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      __lowercase					(    unittest.TestCase    ):

						def __init__(	self				:      List[Any]							,							__lowerCamelCase				:      List[str]							,							__lowerCamelCase				:      List[Any]=3							,							__lowerCamelCase				:      List[str]=32							,							__lowerCamelCase				:      Tuple=3							,							__lowerCamelCase				:      Any=10							,							__lowerCamelCase				:      Optional[Any]=[10, 20, 30, 40]							,							__lowerCamelCase				:      int=[1, 1, 2, 1]							,							__lowerCamelCase				:      List[str]=True							,							__lowerCamelCase				:      List[Any]=True							,							__lowerCamelCase				:      Tuple="relu"							,							__lowerCamelCase				:      Dict=3							,							__lowerCamelCase				:      Dict=None							,							)							->		Any:


									'''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        __a		(	self				:      Optional[Any]   )							->		List[str]:


									'''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        __a		(	self				:      List[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        __a		(	self				:      List[Any]							,							__lowerCamelCase				:      int							,							__lowerCamelCase				:      Tuple   )							->		Union[str, Any]:


									'''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        __a		(	self				:      Dict							,							__lowerCamelCase				:      Union[str, Any]							,							__lowerCamelCase				:      Optional[Any]   )							->		Optional[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        __a		(	self				:      int   )							->		Any:


									'''simple docstring'''

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






@require_flax
class      __lowercase					(    lowerCamelCase__       ,     unittest.TestCase    ):
						lowercase					 =     (FlaxRegNetModel, FlaxRegNetForImageClassification) if is_flax_available() else ()

						lowercase					 =     False
						lowercase					 =     False
						lowercase					 =     False

						def        __a		(	self				:      List[Any]   )							->		None:


									'''simple docstring'''

									lowercase							=		FlaxRegNetModelTester(self   )
									lowercase							=		ConfigTester(self							,							config_class=__lowerCamelCase							,							has_text_modality=__lowerCamelCase   )

						def        __a		(	self				:      Optional[Any]   )							->		str:


									'''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        __a		(	self				:      List[str]   )							->		Tuple:


									'''simple docstring'''

									return

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


									'''simple docstring'''

									lowercase							=		self.model_tester.prepare_config_and_inputs()
									self.model_tester.create_and_check_model(*__lowerCamelCase   )

						def        __a		(	self				:      Tuple   )							->		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        __a		(	self				:      Dict   )							->		Dict:


									'''simple docstring'''

									pass

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


									'''simple docstring'''

									pass

						def        __a		(	self				:      List[str]   )							->		List[Any]:


									'''simple docstring'''

									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        __a		(	self				:      Dict   )							->		Union[str, Any]:


									'''simple docstring'''

									def check_hidden_states_output(__lowerCamelCase				:      Optional[int]							,							__lowerCamelCase				:      Optional[Any]							,							__lowerCamelCase				:      Union[str, 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							=		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        __a		(	self				:      Union[str, Any]   )							->		Optional[Any]:


									'''simple docstring'''

									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				:      List[str]							,							**__lowerCamelCase				:      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        __UpperCAmelCase    (       )->       Tuple:



			"""simple docstring"""







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






@require_flax
class      __lowercase					(    unittest.TestCase    ):

						@cached_property
						def        __a		(	self				:      Union[str, Any]   )							->		Optional[int]:


									'''simple docstring'''

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



						@slow
						def        __a		(	self				:      int   )							->		Any:


									'''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, 10_00)
									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 cmath
import math






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase,		UpperCAmelCase       )->       complex:



			"""simple docstring"""







			lowercase							=		math.radians(UpperCAmelCase       )
			lowercase							=		math.radians(UpperCAmelCase       )

			# Convert voltage and current to rectangular form
			lowercase							=		cmath.rect(UpperCAmelCase,		UpperCAmelCase       )
			lowercase							=		cmath.rect(UpperCAmelCase,		UpperCAmelCase       )

			# Calculate apparent power
			return voltage_rect * current_rect


if __name__ == "__main__":
						import doctest

						doctest.testmod()





