

"""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 				SCREAMING_SNAKE_CASE					(		unittest.TestCase       ):






					"""simple docstring"""



					def __init__(       self			:				int   ,lowercase_			:				List[Any]   ,lowercase_			:				int=1_3   ,lowercase_			:				Union[str, Any]=3_0   ,lowercase_			:				Tuple=2   ,lowercase_			:				str=3   ,lowercase_			:				Dict=True   ,lowercase_			:				List[Any]=True   ,lowercase_			:				str=3_2   ,lowercase_			:				Any=5   ,lowercase_			:				Optional[int]=4   ,lowercase_			:				Optional[Any]=3_7   ,lowercase_			:				List[Any]="gelu"   ,lowercase_			:				Optional[Any]=0.1   ,lowercase_			:				int=0.1   ,lowercase_			:				List[str]=1_0   ,lowercase_			:				List[str]=0.02   ,):
						lowerCAmelCase__	:						Any  				=	parent
						lowerCAmelCase__	:						int  				=	batch_size
						lowerCAmelCase__	:						Dict  				=	image_size
						lowerCAmelCase__	:						Optional[Any]  				=	patch_size
						lowerCAmelCase__	:						List[str]  				=	num_channels
						lowerCAmelCase__	:						Tuple  				=	is_training
						lowerCAmelCase__	:						int  				=	use_labels
						lowerCAmelCase__	:						Optional[int]  				=	hidden_size
						lowerCAmelCase__	:						Union[str, Any]  				=	num_hidden_layers
						lowerCAmelCase__	:						str  				=	num_attention_heads
						lowerCAmelCase__	:						str  				=	intermediate_size
						lowerCAmelCase__	:						Optional[int]  				=	hidden_act
						lowerCAmelCase__	:						Union[str, Any]  				=	hidden_dropout_prob
						lowerCAmelCase__	:						Union[str, Any]  				=	attention_probs_dropout_prob
						lowerCAmelCase__	:						Tuple  				=	type_sequence_label_size
						lowerCAmelCase__	:						str  				=	initializer_range

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







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

						lowerCAmelCase__	:						int  				=	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=lowercase_   ,initializer_range=self.initializer_range   ,)

						return config, pixel_values







					def        __lowerCAmelCase (       self			:				Optional[Any]   ,lowercase_			:				Dict   ,lowercase_			:				Union[str, Any]		):
						lowerCAmelCase__	:						List[Any]  				=	FlaxViTModel(config=lowercase_		)
						lowerCAmelCase__	:						Any  				=	model(lowercase_		)
						# expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
						lowerCAmelCase__	:						List[str]  				=	(self.image_size, self.image_size)
						lowerCAmelCase__	:						Any  				=	(self.patch_size, self.patch_size)
						lowerCAmelCase__	:						Any  				=	(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        __lowerCAmelCase (       self			:				Dict   ,lowercase_			:				Union[str, Any]   ,lowercase_			:				List[Any]		):
						lowerCAmelCase__	:						Any  				=	self.type_sequence_label_size
						lowerCAmelCase__	:						int  				=	FlaxViTForImageClassification(config=lowercase_		)
						lowerCAmelCase__	:						Optional[int]  				=	model(lowercase_		)
						self.parent.assertEqual(result.logits.shape   ,(self.batch_size, self.type_sequence_label_size)		)

						# test greyscale images
						lowerCAmelCase__	:						List[str]  				=	1
						lowerCAmelCase__	:						Optional[Any]  				=	FlaxViTForImageClassification(lowercase_		)

						lowerCAmelCase__	:						Union[str, Any]  				=	floats_tensor([self.batch_size, 1, self.image_size, self.image_size]		)
						lowerCAmelCase__	:						Optional[int]  				=	model(lowercase_		)







					def        __lowerCAmelCase (       self			:				Tuple		):
						lowerCAmelCase__	:						Tuple  				=	self.prepare_config_and_inputs()
						(
						    (
						    lowerCAmelCase__							
						)				,(
						    lowerCAmelCase__							
						)				,							
						)	:						List[str]  				=	config_and_inputs
						lowerCAmelCase__	:						Optional[Any]  				=	{'''pixel_values''': pixel_values}
						return config, inputs_dict







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






					"""simple docstring"""



					lowercase__				 =       (FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()







					def        __lowerCAmelCase (       self			:				List[Any]		):
						lowerCAmelCase__	:						int  				=	FlaxViTModelTester(self		)
						lowerCAmelCase__	:						Any  				=	ConfigTester(self   ,config_class=lowercase_   ,has_text_modality=lowercase_   ,hidden_size=3_7		)







					def        __lowerCAmelCase (       self			:				int		):
						self.config_tester.run_common_tests()







					def        __lowerCAmelCase (       self			:				str		):
						lowerCAmelCase__	:						str  				=	self.model_tester.prepare_config_and_inputs()
						self.model_tester.create_and_check_model(*lowercase_		)







					def        __lowerCAmelCase (       self			:				Dict		):
						lowerCAmelCase__	:						Union[str, Any]  				=	self.model_tester.prepare_config_and_inputs()
						self.model_tester.create_and_check_for_image_classification(*lowercase_		)







					def        __lowerCAmelCase (       self			:				Union[str, Any]		):
						lowerCAmelCase__				,lowerCAmelCase__	:						List[str]  				=	self.model_tester.prepare_config_and_inputs_for_common()

						for model_class in self.all_model_classes:
							lowerCAmelCase__	:						Optional[Any]  				=	model_class(lowercase_		)
							lowerCAmelCase__	:						Optional[int]  				=	inspect.signature(model.__call__		)
							# signature.parameters is an OrderedDict => so arg_names order is deterministic
							lowerCAmelCase__	:						Dict  				=	[*signature.parameters.keys()]

							lowerCAmelCase__	:						List[str]  				=	['''pixel_values''']
							self.assertListEqual(arg_names[:1]   ,lowercase_		)







					def        __lowerCAmelCase (       self			:				str		):
						lowerCAmelCase__				,lowerCAmelCase__	:						Tuple  				=	self.model_tester.prepare_config_and_inputs_for_common()

						for model_class in self.all_model_classes:
							with self.subTest(model_class.__name__		):
								lowerCAmelCase__	:						Union[str, Any]  				=	self._prepare_for_class(lowercase_   ,lowercase_		)
								lowerCAmelCase__	:						Any  				=	model_class(lowercase_		)

								@jax.jit
								def model_jitted(lowercase_			:				Optional[Any]   ,**lowercase_			:				Dict		):
									return model(pixel_values=lowercase_   ,**lowercase_		)

								with self.subTest('''JIT Enabled'''		):
									lowerCAmelCase__	:						Optional[Any]  				=	model_jitted(**lowercase_		).to_tuple()

								with self.subTest('''JIT Disabled'''		):
									with jax.disable_jit():
										lowerCAmelCase__	:						List[Any]  				=	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		)







					@slow
					def        __lowerCAmelCase (       self			:				Optional[Any]		):
						for model_class_name in self.all_model_classes:
							lowerCAmelCase__	:						Optional[Any]  				=	model_class_name.from_pretrained('''google/vit-base-patch16-224'''		)
							lowerCAmelCase__	:						List[str]  				=	model(np.ones((1, 3, 2_2_4, 2_2_4)		)		)
							self.assertIsNotNone(lowercase_		)








from __future__ import annotations







def        _lowerCamelCase(	lowercase__	)						->	list[int]:

		'''simple docstring'''







		__lowercase=			2
		__lowercase=			[]
		while i * i <= n:
				if n % i:
						i += 1
				else:
						n //= i
						factors.append(lowercase__	)
		if n > 1:
				factors.append(lowercase__	)
		return factors


if __name__ == "__main__":
	import doctest

	doctest.testmod()






