]		={1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
       _lowerCamelCase       :		str		={1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
       _lowerCamelCase       :		List[Any]		={1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
       _lowerCamelCase       :		Any		={1: [2, 3], 2: [1, 3], 3: [1, 2]}
       _lowerCamelCase       :		Dict		={
           1: [],
           2: []
           # all degree is zero
       }
       _lowerCamelCase       :		str		=10
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )
       check_euler(SCREAMING_SNAKE_CASE__		,			SCREAMING_SNAKE_CASE__     )


if __name__ == "__main__":
 main()


