



'''simple docstring'''





import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version




def        lowerCamelCase  (				*_snake_case  :						Dict     ,_snake_case  :						Tuple = None     ,_snake_case  :						Tuple=True     ,_snake_case  :						Tuple=2       ):





    '''simple docstring'''


    from .. import __version__

    lowercase__		       =						take_from
    lowercase__		       =						()
    if not isinstance(args[0]     ,lowerCAmelCase_       ):
        lowercase__		       =						(args,)

    for attribute, version_name, message in args:
        if version.parse(version.parse(lowerCAmelCase_       ).base_version       ) >= version.parse(lowerCAmelCase_       ):
            raise ValueError(
                f'''The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers\''''
                f''' version {__version__} is >= {version_name}'''       )

        lowercase__		       =						None
        if isinstance(lowerCAmelCase_     ,lowerCAmelCase_       ) and attribute in deprecated_kwargs:
            values += (deprecated_kwargs.pop(lowerCAmelCase_       ),)
            lowercase__		       =						f'''The `{attribute}` argument is deprecated and will be removed in version {version_name}.'''
        elif hasattr(lowerCAmelCase_     ,lowerCAmelCase_       ):
            values += (getattr(lowerCAmelCase_     ,lowerCAmelCase_       ),)
            lowercase__		       =						f'''The `{attribute}` attribute is deprecated and will be removed in version {version_name}.'''
        elif deprecated_kwargs is None:
            lowercase__		       =						f'''`{attribute}` is deprecated and will be removed in version {version_name}.'''

        if warning is not None:
            lowercase__		       =						warning + " " if standard_warn else ""
            warnings.warn(warning + message     ,lowerCAmelCase_     ,stacklevel=lowerCAmelCase_       )

    if isinstance(lowerCAmelCase_     ,lowerCAmelCase_       ) and len(lowerCAmelCase_       ) > 0:
        lowercase__		       =						inspect.getouterframes(inspect.currentframe()       )[1]
        lowercase__		       =						call_frame.filename
        lowercase__		       =						call_frame.lineno
        lowercase__		       =						call_frame.function
        lowercase__		       =						next(iter(deprecated_kwargs.items()       )       )
        raise TypeError(f'''{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`'''       )

    if len(lowerCAmelCase_       ) == 0:
        return
    elif len(lowerCAmelCase_       ) == 1:
        return values[0]
    return values









'''simple docstring'''





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 				snake_case (unittest.TestCase   ):



       def __init__(				self     ,UpperCAmelCase_     ,UpperCAmelCase_=100     ,UpperCAmelCase_=13     ,UpperCAmelCase_=30     ,UpperCAmelCase_=2     ,UpperCAmelCase_=3     ,UpperCAmelCase_=True     ,UpperCAmelCase_=True     ,UpperCAmelCase_=32     ,UpperCAmelCase_=5     ,UpperCAmelCase_=4     ,UpperCAmelCase_=37     ,UpperCAmelCase_="gelu"     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=0.1     ,UpperCAmelCase_=10     ,UpperCAmelCase_=0.02     ,UpperCAmelCase_=3     ,)  ->							List[Any]:
           lowercase__		       =						parent
           lowercase__		       =						vocab_size
           lowercase__		       =						batch_size
           lowercase__		       =						image_size
           lowercase__		       =						patch_size
           lowercase__		       =						num_channels
           lowercase__		       =						is_training
           lowercase__		       =						use_labels
           lowercase__		       =						hidden_size
           lowercase__		       =						num_hidden_layers
           lowercase__		       =						num_attention_heads
           lowercase__		       =						intermediate_size
           lowercase__		       =						hidden_act
           lowercase__		       =						hidden_dropout_prob
           lowercase__		       =						attention_probs_dropout_prob
           lowercase__		       =						type_sequence_label_size
           lowercase__		       =						initializer_range

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



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

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

           lowercase__		       =						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=UpperCAmelCase_     ,initializer_range=self.initializer_range     ,)

           return config, pixel_values, labels



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_     ,UpperCAmelCase_      )  ->							Optional[int]:
           lowercase__		       =						FlaxBeitModel(config=UpperCAmelCase_      )
           lowercase__		       =						model(UpperCAmelCase_      )
           self.parent.assertEqual(result.last_hidden_state.shape     ,(self.batch_size, self.seq_length, self.hidden_size)      )



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_     ,UpperCAmelCase_      )  ->							Tuple:
           lowercase__		       =						FlaxBeitForMaskedImageModeling(config=UpperCAmelCase_      )
           lowercase__		       =						model(UpperCAmelCase_      )
           self.parent.assertEqual(result.logits.shape     ,(self.batch_size, self.seq_length - 1, self.vocab_size)      )



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_     ,UpperCAmelCase_      )  ->							List[str]:
           lowercase__		       =						self.type_sequence_label_size
           lowercase__		       =						FlaxBeitForImageClassification(config=UpperCAmelCase_      )
           lowercase__		       =						model(UpperCAmelCase_      )
           self.parent.assertEqual(result.logits.shape     ,(self.batch_size, self.type_sequence_label_size)      )

           # test greyscale images
           lowercase__		       =						1
           lowercase__		       =						FlaxBeitForImageClassification(UpperCAmelCase_      )

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







       def 							_a      (				self      )  ->							int:
           lowercase__		       =						self.prepare_config_and_inputs()
           (
               (
               lowercase__
           )       ,       (
               lowercase__
           )       ,       (
               lowercase__
           )       ,       
           )		       =						config_and_inputs
           lowercase__		       =						{"pixel_values": pixel_values}
           return config, inputs_dict





@require_flax
class 				snake_case (UpperCamelCase		,      unittest.TestCase   ):
       lowerCAmelCase__  :Optional[int]						   =					(
           (FlaxBeitModel, FlaxBeitForImageClassification, FlaxBeitForMaskedImageModeling) if is_flax_available() else ()
       )



       def 							_a      (				self      )  ->							None:
           lowercase__		       =						FlaxBeitModelTester(self      )
           lowercase__		       =						ConfigTester(self     ,config_class=UpperCAmelCase_     ,has_text_modality=UpperCAmelCase_     ,hidden_size=37      )



       def 							_a      (				self      )  ->							Union[str, Any]:
           self.config_tester.run_common_tests()



       def 							_a      (				self      )  ->							Optional[Any]:
           lowercase__       ,       lowercase__		       =						self.model_tester.prepare_config_and_inputs_for_common()

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

               lowercase__		       =						["pixel_values"]
               self.assertListEqual(arg_names[:1]     ,UpperCAmelCase_      )



       def 							_a      (				self      )  ->							int:
           lowercase__       ,       lowercase__		       =						self.model_tester.prepare_config_and_inputs_for_common()

           for model_class in self.all_model_classes:
               with self.subTest(model_class.__name__      ):
                   lowercase__		       =						self._prepare_for_class(UpperCAmelCase_     ,UpperCAmelCase_      )
                   lowercase__		       =						model_class(UpperCAmelCase_      )

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

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

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



       def 							_a      (				self      )  ->							List[Any]:
           lowercase__		       =						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_model(*UpperCAmelCase_      )



       def 							_a      (				self      )  ->							Union[str, Any]:
           lowercase__		       =						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_for_masked_lm(*UpperCAmelCase_      )



       def 							_a      (				self      )  ->							str:
           lowercase__		       =						self.model_tester.prepare_config_and_inputs()
           self.model_tester.create_and_check_for_image_classification(*UpperCAmelCase_      )







       @slow
       def 							_a      (				self      )  ->							Tuple:
           for model_class_name in self.all_model_classes:
               lowercase__		       =						model_class_name.from_pretrained("microsoft/beit-base-patch16-224"      )
               lowercase__		       =						model(np.ones((1, 3, 224, 224)      )      )
               self.assertIsNotNone(UpperCAmelCase_      )





def        lowerCamelCase  (				):





    '''simple docstring'''


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



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



       @cached_property
       def 							_a      (				self      )  ->							Optional[int]:
           return BeitImageProcessor.from_pretrained("microsoft/beit-base-patch16-224"      ) if is_vision_available() else None



       @slow
       def 							_a      (				self      )  ->							Union[str, Any]:
           lowercase__		       =						FlaxBeitForMaskedImageModeling.from_pretrained("microsoft/beit-base-patch16-224-pt22k"      )

           lowercase__		       =						self.default_image_processor
           lowercase__		       =						prepare_img()
           lowercase__		       =						image_processor(images=UpperCAmelCase_     ,return_tensors="np"      ).pixel_values

           # prepare bool_masked_pos
           lowercase__		       =						np.ones((1, 196)     ,dtype=UpperCAmelCase_      )

           # forward pass
           lowercase__		       =						model(pixel_values=UpperCAmelCase_     ,bool_masked_pos=UpperCAmelCase_      )
           lowercase__		       =						outputs.logits

           # verify the logits
           lowercase__		       =						(1, 196, 8_192)
           self.assertEqual(logits.shape     ,UpperCAmelCase_      )

           lowercase__		       =						np.array(
               [[-3.24_37, 0.50_72, -13.91_74], [-3.24_56, 0.49_48, -13.94_01], [-3.20_33, 0.51_21, -13.85_50]]      )

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



       @slow
       def 							_a      (				self      )  ->							List[str]:
           lowercase__		       =						FlaxBeitForImageClassification.from_pretrained("microsoft/beit-base-patch16-224"      )

           lowercase__		       =						self.default_image_processor
           lowercase__		       =						prepare_img()
           lowercase__		       =						image_processor(images=UpperCAmelCase_     ,return_tensors="np"      )

           # forward pass
           lowercase__		       =						model(**UpperCAmelCase_      )
           lowercase__		       =						outputs.logits

           # verify the logits
           lowercase__		       =						(1, 1_000)
           self.assertEqual(logits.shape     ,UpperCAmelCase_      )

           lowercase__		       =						np.array([-1.23_85, -1.09_87, -1.01_08]      )

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

           lowercase__		       =						281
           self.assertEqual(logits.argmax(-1      ).item()     ,UpperCAmelCase_      )







       @slow
       def 							_a      (				self      )  ->							Optional[int]:
           lowercase__		       =						FlaxBeitForImageClassification.from_pretrained("microsoft/beit-large-patch16-224-pt22k-ft22k"      )

           lowercase__		       =						self.default_image_processor
           lowercase__		       =						prepare_img()
           lowercase__		       =						image_processor(images=UpperCAmelCase_     ,return_tensors="np"      )

           # forward pass
           lowercase__		       =						model(**UpperCAmelCase_      )
           lowercase__		       =						outputs.logits

           # verify the logits
           lowercase__		       =						(1, 21_841)
           self.assertEqual(logits.shape     ,UpperCAmelCase_      )

           lowercase__		       =						np.array([1.68_81, -0.27_87, 0.59_01]      )

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

           lowercase__		       =						2_396
           self.assertEqual(logits.argmax(-1      ).item()     ,UpperCAmelCase_      )




