





class 				A_				:







       """simple docstring"""





       def __init__(    self	:	Optional[Any]  )						->					int:
         _lowercase							= 0
         _lowercase							= 0
         _lowercase							= {}







       def    __UpperCAmelCase (    self	:	Optional[int]						,__A	:	Optional[int]  )						->					Dict:
         if vertex not in self.adjacency:
           _lowercase							= {}
           self.num_vertices += 1







       def    __UpperCAmelCase (    self	:	Tuple						,__A	:	Dict						,__A	:	Tuple						,__A	:	Optional[int]  )						->					Optional[Any]:
         self.add_vertex(__A  )
         self.add_vertex(__A  )

         if head == tail:
           return

         _lowercase							= weight
         _lowercase							= weight







       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					Tuple:
         _lowercase							= self.get_edges()
         for edge in edges:
           _lowercase						,		_lowercase						,		_lowercase							= edge
           edges.remove((tail, head, weight)  )
         for i in range(len(__A  )  ):
           _lowercase							= list(edges[i]  )

         edges.sort(key=lambda __A  : e[2]  )
         for i in range(len(__A  ) - 1  ):
           if edges[i][2] >= edges[i + 1][2]:
             _lowercase							= edges[i][2] + 1
         for edge in edges:
           _lowercase						,		_lowercase						,		_lowercase							= edge
           _lowercase							= weight
           _lowercase							= weight







       def __str__(    self	:	List[str]  )						->					Optional[int]:
         _lowercase							= ''
         for tail in self.adjacency:
           for head in self.adjacency[tail]:
             _lowercase							= self.adjacency[head][tail]
             string += F"""{head} -> {tail} == {weight}\n"""
         return string.rstrip('\n'  )







       def    __UpperCAmelCase (    self	:	Dict  )						->					Optional[Any]:
         _lowercase							= []
         for tail in self.adjacency:
           for head in self.adjacency[tail]:
             output.append((tail, head, self.adjacency[head][tail])  )
         return output







       def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					Tuple:
         return self.adjacency.keys()







       @staticmethod
       def    __UpperCAmelCase (    __A	:	List[str]=None						,__A	:	Optional[Any]=None  )						->					Dict:
         _lowercase							= Graph()
         if vertices is None:
           _lowercase							= []
         if edges is None:
           _lowercase							= []
         for vertex in vertices:
           g.add_vertex(__A  )
         for edge in edges:
           g.add_edge(*__A  )
         return g





       class 				A_				:







              """simple docstring"""





              def __init__(    self	:	Dict  )						->					List[str]:
                _lowercase							= {}
                _lowercase							= {}







              def __len__(    self	:	Union[str, Any]  )						->					str:
                return len(self.parent  )







              def    __UpperCAmelCase (    self	:	str						,__A	:	Any  )						->					Dict:
                if item in self.parent:
                  return self.find(__A  )

                _lowercase							= item
                _lowercase							= 0
                return item







              def    __UpperCAmelCase (    self	:	Tuple						,__A	:	Optional[int]  )						->					Optional[int]:
                if item not in self.parent:
                  return self.make_set(__A  )
                if item != self.parent[item]:
                  _lowercase							= self.find(self.parent[item]  )
                return self.parent[item]







              def    __UpperCAmelCase (    self	:	Union[str, Any]						,__A	:	Dict						,__A	:	List[Any]  )						->					Optional[Any]:
                _lowercase							= self.find(__A  )
                _lowercase							= self.find(__A  )

                if roota == roota:
                  return roota

                if self.rank[roota] > self.rank[roota]:
                  _lowercase							= roota
                  return roota

                if self.rank[roota] < self.rank[roota]:
                  _lowercase							= roota
                  return roota

                if self.rank[roota] == self.rank[roota]:
                  self.rank[roota] += 1
                  _lowercase							= roota
                  return roota
                return None







       @staticmethod
       def    __UpperCAmelCase (    __A	:	str  )						->					Optional[Any]:
         _lowercase							= graph.num_vertices

         _lowercase							= Graph.UnionFind()
         _lowercase							= []
         while num_components > 1:
           _lowercase							= {}
           for vertex in graph.get_vertices():
             _lowercase							= -1

           _lowercase							= graph.get_edges()
           for edge in edges:
             _lowercase						,		_lowercase						,		_lowercase							= edge
             edges.remove((tail, head, weight)  )
           for edge in edges:
             _lowercase						,		_lowercase						,		_lowercase							= edge
             _lowercase							= union_find.find(__A  )
             _lowercase							= union_find.find(__A  )
             if seta != seta:
               if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                 _lowercase							= [head, tail, weight]

               if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                 _lowercase							= [head, tail, weight]
           for vertex in cheap_edge:
             if cheap_edge[vertex] != -1:
               _lowercase						,		_lowercase						,		_lowercase							= cheap_edge[vertex]
               if union_find.find(__A  ) != union_find.find(__A  ):
                 union_find.union(__A						,__A  )
                 mst_edges.append(cheap_edge[vertex]  )
                 _lowercase							= num_components - 1
         _lowercase							= Graph.build(edges=__A  )
         return mst






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 				A_				(      unittest.TestCase	):







       """simple docstring"""





       def __init__(    self	:	List[str]						,__A	:	str						,__A	:	Dict=3						,__A	:	str=32						,__A	:	int=3						,__A	:	Union[str, Any]=10						,__A	:	Optional[Any]=[10, 20, 30, 40]						,__A	:	List[str]=[1, 1, 2, 1]						,__A	:	Optional[int]=True						,__A	:	Optional[Any]=True						,__A	:	int="relu"						,__A	:	Union[str, Any]=3						,__A	:	List[Any]=None						,)						->					int:
         _lowercase							= parent
         _lowercase							= batch_size
         _lowercase							= image_size
         _lowercase							= num_channels
         _lowercase							= embeddings_size
         _lowercase							= hidden_sizes
         _lowercase							= depths
         _lowercase							= is_training
         _lowercase							= use_labels
         _lowercase							= hidden_act
         _lowercase							= num_labels
         _lowercase							= scope
         _lowercase							= len(__A  )







       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					Any:
         _lowercase							= floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]  )

         _lowercase							= self.get_config()

         return config, pixel_values







       def    __UpperCAmelCase (    self	:	Any  )						->					int:
         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    __UpperCAmelCase (    self	:	Tuple						,__A	:	Any						,__A	:	Union[str, Any]  )						->					List[Any]:
         _lowercase							= FlaxRegNetModel(config=__A  )
         _lowercase							= model(__A  )

         # 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    __UpperCAmelCase (    self	:	List[Any]						,__A	:	Optional[int]						,__A	:	Dict  )						->					Any:
         _lowercase							= self.num_labels
         _lowercase							= FlaxRegNetForImageClassification(config=__A  )
         _lowercase							= model(__A  )
         self.parent.assertEqual(result.logits.shape						,(self.batch_size, self.num_labels)  )







       def    __UpperCAmelCase (    self	:	Tuple  )						->					Any:
         _lowercase							= self.prepare_config_and_inputs()
         _lowercase						,		_lowercase							= config_and_inputs
         _lowercase							= {'pixel_values': pixel_values}
         return config, inputs_dict





@require_flax
class 				A_				(      UpperCAmelCase					,	unittest.TestCase	):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_      : Tuple      =  (FlaxRegNetModel, FlaxRegNetForImageClassification) if is_flax_available() else ()

       SCREAMING_SNAKE_CASE_      : Union[str, Any]      =  False
       SCREAMING_SNAKE_CASE_      : Any      =  False
       SCREAMING_SNAKE_CASE_      : Union[str, Any]      =  False







       def    __UpperCAmelCase (    self	:	Dict  )						->					None:
         _lowercase							= FlaxRegNetModelTester(self  )
         _lowercase							= ConfigTester(self						,config_class=__A						,has_text_modality=__A  )







       def    __UpperCAmelCase (    self	:	List[str]  )						->					Union[str, Any]:
         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    __UpperCAmelCase (    self	:	Optional[int]  )						->					Any:
         return







       def    __UpperCAmelCase (    self	:	Dict  )						->					int:
         _lowercase							= self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*__A  )







       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					Any:
         _lowercase							= self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_image_classification(*__A  )







       @unittest.skip(reason='RegNet does not use inputs_embeds'  )
       def    __UpperCAmelCase (    self	:	List[str]  )						->					Optional[int]:
         pass







       @unittest.skip(reason='RegNet does not support input and output embeddings'  )
       def    __UpperCAmelCase (    self	:	Tuple  )						->					Any:
         pass







       def    __UpperCAmelCase (    self	:	Dict  )						->					List[str]:
         _lowercase						,		_lowercase							= self.model_tester.prepare_config_and_inputs_for_common()

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

           _lowercase							= ['pixel_values']
           self.assertListEqual(arg_names[:1]						,__A  )







       def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					List[str]:
         def check_hidden_states_output(__A	:	Optional[Any]						,__A	:	Optional[int]						,__A	:	str  ):
           _lowercase							= model_class(__A  )

           _lowercase							= model(**self._prepare_for_class(__A						,__A  )  )

           _lowercase							= outputs.encoder_hidden_states if config.is_encoder_decoder else outputs.hidden_states

           _lowercase							= self.model_tester.num_stages
           self.assertEqual(len(__A  )						,expected_num_stages + 1  )

         _lowercase						,		_lowercase							= self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
           _lowercase							= True
           check_hidden_states_output(__A						,__A						,__A  )

           # check that output_hidden_states also work using config
           del inputs_dict["output_hidden_states"]
           _lowercase							= True

           check_hidden_states_output(__A						,__A						,__A  )







       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					int:
         _lowercase						,		_lowercase							= self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
           with self.subTest(model_class.__name__  ):
             _lowercase							= self._prepare_for_class(__A						,__A  )
             _lowercase							= model_class(__A  )

             @jax.jit
             def model_jitted(__A	:	Any						,**__A	:	Union[str, Any]  ):
               return model(pixel_values=__A						,**__A  )

             with self.subTest('JIT Enabled'  ):
               _lowercase							= model_jitted(**__A  ).to_tuple()

             with self.subTest('JIT Disabled'  ):
               with jax.disable_jit():
                 _lowercase							= model_jitted(**__A  ).to_tuple()

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

def 							SCREAMING_SNAKE_CASE__       (  )      ->						str:
  _lowercase							= Image.open('./tests/fixtures/tests_samples/COCO/000000039769.png'     )
  return image







@require_flax
class 				A_				(      unittest.TestCase	):







       """simple docstring"""





       @cached_property
       def    __UpperCAmelCase (    self	:	str  )						->					Any:
         return AutoImageProcessor.from_pretrained('facebook/regnet-y-040'  ) if is_vision_available() else None







       @slow
       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					Any:
         _lowercase							= FlaxRegNetForImageClassification.from_pretrained('facebook/regnet-y-040'  )

         _lowercase							= self.default_image_processor
         _lowercase							= prepare_img()
         _lowercase							= image_processor(images=__A						,return_tensors='np'  )

         _lowercase							= model(**__A  )

         # verify the logits
         _lowercase							= (1, 1000)
         self.assertEqual(outputs.logits.shape						,__A  )

         _lowercase							= jnp.array([-0.4180, -1.5051, -3.4836]  )

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