
"""simple docstring"""





_a		       =							[
    'Audio',
    'Array2D',
    'Array3D',
    'Array4D',
    'Array5D',
    'ClassLabel',
    'Features',
    'Sequence',
    'Value',
    'Image',
    'Translation',
    'TranslationVariableLanguages',
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages




"""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 A_	(unittest.TestCase      ):




  '''simple docstring'''







  def __init__(		self				,   lowercase_				,   lowercase_=13				,   lowercase_=30				,   lowercase_=2				,   lowercase_=3				,   lowercase_=True				,   lowercase_=True				,   lowercase_=32				,   lowercase_=5				,   lowercase_=4				,   lowercase_=37				,   lowercase_="gelu"				,   lowercase_=0.1				,   lowercase_=0.1				,   lowercase_=10				,   lowercase_=0.02				,   ):

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

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







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size]  )

     UpperCAmelCase_					:					Dict			     =    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        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    FlaxViTModel(config=lowercase_  )
     UpperCAmelCase_					:					int			     =    model(lowercase_  )
     # expected sequence length = num_patches + 1 (we add 1 for the [CLS] token)
     UpperCAmelCase_					:					Optional[Any]			     =    (self.image_size, self.image_size)
     UpperCAmelCase_					:					List[Any]			     =    (self.patch_size, self.patch_size)
     UpperCAmelCase_					:					str			     =    (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        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_  ):

     """simple docstring"""
     UpperCAmelCase_					:					Tuple			     =    self.type_sequence_label_size
     UpperCAmelCase_					:					Tuple			     =    FlaxViTForImageClassification(config=lowercase_  )
     UpperCAmelCase_					:					str			     =    model(lowercase_  )
     self.parent.assertEqual(result.logits.shape				,   (self.batch_size, self.type_sequence_label_size)  )

     # test greyscale images
     UpperCAmelCase_					:					Any			     =    1
     UpperCAmelCase_					:					Optional[int]			     =    FlaxViTForImageClassification(lowercase_  )

     UpperCAmelCase_					:					List[Any]			     =    floats_tensor([self.batch_size, 1, self.image_size, self.image_size]  )
     UpperCAmelCase_					:					List[Any]			     =    model(lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[Any]			     =    self.prepare_config_and_inputs()
     (
         (
         UpperCAmelCase_
     )     ,   (
         UpperCAmelCase_
     )     ,   
     )					:					Tuple			     =    config_and_inputs
     UpperCAmelCase_					:					Union[str, Any]			     =    {"pixel_values": pixel_values}
     return config, inputs_dict




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




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Any       =		(FlaxViTModel, FlaxViTForImageClassification) if is_flax_available() else ()







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[Any]			     =    FlaxViTModelTester(self  )
     UpperCAmelCase_					:					Dict			     =    ConfigTester(self				,   config_class=lowercase_				,   has_text_modality=lowercase_				,   hidden_size=37  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     self.config_tester.run_common_tests()







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[Any]			     =    self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_model(*lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    self.model_tester.prepare_config_and_inputs()
     self.model_tester.create_and_check_for_image_classification(*lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					List[str]			     =    self.model_tester.prepare_config_and_inputs_for_common()

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

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







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_     ,   UpperCAmelCase_					:					Tuple			     =    self.model_tester.prepare_config_and_inputs_for_common()

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

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

           with self.subTest("JIT Enabled"  ):
              UpperCAmelCase_					:					Union[str, Any]			     =    model_jitted(**lowercase_  ).to_tuple()

           with self.subTest("JIT Disabled"  ):
              with jax.disable_jit():
                 UpperCAmelCase_					:					Tuple			     =    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        UpperCamelCase__					(		self  ):

     """simple docstring"""
     for model_class_name in self.all_model_classes:
        UpperCAmelCase_					:					Union[str, Any]			     =    model_class_name.from_pretrained("google/vit-base-patch16-224"  )
        UpperCAmelCase_					:					List[str]			     =    model(np.ones((1, 3, 224, 224)  )  )
        self.assertIsNotNone(lowercase_  )


