


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 			_lowercase (							unittest.TestCase):


       """simple docstring"""




       def __init__(   self							:			Optional[Any]					,      __lowerCamelCase							:			Optional[int]					,      __lowerCamelCase							:			int=13					,      __lowerCamelCase							:			List[Any]=30					,      __lowerCamelCase							:			int=2					,      __lowerCamelCase							:			Dict=3					,      __lowerCamelCase							:			int=True					,      __lowerCamelCase							:			Optional[Any]=True					,      __lowerCamelCase							:			List[str]=32					,      __lowerCamelCase							:			Optional[Any]=5					,      __lowerCamelCase							:			Union[str, Any]=4					,      __lowerCamelCase							:			Tuple=37					,      __lowerCamelCase							:			str="gelu"					,      __lowerCamelCase							:			Dict=0.1					,      __lowerCamelCase							:			Optional[int]=0.1					,      __lowerCamelCase							:			Optional[Any]=10					,      __lowerCamelCase							:			Optional[Any]=0.0_2					,      ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[Any]    =  parent
             lowerCamelCase__		:				Union[str, Any]    =  batch_size
             lowerCamelCase__		:				Dict    =  image_size
             lowerCamelCase__		:				str    =  patch_size
             lowerCamelCase__		:				str    =  num_channels
             lowerCamelCase__		:				Tuple    =  is_training
             lowerCamelCase__		:				List[str]    =  use_labels
             lowerCamelCase__		:				Tuple    =  hidden_size
             lowerCamelCase__		:				Any    =  num_hidden_layers
             lowerCamelCase__		:				Optional[int]    =  num_attention_heads
             lowerCamelCase__		:				List[Any]    =  intermediate_size
             lowerCamelCase__		:				Any    =  hidden_act
             lowerCamelCase__		:				Any    =  hidden_dropout_prob
             lowerCamelCase__		:				Any    =  attention_probs_dropout_prob
             lowerCamelCase__		:				List[Any]    =  type_sequence_label_size
             lowerCamelCase__		:				Any    =  initializer_range

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





       def 						lowerCAmelCase     (   self							:			Tuple       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]       )

             lowerCamelCase__		:				str    =  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=__lowerCamelCase					,      initializer_range=self.initializer_range					,      )

             return config, pixel_values





       def 						lowerCAmelCase     (   self							:			List[str]					,      __lowerCamelCase							:			Tuple					,      __lowerCamelCase							:			Any       ):


             '''simple docstring'''



             lowerCamelCase__		:				List[Any]    =  FlaxViTModel(config=__lowerCamelCase       )
             lowerCamelCase__		:				str    =  model(__lowerCamelCase       )
             # expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
             lowerCamelCase__		:				Tuple    =  (self.image_size, self.image_size)
             lowerCamelCase__		:				str    =  (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							:			Optional[int]					,      __lowerCamelCase							:			List[Any]					,      __lowerCamelCase							:			Any       ):


             '''simple docstring'''



             lowerCamelCase__		:				Dict    =  self.type_sequence_label_size
             lowerCamelCase__		:				Any    =  FlaxViTForImageClassification(config=__lowerCamelCase       )
             lowerCamelCase__		:				Any    =  model(__lowerCamelCase       )
             self.parent.assertEqual(result.logits.shape					,      (self.batch_size, self.type_sequence_label_size)       )

             # test greyscale images
             lowerCamelCase__		:				Union[str, Any]    =  1
             lowerCamelCase__		:				List[str]    =  FlaxViTForImageClassification(__lowerCamelCase       )

             lowerCamelCase__		:				int    =  floats_tensor([self.batch_size, 1, self.image_size, self.image_size]       )
             lowerCamelCase__		:				int    =  model(__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             lowerCamelCase__		:				Union[str, Any]    =  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 			_lowercase (							lowercase_							,  unittest.TestCase):


       """simple docstring"""




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





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


             '''simple docstring'''



             lowerCamelCase__		:				Optional[int]    =  FlaxViTModelTester(self       )
             lowerCamelCase__		:				Optional[int]    =  ConfigTester(self					,      config_class=__lowerCamelCase					,      has_text_modality=__lowerCamelCase					,      hidden_size=37       )





       def 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



             self.config_tester.run_common_tests()





       def 						lowerCAmelCase     (   self							:			Any       ):


             '''simple docstring'''



             lowerCamelCase__		:				List[Any]    =  self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_model(*__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Optional[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_for_image_classification(*__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__    ,   lowerCamelCase__		:				List[str]    =  self.model_tester.prepare_config_and_inputs_for_common()

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

                   lowerCamelCase__		:				Tuple    =  ["pixel_values"]
                   self.assertListEqual(arg_names[:1]					,      __lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__    ,   lowerCamelCase__		:				List[str]    =  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(__lowerCamelCase					,      __lowerCamelCase       )
                         lowerCamelCase__		:				Optional[int]    =  model_class(__lowerCamelCase       )

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

                         with self.subTest("JIT Enabled"       ):
                               lowerCamelCase__		:				int    =  model_jitted(**__lowerCamelCase       ).to_tuple()

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





       @slow
       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             for model_class_name in self.all_model_classes:
                   lowerCamelCase__		:				Any    =  model_class_name.from_pretrained("google/vit-base-patch16-224"       )
                   lowerCamelCase__		:				Optional[Any]    =  model(np.ones((1, 3, 224, 224)       )       )
                   self.assertIsNotNone(__lowerCamelCase       )





class  lowercase				:




				def __init__(					self      ,   snake_case      ,   snake_case      ,   snake_case       ):
											snake_case_							=    name
											snake_case_							=    value
											snake_case_							=    weight




				def __repr__(					self       ):
											return F'''{self.__class__.__name__}({self.name}, {self.value}, {self.weight})'''




				def     a							(					self       ):
											return self.value




				def     a							(					self       ):
											return self.name




				def     a							(					self       ):
											return self.weight




				def     a							(					self       ):
											return self.value / self.weight





def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    []
							for i in range(len(UpperCamelCase__      )      ):
														menu.append(Things(name[i]   ,							value[i]   ,							weight[i]      )      )
							return menu





def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    sorted(UpperCamelCase__   ,							key=UpperCamelCase__   ,							reverse=UpperCamelCase__      )
							snake_case_							=    []
							snake_case_				,    snake_case_							=    0.0, 0.0
							for i in range(len(UpperCamelCase__      )      ):
														if (total_cost + items_copy[i].get_weight()) <= max_cost:
																					result.append(items_copy[i]      )
																					total_cost += items_copy[i].get_weight()
																					total_value += items_copy[i].get_value()
							return (result, total_value)





def 					__lowerCamelCase	( ):







							'''simple docstring'''








if __name__ == "__main__":
					import doctest

					doctest.testmod()




