






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		:       Optional[Any],    lowerCamelCase		:       Dict,    lowerCamelCase		:       Any=3,    lowerCamelCase		:       List[str]=32,    lowerCamelCase		:       Any=3,    lowerCamelCase		:       Dict=10,    lowerCamelCase		:       Tuple=[10, 20, 30, 40],    lowerCamelCase		:       Dict=[1, 1, 2, 1],    lowerCamelCase		:       Optional[Any]=True,    lowerCamelCase		:       str=True,    lowerCamelCase		:       Optional[Any]="relu",    lowerCamelCase		:       List[Any]=3,    lowerCamelCase		:       List[Any]=None,    ):

								'''simple docstring'''
								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(lowerCamelCase    )




				def 							lowercase__  (	self		:       Optional[int]    ):

								'''simple docstring'''
								lowercase__  					=     floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]    )

								lowercase__  					=     self.get_config()

								return config, pixel_values




				def 							lowercase__  (	self		:       Union[str, Any]    ):

								'''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 							lowercase__  (	self		:       Dict,    lowerCamelCase		:       Tuple,    lowerCamelCase		:       Dict    ):

								'''simple docstring'''
								lowercase__  					=     FlaxRegNetModel(config=lowerCamelCase    )
								lowercase__  					=     model(lowerCamelCase    )

								# 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 							lowercase__  (	self		:       Any,    lowerCamelCase		:       List[Any],    lowerCamelCase		:       int    ):

								'''simple docstring'''
								lowercase__  					=     self.num_labels
								lowercase__  					=     FlaxRegNetForImageClassification(config=lowerCamelCase    )
								lowercase__  					=     model(lowerCamelCase    )
								self.parent.assertEqual(result.logits.shape,    (self.batch_size, self.num_labels)    )




				def 							lowercase__  (	self		:       int    ):

								'''simple docstring'''
								lowercase__  					=     self.prepare_config_and_inputs()
								lowercase__					,		lowercase__  					=     config_and_inputs
								lowercase__  					=     {'''pixel_values''': pixel_values}
								return config, inputs_dict



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

				"""simple docstring"""




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

				lowercase__											=			False
				lowercase__											=			False
				lowercase__											=			False




				def 							lowercase__  (	self		:       Any    ):

								'''simple docstring'''
								lowercase__  					=     FlaxRegNetModelTester(self    )
								lowercase__  					=     ConfigTester(self,    config_class=lowerCamelCase,    has_text_modality=lowerCamelCase    )




				def 							lowercase__  (	self		:       Optional[Any]    ):

								'''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 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								return




				def 							lowercase__  (	self		:       int    ):

								'''simple docstring'''
								lowercase__  					=     self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_model(*lowerCamelCase    )




				def 							lowercase__  (	self		:       Any    ):

								'''simple docstring'''
								lowercase__  					=     self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_for_image_classification(*lowerCamelCase    )




				@unittest.skip(reason='''RegNet does not use inputs_embeds'''    )
				def 							lowercase__  (	self		:       Optional[Any]    ):

								'''simple docstring'''
								pass




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

								'''simple docstring'''
								pass




				def 							lowercase__  (	self		:       List[str]    ):

								'''simple docstring'''
								lowercase__					,		lowercase__  					=     self.model_tester.prepare_config_and_inputs_for_common()

								for model_class in self.all_model_classes:
												lowercase__  					=     model_class(lowerCamelCase    )
												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],    lowerCamelCase    )




				def 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								def check_hidden_states_output(lowerCamelCase		:       Optional[int],    lowerCamelCase		:       Any,    lowerCamelCase		:       Any    ):
												lowercase__  					=     model_class(lowerCamelCase    )

												lowercase__  					=     model(**self._prepare_for_class(lowerCamelCase,    lowerCamelCase    )    )

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

												lowercase__  					=     self.model_tester.num_stages
												self.assertEqual(len(lowerCamelCase    ),    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(lowerCamelCase,    lowerCamelCase,    lowerCamelCase    )

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

												check_hidden_states_output(lowerCamelCase,    lowerCamelCase,    lowerCamelCase    )




				def 							lowercase__  (	self		:       List[Any]    ):

								'''simple docstring'''
								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(lowerCamelCase,    lowerCamelCase    )
																lowercase__  					=     model_class(lowerCamelCase    )

																@jax.jit
																def model_jitted(lowerCamelCase		:       Optional[int],    **lowerCamelCase		:       List[str]    ):
																				return model(pixel_values=lowerCamelCase,    **lowerCamelCase    )

																with self.subTest('''JIT Enabled'''    ):
																				lowercase__  					=     model_jitted(**lowerCamelCase    ).to_tuple()

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

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






def     a     (		):






				'''simple docstring'''
				lowercase__  					=     Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''							)
				return image




@require_flax
class  _UpperCAmelCase   (			unittest.TestCase      ):

				"""simple docstring"""




				@cached_property
				def 							lowercase__  (	self		:       List[str]    ):

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




				@slow
				def 							lowercase__  (	self		:       int    ):

								'''simple docstring'''
								lowercase__  					=     FlaxRegNetForImageClassification.from_pretrained('''facebook/regnet-y-040'''    )

								lowercase__  					=     self.default_image_processor
								lowercase__  					=     prepare_img()
								lowercase__  					=     image_processor(images=lowerCamelCase,    return_tensors='''np'''    )

								lowercase__  					=     model(**lowerCamelCase    )

								# verify the logits
								lowercase__  					=     (1, 1_000)
								self.assertEqual(outputs.logits.shape,    lowerCamelCase    )

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

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












import heapq as hq
import math
from collections.abc import Iterator
class  _UpperCAmelCase   :

				"""simple docstring"""




				def __init__(	self		:       str,    lowerCamelCase		:       List[Any]    ):

								'''simple docstring'''
								lowercase__  					=     str(id_    )
								lowercase__  					=     None
								lowercase__  					=     None
								lowercase__  					=     []
								lowercase__  					=     {}  # {vertex:distance}




				def __lt__(	self		:       Dict,    lowerCamelCase		:       Tuple    ):

								'''simple docstring'''
								return self.key < other.key




				def __repr__(	self		:       Dict    ):

								'''simple docstring'''
								return self.id




				def 							lowercase__  (	self		:       str,    lowerCamelCase		:       List[str]    ):

								'''simple docstring'''
								self.neighbors.append(lowerCamelCase    )




				def 							lowercase__  (	self		:       Any,    lowerCamelCase		:       Dict,    lowerCamelCase		:       Optional[Any]    ):

								'''simple docstring'''
								lowercase__  					=     weight






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				# add the neighbors:
				graph[a - 1].add_neighbor(graph[b - 1]							)
				graph[b - 1].add_neighbor(graph[a - 1]							)
				# add the edges:
				graph[a - 1].add_edge(graph[b - 1]						,  lowerCamelCase_							)
				graph[b - 1].add_edge(graph[a - 1]						,  lowerCamelCase_							)






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     []
				for u in graph:
								lowercase__  					=     math.inf
								lowercase__  					=     None
				lowercase__  					=     0
				lowercase__  					=     graph[:]
				while q:
								lowercase__  					=     min(lowerCamelCase_							)
								q.remove(lowerCamelCase_							)
								for v in u.neighbors:
												if (v in q) and (u.edges[v.id] < v.key):
																lowercase__  					=     u
																lowercase__  					=     u.edges[v.id]
				for i in range(1						,  len(lowerCamelCase_							)							):
								a.append((int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)							)
				return a






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				for u in graph:
								lowercase__  					=     math.inf
								lowercase__  					=     None
				lowercase__  					=     0

				lowercase__  					=     list(lowerCamelCase_							)
				hq.heapify(lowerCamelCase_							)

				while h:
								lowercase__  					=     hq.heappop(lowerCamelCase_							)
								for v in u.neighbors:
												if (v in h) and (u.edges[v.id] < v.key):
																lowercase__  					=     u
																lowercase__  					=     u.edges[v.id]
																hq.heapify(lowerCamelCase_							)

				for i in range(1						,  len(lowerCamelCase_							)							):
								yield (int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)






def     a     (		):






				'''simple docstring'''


if __name__ == "__main__":
							import doctest

							doctest.testmod()




