"""simple docstring"""







import inspect
import unittest

from transformers import ResNetConfig, 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.resnet.modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel

if is_vision_available():
						from PIL import Image

						from transformers import AutoImageProcessor


class       _lowercase		( unittest.TestCase	):

				def __init__(  self							:     Union[str, Any]							,     _lowercase							:     List[Any]							,     _lowercase							:     Tuple=3							,     _lowercase							:     str=3_2							,     _lowercase							:     List[str]=3							,     _lowercase							:     int=1_0							,     _lowercase							:     List[Any]=[1_0, 2_0, 3_0, 4_0]							,     _lowercase							:     Dict=[1, 1, 2, 1]							,     _lowercase							:     Any=True							,     _lowercase							:     Any=True							,     _lowercase							:     List[str]="relu"							,     _lowercase							:     int=3							,     _lowercase							:     Optional[Any]=None							,     ):


										'''simple docstring'''
										UpperCAmelCase__       						=		parent
										UpperCAmelCase__       						=		batch_size
										UpperCAmelCase__       						=		image_size
										UpperCAmelCase__       						=		num_channels
										UpperCAmelCase__       						=		embeddings_size
										UpperCAmelCase__       						=		hidden_sizes
										UpperCAmelCase__       						=		depths
										UpperCAmelCase__       						=		is_training
										UpperCAmelCase__       						=		use_labels
										UpperCAmelCase__       						=		hidden_act
										UpperCAmelCase__       						=		num_labels
										UpperCAmelCase__       						=		scope
										UpperCAmelCase__       						=		len(_lowercase  )

				def 							A			(  self							:     List[Any]  ):


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

										UpperCAmelCase__       						=		self.get_config()

										return config, pixel_values

				def 							A			(  self							:     Optional[Any]  ):


										'''simple docstring'''
										return ResNetConfig(
										    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[str]							,     _lowercase							:     Optional[int]							,     _lowercase							:     Union[str, Any]  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		FlaxResNetModel(config=_lowercase  )
										UpperCAmelCase__       						=		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 // 3_2, self.image_size // 3_2)							,     )

				def 							A			(  self							:     Union[str, Any]							,     _lowercase							:     List[Any]							,     _lowercase							:     Union[str, Any]  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		self.num_labels
										UpperCAmelCase__       						=		FlaxResNetForImageClassification(config=_lowercase  )
										UpperCAmelCase__       						=		model(_lowercase  )
										self.parent.assertEqual(result.logits.shape							,     (self.batch_size, self.num_labels)  )

				def 							A			(  self							:     Any  ):


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


@require_flax
class       _lowercase		( __lowerCamelCase   ,   unittest.TestCase	):
				lowerCamelCase__							=							(FlaxResNetModel, FlaxResNetForImageClassification) if is_flax_available() else ()

				lowerCamelCase__							=							False
				lowerCamelCase__							=							False
				lowerCamelCase__							=							False

				def 							A			(  self							:     List[Any]  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		FlaxResNetModelTester(self  )
										UpperCAmelCase__       						=		ConfigTester(self							,     config_class=_lowercase							,     has_text_modality=_lowercase  )

				def 							A			(  self							:     List[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							:     str  ):


										'''simple docstring'''
										return

				def 							A			(  self							:     List[Any]  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_model(*_lowercase  )

				def 							A			(  self							:     Any  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_for_image_classification(*_lowercase  )

				@unittest.skip(reason="""ResNet does not use inputs_embeds"""  )
				def 							A			(  self							:     Any  ):


										'''simple docstring'''
										pass

				@unittest.skip(reason="""ResNet does not support input and output embeddings"""  )
				def 							A			(  self							:     Optional[int]  ):


										'''simple docstring'''
										pass

				def 							A			(  self							:     Any  ):


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

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

																UpperCAmelCase__       						=		["""pixel_values"""]
																self.assertListEqual(arg_names[:1]							,     _lowercase  )

				def 							A			(  self							:     Tuple  ):


										'''simple docstring'''
										def check_hidden_states_output(_lowercase							:     Optional[int]							,     _lowercase							:     int							,     _lowercase							:     int  ):
																UpperCAmelCase__       						=		model_class(_lowercase  )

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

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

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

				@unittest.skip(reason="""ResNet does not use feedforward chunking"""  )
				def 							A			(  self							:     List[str]  ):


										'''simple docstring'''
										pass

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


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

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

																						@jax.jit
																						def model_jitted(_lowercase							:     int							,     **_lowercase							:     Any  ):
																												return model(pixel_values=_lowercase							,     **_lowercase  )

																						with self.subTest("""JIT Enabled"""  ):
																												UpperCAmelCase__       						=		model_jitted(**_lowercase  ).to_tuple()

																						with self.subTest("""JIT Disabled"""  ):
																												with jax.disable_jit():
																																		UpperCAmelCase__       						=		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 	a__   (		)->						List[Any]:
						UpperCAmelCase__       						=		Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""      )
						return image







@require_flax
class       _lowercase		( unittest.TestCase	):

				@cached_property
				def 							A			(  self							:     Tuple  ):


										'''simple docstring'''
										return AutoImageProcessor.from_pretrained("""microsoft/resnet-50"""  ) if is_vision_available() else None

				@slow
				def 							A			(  self							:     Dict  ):


										'''simple docstring'''
										UpperCAmelCase__       						=		FlaxResNetForImageClassification.from_pretrained("""microsoft/resnet-50"""  )

										UpperCAmelCase__       						=		self.default_image_processor
										UpperCAmelCase__       						=		prepare_img()
										UpperCAmelCase__       						=		image_processor(images=_lowercase							,     return_tensors="""np"""  )

										UpperCAmelCase__       						=		model(**_lowercase  )

										# verify the logits
										UpperCAmelCase__       						=		(1, 1_0_0_0)
										self.assertEqual(outputs.logits.shape							,     _lowercase  )

										UpperCAmelCase__       						=		jnp.array([-11.1069, -9.7877, -8.3777]  )

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


"""simple docstring"""







def 	a__   (		UpperCAmelCase__							:      list[int]      )->						int:
						UpperCAmelCase__       						=		len(UpperCAmelCase__      )
						if n in (0, 1):
												return 0
						return sum(query * (n - i - 1) for i, query in enumerate(sorted(UpperCAmelCase__      )      )      )


if __name__ == "__main__":
						import doctest

						doctest.testmod()

