



"""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  lowercase__  (       unittest.TestCase ):







       '''simple docstring'''


       def __init__(				self     :    Union[str, Any]						,							_UpperCAmelCase     :    Any						,							_UpperCAmelCase     :    str=100						,							_UpperCAmelCase     :    Optional[int]=13						,							_UpperCAmelCase     :    Optional[Any]=30						,							_UpperCAmelCase     :    Union[str, Any]=2						,							_UpperCAmelCase     :    List[Any]=3						,							_UpperCAmelCase     :    Optional[int]=True						,							_UpperCAmelCase     :    Union[str, Any]=True						,							_UpperCAmelCase     :    int=32						,							_UpperCAmelCase     :    int=5						,							_UpperCAmelCase     :    Union[str, Any]=4						,							_UpperCAmelCase     :    Optional[Any]=37						,							_UpperCAmelCase     :    Optional[int]="gelu"						,							_UpperCAmelCase     :    Optional[int]=0.1						,							_UpperCAmelCase     :    int=0.1						,							_UpperCAmelCase     :    Optional[int]=10						,							_UpperCAmelCase     :    List[Any]=0.02						,							_UpperCAmelCase     :    str=3						,							)					->		List[Any]:


             '''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 	lowercase__							(				self     :    Optional[Any]       )					->		Optional[int]:


             '''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=__lowerCamelCase						,							initializer_range=self.initializer_range						,							)

             return config, pixel_values, labels



       def 	lowercase__							(				self     :    int						,							_UpperCAmelCase     :    Any						,							_UpperCAmelCase     :    Optional[int]						,							_UpperCAmelCase     :    Dict       )					->		int:


             '''simple docstring'''




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



       def 	lowercase__							(				self     :    int						,							_UpperCAmelCase     :    Any						,							_UpperCAmelCase     :    Union[str, Any]						,							_UpperCAmelCase     :    str       )					->		List[Any]:


             '''simple docstring'''




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



       def 	lowercase__							(				self     :    Optional[int]						,							_UpperCAmelCase     :    str						,							_UpperCAmelCase     :    Any						,							_UpperCAmelCase     :    Any       )					->		Any:


             '''simple docstring'''




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

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

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







       def 	lowercase__							(				self     :    List[str]       )					->		Optional[Any]:


             '''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__  (       __snake_case							,   unittest.TestCase ):







       '''simple docstring'''


       UpperCamelCase		=	(
           (FlaxBeitModel, FlaxBeitForImageClassification, FlaxBeitForMaskedImageModeling) if is_flax_available() else ()
       )



       def 	lowercase__							(				self     :    List[str]       )					->		None:


             '''simple docstring'''




             UpperCAmelCase_     					=				FlaxBeitModelTester(self       )
             UpperCAmelCase_     					=				ConfigTester(self						,							config_class=__lowerCamelCase						,							has_text_modality=__lowerCamelCase						,							hidden_size=37       )



       def 	lowercase__							(				self     :    List[Any]       )					->		Union[str, Any]:


             '''simple docstring'''




             self.config_tester.run_common_tests()



       def 	lowercase__							(				self     :    Dict       )					->		Tuple:


             '''simple docstring'''




             UpperCAmelCase_					,       UpperCAmelCase_     					=				self.model_tester.prepare_config_and_inputs_for_common()

             for model_class in self.all_model_classes:
                   UpperCAmelCase_     					=				model_class(__lowerCamelCase       )
                   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]						,							__lowerCamelCase       )



       def 	lowercase__							(				self     :    Dict       )					->		List[Any]:


             '''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(__lowerCamelCase						,							__lowerCamelCase       )
                         UpperCAmelCase_     					=				model_class(__lowerCamelCase       )

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

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

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



       def 	lowercase__							(				self     :    List[str]       )					->		int:


             '''simple docstring'''




             UpperCAmelCase_     					=				self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_model(*__lowerCamelCase       )



       def 	lowercase__							(				self     :    List[str]       )					->		str:


             '''simple docstring'''




             UpperCAmelCase_     					=				self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_for_masked_lm(*__lowerCamelCase       )



       def 	lowercase__							(				self     :    Union[str, Any]       )					->		str:


             '''simple docstring'''




             UpperCAmelCase_     					=				self.model_tester.prepare_config_and_inputs()
             self.model_tester.create_and_check_for_image_classification(*__lowerCamelCase       )







       @slow
       def 	lowercase__							(				self     :    List[str]       )					->		Optional[int]:


             '''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, 224, 224)       )       )
                   self.assertIsNotNone(__lowerCamelCase       )



def   a__      ( ):
      UpperCAmelCase_     					=				Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png" )
      return image


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







       '''simple docstring'''


       @cached_property
       def 	lowercase__							(				self     :    Any       )					->		List[Any]:


             '''simple docstring'''




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



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


             '''simple docstring'''




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

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

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

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

             # verify the logits
             UpperCAmelCase_     					=				(1, 196, 8192)
             self.assertEqual(logits.shape						,							__lowerCamelCase       )

             UpperCAmelCase_     					=				np.array(
                 [[-3.2437, 0.5072, -13.9174], [-3.2456, 0.4948, -13.9401], [-3.2033, 0.5121, -13.8550]]       )

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



       @slow
       def 	lowercase__							(				self     :    int       )					->		Any:


             '''simple docstring'''




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

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

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

             # verify the logits
             UpperCAmelCase_     					=				(1, 1000)
             self.assertEqual(logits.shape						,							__lowerCamelCase       )

             UpperCAmelCase_     					=				np.array([-1.2385, -1.0987, -1.0108]       )

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

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







       @slow
       def 	lowercase__							(				self     :    Any       )					->		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=__lowerCamelCase						,							return_tensors="np"       )

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

             # verify the logits
             UpperCAmelCase_     					=				(1, 21841)
             self.assertEqual(logits.shape						,							__lowerCamelCase       )

             UpperCAmelCase_     					=				np.array([1.6881, -0.2787, 0.5901]       )

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

             UpperCAmelCase_     					=				2396
             self.assertEqual(logits.argmax(-1       ).item()						,							__lowerCamelCase       )








class 	__lowercase					:





      def __init__(		self    :       Optional[int]							)     -> int:






         """simple docstring"""







         UpperCAmelCase      					=  {}





      def 							_lowercase					(		self    :       str							)     -> None:






         """simple docstring"""







         print(self.vertex							)
         for i in self.vertex:
            print(__lowerCamelCase       ,							""" -> """       ,							""" -> """.join([str(__lowerCamelCase							) for j in self.vertex[i]]							)							)





      def 							_lowercase					(		self    :       Optional[Any]       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       int							)     -> None:






         """simple docstring"""







         if from_vertex in self.vertex:
            self.vertex[from_vertex].append(__lowerCamelCase							)
         else:
            # else make a new vertex
            UpperCAmelCase      					=  [to_vertex]





      def 							_lowercase					(		self    :       str							)     -> None:






         """simple docstring"""







         UpperCAmelCase      					=  [False] * len(self.vertex							)

         # call the recursive helper function
         for i in range(len(self.vertex							)							):
            if not visited[i]:
               self.dfs_recursive(__lowerCamelCase       ,							__lowerCamelCase							)





      def 							_lowercase					(		self    :       Optional[int]       ,							__lowerCamelCase    :       int       ,							__lowerCamelCase    :       list							)     -> None:






         """simple docstring"""







         UpperCAmelCase      					=  True

         print(__lowerCamelCase       ,							end=""" """							)

         # Recur for all the vertices that are adjacent to this node
         for i in self.vertex:
            if not visited[i]:
               self.dfs_recursive(__lowerCamelCase       ,							__lowerCamelCase							)


if __name__ == "__main__":
 __a	 =      Graph()
 g.add_edge(0, 1)
 g.add_edge(0, 2)
 g.add_edge(1, 2)
 g.add_edge(2, 0)
 g.add_edge(2, 3)
 g.add_edge(3, 3)

 g.print_graph()
 print("""DFS:""")
 g.dfs()

 # OUTPUT:
 # 0  ->  1 -> 2
 # 1  ->  2
 # 2  ->  0 -> 3
 # 3  ->  3
 # DFS:
 #  0 1 2 3



