


import inspect
import unittest

import numpy as np

from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available

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


if is_flax_available():
    import jax

    from transformers import FlaxBeitForImageClassification, FlaxBeitForMaskedImageModeling, FlaxBeitModel

if is_vision_available():
    from PIL import Image

    from transformers import BeitImageProcessor


class     lowercase__  (					unittest.TestCase		):






  def __init__(					self      :					Optional[Any]		,						_lowercase      :					int		,						_lowercase      :					int=1_00		,						_lowercase      :					Any=13		,						_lowercase      :					Dict=30		,						_lowercase      :					Tuple=2		,						_lowercase      :					Tuple=3		,						_lowercase      :					Any=True		,						_lowercase      :					int=True		,						_lowercase      :					Tuple=32		,						_lowercase      :					Any=5		,						_lowercase      :					Tuple=4		,						_lowercase      :					Union[str, Any]=37		,						_lowercase      :					List[Any]="gelu"		,						_lowercase      :					Union[str, Any]=0.1		,						_lowercase      :					List[str]=0.1		,						_lowercase      :					List[Any]=10		,						_lowercase      :					Optional[int]=0.0_2		,						_lowercase      :					Any=3		,						):




         """simple docstring"""







         UpperCAmelCase__										=     parent
         UpperCAmelCase__										=     vocab_size
         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 BeiT, 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 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         UpperCAmelCase__										=     floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size] )

         UpperCAmelCase__										=     None
         if self.use_labels:
                UpperCAmelCase__										=     ids_tensor([self.batch_size]		,						self.type_sequence_label_size )

         UpperCAmelCase__										=     BeitConfig(
             vocab_size=self.vocab_size		,						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, labels






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					Any		,						_lowercase      :					List[Any]		,						_lowercase      :					Any ):




         """simple docstring"""







         UpperCAmelCase__										=     FlaxBeitModel(config=_lowercase )
         UpperCAmelCase__										=     model(_lowercase )
         self.parent.assertEqual(result.last_hidden_state.shape		,						(self.batch_size, self.seq_length, self.hidden_size) )






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					Optional[Any]		,						_lowercase      :					Tuple		,						_lowercase      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     FlaxBeitForMaskedImageModeling(config=_lowercase )
         UpperCAmelCase__										=     model(_lowercase )
         self.parent.assertEqual(result.logits.shape		,						(self.batch_size, self.seq_length - 1, self.vocab_size) )






  def 			_UpperCAmelCase  (					self      :					List[str]		,						_lowercase      :					List[Any]		,						_lowercase      :					int		,						_lowercase      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.type_sequence_label_size
         UpperCAmelCase__										=     FlaxBeitForImageClassification(config=_lowercase )
         UpperCAmelCase__										=     model(_lowercase )
         self.parent.assertEqual(result.logits.shape		,						(self.batch_size, self.type_sequence_label_size) )

         # test greyscale images
         UpperCAmelCase__										=     1
         UpperCAmelCase__										=     FlaxBeitForImageClassification(_lowercase )

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






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         UpperCAmelCase__										=     self.prepare_config_and_inputs()
         (
             (
             UpperCAmelCase__			
         )						,			(
             UpperCAmelCase__			
         )						,			(
             UpperCAmelCase__			
         )						,						
         )										=     config_and_inputs
         UpperCAmelCase__										=     {"pixel_values": pixel_values}
         return config, inputs_dict




@require_flax
class     lowercase__  (					__SCREAMING_SNAKE_CASE					,							unittest.TestCase		):
  A__=  (
      (FlaxBeitModel, FlaxBeitForImageClassification, FlaxBeitForMaskedImageModeling) if is_flax_available() else ()
  )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__										=     FlaxBeitModelTester(self )
         UpperCAmelCase__										=     ConfigTester(self		,						config_class=_lowercase		,						has_text_modality=_lowercase		,						hidden_size=37 )






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




         """simple docstring"""







         self.config_tester.run_common_tests()






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







         UpperCAmelCase__						,			UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
                UpperCAmelCase__										=     model_class(_lowercase )
                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]		,						_lowercase )






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__						,			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(_lowercase		,						_lowercase )
                       UpperCAmelCase__										=     model_class(_lowercase )

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

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

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






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*_lowercase )






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




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_masked_lm(*_lowercase )






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_image_classification(*_lowercase )






  @slow
  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         for model_class_name in self.all_model_classes:
                UpperCAmelCase__										=     model_class_name.from_pretrained("microsoft/beit-base-patch16-224" )
                UpperCAmelCase__										=     model(np.ones((1, 3, 2_24, 2_24) ) )
                self.assertIsNotNone(_lowercase )





def __UpperCAmelCase       (		)						->					List[Any]:



       '''simple docstring'''





       UpperCAmelCase__										=     Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"			)
       return image






@require_vision
@require_flax
class     lowercase__  (					unittest.TestCase		):






  @cached_property
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







         return BeitImageProcessor.from_pretrained("microsoft/beit-base-patch16-224" ) if is_vision_available() else None






  @slow
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     FlaxBeitForMaskedImageModeling.from_pretrained("microsoft/beit-base-patch16-224-pt22k" )

         UpperCAmelCase__										=     self.default_image_processor
         UpperCAmelCase__										=     prepare_img()
         UpperCAmelCase__										=     image_processor(images=_lowercase		,						return_tensors="np" ).pixel_values

         # prepare bool_masked_pos
         UpperCAmelCase__										=     np.ones((1, 1_96)		,						dtype=_lowercase )

         # forward pass
         UpperCAmelCase__										=     model(pixel_values=_lowercase		,						bool_masked_pos=_lowercase )
         UpperCAmelCase__										=     outputs.logits

         # verify the logits
         UpperCAmelCase__										=     (1, 1_96, 81_92)
         self.assertEqual(logits.shape		,						_lowercase )

         UpperCAmelCase__										=     np.array(
             [[-3.2_4_3_7, 0.5_0_7_2, -13.91_74], [-3.2_4_5_6, 0.4_9_4_8, -13.94_01], [-3.2_0_3_3, 0.5_1_2_1, -13.85_50]] )

         self.assertTrue(np.allclose(logits[bool_masked_pos][:3, :3]		,						_lowercase		,						atol=1E-2 ) )






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




         """simple docstring"""







         UpperCAmelCase__										=     FlaxBeitForImageClassification.from_pretrained("microsoft/beit-base-patch16-224" )

         UpperCAmelCase__										=     self.default_image_processor
         UpperCAmelCase__										=     prepare_img()
         UpperCAmelCase__										=     image_processor(images=_lowercase		,						return_tensors="np" )

         # forward pass
         UpperCAmelCase__										=     model(**_lowercase )
         UpperCAmelCase__										=     outputs.logits

         # verify the logits
         UpperCAmelCase__										=     (1, 10_00)
         self.assertEqual(logits.shape		,						_lowercase )

         UpperCAmelCase__										=     np.array([-1.2_3_8_5, -1.0_9_8_7, -1.0_1_0_8] )

         self.assertTrue(np.allclose(logits[0, :3]		,						_lowercase		,						atol=1E-4 ) )

         UpperCAmelCase__										=     2_81
         self.assertEqual(logits.argmax(-1 ).item()		,						_lowercase )






  @slow
  def 			_UpperCAmelCase  (					self      :					Union[str, Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     FlaxBeitForImageClassification.from_pretrained("microsoft/beit-large-patch16-224-pt22k-ft22k" )

         UpperCAmelCase__										=     self.default_image_processor
         UpperCAmelCase__										=     prepare_img()
         UpperCAmelCase__										=     image_processor(images=_lowercase		,						return_tensors="np" )

         # forward pass
         UpperCAmelCase__										=     model(**_lowercase )
         UpperCAmelCase__										=     outputs.logits

         # verify the logits
         UpperCAmelCase__										=     (1, 2_18_41)
         self.assertEqual(logits.shape		,						_lowercase )

         UpperCAmelCase__										=     np.array([1.6_8_8_1, -0.2_7_8_7, 0.5_9_0_1] )

         self.assertTrue(np.allclose(logits[0, :3]		,						_lowercase		,						atol=1E-4 ) )

         UpperCAmelCase__										=     23_96
         self.assertEqual(logits.argmax(-1 ).item()		,						_lowercase )









import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


A      = logging.get_logger(__name__)


class     lowercase__  (					__SCREAMING_SNAKE_CASE		):






  def __init__(					self      :					Union[str, Any]		,						*_lowercase      :					Any		,						**_lowercase      :					Optional[int] ):




         """simple docstring"""







         warnings.warn(
             "The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
             " use DPTImageProcessor instead."		,						_lowercase		,						)
         super().__init__(*_lowercase		,						**_lowercase )





