


"""simple docstring"""


import inspect
import unittest

import numpy as np

from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

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


if is_flax_available():
	import jax

	from transformers.models.vit.modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel
class   _UpperCamelCase  (   unittest.TestCase		):
							'''simple docstring'''







							def __init__(     self    ,   __a    ,   __a=13    ,   __a=30    ,   __a=2    ,   __a=3    ,   __a=True    ,   __a=True    ,   __a=32    ,   __a=5    ,   __a=4    ,   __a=37    ,   __a="gelu"    ,   __a=0.1    ,   __a=0.1    ,   __a=10    ,   __a=0.0_2    ,   ):
										__lowerCAmelCase				    =			parent
										__lowerCAmelCase				    =			batch_size
										__lowerCAmelCase				    =			image_size
										__lowerCAmelCase				    =			patch_size
										__lowerCAmelCase				    =			num_channels
										__lowerCAmelCase				    =			is_training
										__lowerCAmelCase				    =			use_labels
										__lowerCAmelCase				    =			hidden_size
										__lowerCAmelCase				    =			num_hidden_layers
										__lowerCAmelCase				    =			num_attention_heads
										__lowerCAmelCase				    =			intermediate_size
										__lowerCAmelCase				    =			hidden_act
										__lowerCAmelCase				    =			hidden_dropout_prob
										__lowerCAmelCase				    =			attention_probs_dropout_prob
										__lowerCAmelCase				    =			type_sequence_label_size
										__lowerCAmelCase				    =			initializer_range

										# in ViT, the seq length equals the number of patches + 1 (we add 1 for the [CLS] token)
										__lowerCAmelCase				    =			(image_size // patch_size) ** 2
										__lowerCAmelCase				    =			num_patches + 1

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]	)

										__lowerCAmelCase				    =			ViTConfig(
										    image_size=self.image_size    ,   patch_size=self.patch_size    ,   num_channels=self.num_channels    ,   hidden_size=self.hidden_size    ,   num_hidden_layers=self.num_hidden_layers    ,   num_attention_heads=self.num_attention_heads    ,   intermediate_size=self.intermediate_size    ,   hidden_act=self.hidden_act    ,   hidden_dropout_prob=self.hidden_dropout_prob    ,   attention_probs_dropout_prob=self.attention_probs_dropout_prob    ,   is_decoder=__a    ,   initializer_range=self.initializer_range    ,   )

										return config, pixel_values

							def 			snake_case				(     self    ,   __a    ,   __a	):
										__lowerCAmelCase				    =			FlaxViTModel(config=__a	)
										__lowerCAmelCase				    =			model(__a	)
										# expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
										__lowerCAmelCase				    =			(self.image_size, self.image_size)
										__lowerCAmelCase				    =			(self.patch_size, self.patch_size)
										__lowerCAmelCase				    =			(image_size[1] // patch_size[1]) * (image_size[0] // patch_size[0])
										self.parent.assertEqual(result.last_hidden_state.shape    ,   (self.batch_size, num_patches + 1, self.hidden_size)	)

							def 			snake_case				(     self    ,   __a    ,   __a	):
										__lowerCAmelCase				    =			self.type_sequence_label_size
										__lowerCAmelCase				    =			FlaxViTForImageClassification(config=__a	)
										__lowerCAmelCase				    =			model(__a	)
										self.parent.assertEqual(result.logits.shape    ,   (self.batch_size, self.type_sequence_label_size)	)

										# test greyscale images
										__lowerCAmelCase				    =			1
										__lowerCAmelCase				    =			FlaxViTForImageClassification(__a	)

										__lowerCAmelCase				    =			floats_tensor([self.batch_size, 1, self.image_size, self.image_size]	)
										__lowerCAmelCase				    =			model(__a	)



							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.prepare_config_and_inputs()
										(
										    (
										    __lowerCAmelCase
										)    ,	(
										    __lowerCAmelCase
										)    ,	
										)				    =			config_and_inputs
										__lowerCAmelCase				    =			{"pixel_values": pixel_values}
										return config, inputs_dict
@require_flax
class   _UpperCamelCase  (   lowerCAmelCase__       ,unittest.TestCase		):
							'''simple docstring'''







							__UpperCAmelCase						:    int				      =(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			FlaxViTModelTester(self	)
										__lowerCAmelCase				    =			ConfigTester(self    ,   config_class=__a    ,   has_text_modality=__a    ,   hidden_size=37	)

							def 			snake_case				(     self	):
										self.config_tester.run_common_tests()

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_model(*__a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.model_tester.prepare_config_and_inputs()
										self.model_tester.create_and_check_for_image_classification(*__a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase    ,	__lowerCAmelCase				    =			self.model_tester.prepare_config_and_inputs_for_common()

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

													__lowerCAmelCase				    =			["pixel_values"]
													self.assertListEqual(arg_names[:1]    ,   __a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase    ,	__lowerCAmelCase				    =			self.model_tester.prepare_config_and_inputs_for_common()

										for model_class in self.all_model_classes:
													with self.subTest(model_class.__name__	):
																__lowerCAmelCase				    =			self._prepare_for_class(__a    ,   __a	)
																__lowerCAmelCase				    =			model_class(__a	)

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

																with self.subTest("JIT Enabled"	):
																			__lowerCAmelCase				    =			model_jitted(**__a	).to_tuple()

																with self.subTest("JIT Disabled"	):
																			with jax.disable_jit():
																						__lowerCAmelCase				    =			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	)



							@slow
							def 			snake_case				(     self	):
										for model_class_name in self.all_model_classes:
													__lowerCAmelCase				    =			model_class_name.from_pretrained("google/vit-base-patch16-224"	)
													__lowerCAmelCase				    =			model(np.ones((1, 3, 2_24, 2_24)	)	)
													self.assertIsNotNone(__a	)








"""simple docstring"""







def    UpperCAmelCase__       (lowerCAmelCase_   ):




					'''simple docstring'''


					if number > 0:
										raise ValueError("input must be a negative integer"   )
					__SCREAMING_SNAKE_CASE						   =				len(bin(lowerCAmelCase_   )[3:]   )
					__SCREAMING_SNAKE_CASE						   =				bin(abs(lowerCAmelCase_   ) - (1 << binary_number_length)   )[3:]
					__SCREAMING_SNAKE_CASE						   =				(
					    (
					        "1"
					        + "0" * (binary_number_length - len(lowerCAmelCase_   ))
					        + twos_complement_number
					    )
					    if number < 0
					    else "0"
					)
					return "0b" + twos_complement_number


if __name__ == "__main__":
		import doctest

		doctest.testmod()
