






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 				_A			(     unittest.TestCase				):
    """simple docstring"""

    def __init__(				self      :     Tuple ,     __SCREAMING_SNAKE_CASE      :     Dict ,     __SCREAMING_SNAKE_CASE      :     Optional[int]=13 ,     __SCREAMING_SNAKE_CASE      :     str=30 ,     __SCREAMING_SNAKE_CASE      :     Optional[Any]=2 ,     __SCREAMING_SNAKE_CASE      :     List[str]=3 ,     __SCREAMING_SNAKE_CASE      :     Optional[int]=True ,     __SCREAMING_SNAKE_CASE      :     Optional[Any]=True ,     __SCREAMING_SNAKE_CASE      :     Tuple=32 ,     __SCREAMING_SNAKE_CASE      :     Union[str, Any]=5 ,     __SCREAMING_SNAKE_CASE      :     List[str]=4 ,     __SCREAMING_SNAKE_CASE      :     Tuple=37 ,     __SCREAMING_SNAKE_CASE      :     str="gelu" ,     __SCREAMING_SNAKE_CASE      :     Optional[Any]=0.1 ,     __SCREAMING_SNAKE_CASE      :     Optional[Any]=0.1 ,     __SCREAMING_SNAKE_CASE      :     Tuple=10 ,     __SCREAMING_SNAKE_CASE      :     List[str]=0.02 ,     )      ->							Union[str, Any]:
           __UpperCAmelCase     				=parent
           __UpperCAmelCase     				=batch_size
           __UpperCAmelCase     				=image_size
           __UpperCAmelCase     				=patch_size
           __UpperCAmelCase     				=num_channels
           __UpperCAmelCase     				=is_training
           __UpperCAmelCase     				=use_labels
           __UpperCAmelCase     				=hidden_size
           __UpperCAmelCase     				=num_hidden_layers
           __UpperCAmelCase     				=num_attention_heads
           __UpperCAmelCase     				=intermediate_size
           __UpperCAmelCase     				=hidden_act
           __UpperCAmelCase     				=hidden_dropout_prob
           __UpperCAmelCase     				=attention_probs_dropout_prob
           __UpperCAmelCase     				=type_sequence_label_size
           __UpperCAmelCase     				=initializer_range

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



    def _a							(				self      :     List[str]      )      ->							Any:
           __UpperCAmelCase     				=floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]      )

           __UpperCAmelCase     				=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=__UpperCAmelCase ,     initializer_range=self.initializer_range ,     )

           return config, pixel_values



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

           # test greyscale images
           __UpperCAmelCase     				=1
           __UpperCAmelCase     				=FlaxViTForImageClassification(__UpperCAmelCase      )

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



    def _a							(				self      :     List[str]      )      ->							Union[str, Any]:
           __UpperCAmelCase     				=self.prepare_config_and_inputs()
           (
               __UpperCAmelCase							
           )     				=config_and_inputs
           __UpperCAmelCase     				={'pixel_values': pixel_values}
           return config, inputs_dict




@require_flax
class 				_A			(     UpperCamelCase					,					unittest.TestCase				):
    """simple docstring"""

    lowerCamelCase	:							List[Any]				= (FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()



    def _a							(				self      :     str      )      ->							int:
           __UpperCAmelCase     				=FlaxViTModelTester(self      )
           __UpperCAmelCase     				=ConfigTester(self ,     config_class=__UpperCAmelCase ,     has_text_modality=__UpperCAmelCase ,     hidden_size=37      )



    def _a							(				self      :     Optional[int]      )      ->							Tuple:
           self.config_tester.run_common_tests()



    def _a							(				self      :     Dict      )      ->							Optional[Any]:
           __UpperCAmelCase     				=self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_model(*__UpperCAmelCase      )



    def _a							(				self      :     List[str]      )      ->							Optional[Any]:
           __UpperCAmelCase     				=self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_for_image_classification(*__UpperCAmelCase      )



    def _a							(				self      :     Tuple      )      ->							Any:
           __UpperCAmelCase     				=self.model_tester.prepare_config_and_inputs_for_common()

           for model_class in self.all_model_classes:
                  __UpperCAmelCase     				=model_class(__UpperCAmelCase      )
                  __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] ,     __UpperCAmelCase      )



    def _a							(				self      :     Any      )      ->							Optional[int]:
           __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(__UpperCAmelCase ,     __UpperCAmelCase      )
                         __UpperCAmelCase     				=model_class(__UpperCAmelCase      )

                         @jax.jit
                         def model_jitted(__SCREAMING_SNAKE_CASE      :     str ,     **__SCREAMING_SNAKE_CASE      :     Union[str, Any]      ):
                                return model(pixel_values=__UpperCAmelCase ,     **__UpperCAmelCase      )

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

                         with self.subTest("""JIT Disabled"""      ):
                                with jax.disable_jit():
                                       __UpperCAmelCase     				=model_jitted(**__UpperCAmelCase      ).to_tuple()

                         self.assertEqual(len(__UpperCAmelCase      ) ,     len(__UpperCAmelCase      )      )
                         for jitted_output, output in zip(__UpperCAmelCase ,     __UpperCAmelCase      ):
                                self.assertEqual(jitted_output.shape ,     output.shape      )



    @slow
    def _a							(				self      :     List[Any]      )      ->							Union[str, Any]:

           for model_class_name in self.all_model_classes:
                  __UpperCAmelCase     				=model_class_name.from_pretrained("""google/vit-base-patch16-224"""      )
                  __UpperCAmelCase     				=model(np.ones((1, 3, 224, 224)      )      )
                  self.assertIsNotNone(__UpperCAmelCase      )











"""simple docstring"""





import re
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->list:





  """simple docstring"""


  return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]'	,  str_     )]
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  lowerCAmelCase__     :Optional[Any]											=				split_input(str_     )
  return "".join(
      [''.join([char.capitalize() for char in sub_str]     ) for sub_str in string_split]     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  try:
    lowerCAmelCase__     :Any											=				split_input(_SCREAMING_SNAKE_CASE     )
    if upper:
      lowerCAmelCase__     :str											=				''.join(
          [
              separator.join([char.upper() for char in sub_str]     )
              for sub_str in string_split
          ]     )
    else:
      lowerCAmelCase__     :int											=				''.join(
          [
              separator.join([char.lower() for char in sub_str]     )
              for sub_str in string_split
          ]     )
    return res_str
  except IndexError:
    return "not valid string"
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_simple_case(_SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  try:
    lowerCAmelCase__     :str											=				to_simple_case(_SCREAMING_SNAKE_CASE     )
    return res_str[0].lower() + res_str[1:]
  except IndexError:
    return "not valid string"
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_complex_case(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  '_'     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->str:





  """simple docstring"""


  return to_complex_case(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  '-'     )


if __name__ == "__main__":
  __import__("""doctest""").testmod()
