

'''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 						__magic_name__   (							unittest.TestCase ):







 def __init__(       self  , snake_case_  , snake_case_=1_00  , snake_case_=13  , snake_case_=30  , snake_case_=2  , snake_case_=3  , snake_case_=True  , snake_case_=True  , snake_case_=32  , snake_case_=5  , snake_case_=4  , snake_case_=37  , snake_case_="gelu"  , snake_case_=0.1  , snake_case_=0.1  , snake_case_=10  , snake_case_=0.02  , snake_case_=3  , ):
   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   ):
   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=snake_case_  , initializer_range=self.initializer_range  , )

   return config, pixel_values, labels







 def 						_A(       self  , snake_case_  , snake_case_  , snake_case_   ):
   lowercase									=FlaxBeitModel(config=snake_case_   )
   lowercase									=model(snake_case_   )
   self.parent.assertEqual(result.last_hidden_state.shape  , (self.batch_size, self.seq_length, self.hidden_size)   )







 def 						_A(       self  , snake_case_  , snake_case_  , snake_case_   ):
   lowercase									=FlaxBeitForMaskedImageModeling(config=snake_case_   )
   lowercase									=model(snake_case_   )
   self.parent.assertEqual(result.logits.shape  , (self.batch_size, self.seq_length - 1, self.vocab_size)   )







 def 						_A(       self  , snake_case_  , snake_case_  , snake_case_   ):
   lowercase									=self.type_sequence_label_size
   lowercase									=FlaxBeitForImageClassification(config=snake_case_   )
   lowercase									=model(snake_case_   )
   self.parent.assertEqual(result.logits.shape  , (self.batch_size, self.type_sequence_label_size)   )

   # test greyscale images
   lowercase									=1
   lowercase									=FlaxBeitForImageClassification(snake_case_   )

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







 def 						_A(       self   ):
   lowercase									=self.prepare_config_and_inputs()
   (
       (
       lowercase
   )							, (
       lowercase
   )							, (
       lowercase
   )							, 
   )									=config_and_inputs
   lowercase									={'''pixel_values''': pixel_values}
   return config, inputs_dict

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







 def 						_A(       self   ):
   lowercase									=FlaxBeitModelTester(self   )
   lowercase									=ConfigTester(self  , config_class=snake_case_  , has_text_modality=snake_case_  , hidden_size=37   )







 def 						_A(       self   ):
   self.config_tester.run_common_tests()







 def 						_A(       self   ):
   lowercase							, lowercase									=self.model_tester.prepare_config_and_inputs_for_common()

   for model_class in self.all_model_classes:
     lowercase									=model_class(snake_case_   )
     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]  , snake_case_   )







 def 						_A(       self   ):
   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(snake_case_  , snake_case_   )
       lowercase									=model_class(snake_case_   )

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

       with self.subTest('''JIT Enabled'''   ):
         lowercase									=model_jitted(**snake_case_   ).to_tuple()

       with self.subTest('''JIT Disabled'''   ):
         with jax.disable_jit():
           lowercase									=model_jitted(**snake_case_   ).to_tuple()

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







 def 						_A(       self   ):
   lowercase									=self.model_tester.prepare_config_and_inputs()
   self.model_tester.create_and_check_model(*snake_case_   )







 def 						_A(       self   ):
   lowercase									=self.model_tester.prepare_config_and_inputs()
   self.model_tester.create_and_check_for_masked_lm(*snake_case_   )







 def 						_A(       self   ):
   lowercase									=self.model_tester.prepare_config_and_inputs()
   self.model_tester.create_and_check_for_image_classification(*snake_case_   )







 @slow
 def 						_A(       self   ):
   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, 2_24, 2_24)   )   )
     self.assertIsNotNone(snake_case_   )




def 	UpperCamelCase   (       )		->	str:




  '''simple docstring'''



  lowercase									=Image.open('''./tests/fixtures/tests_samples/COCO/000000039769.png'''	)
  return image




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







 @cached_property
 def 						_A(       self   ):
   return BeitImageProcessor.from_pretrained('''microsoft/beit-base-patch16-224'''   ) if is_vision_available() else None







 @slow
 def 						_A(       self   ):
   lowercase									=FlaxBeitForMaskedImageModeling.from_pretrained('''microsoft/beit-base-patch16-224-pt22k'''   )

   lowercase									=self.default_image_processor
   lowercase									=prepare_img()
   lowercase									=image_processor(images=snake_case_  , return_tensors='''np'''   ).pixel_values

   # prepare bool_masked_pos
   lowercase									=np.ones((1, 1_96)  , dtype=snake_case_   )

   # forward pass
   lowercase									=model(pixel_values=snake_case_  , bool_masked_pos=snake_case_   )
   lowercase									=outputs.logits

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

   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]  , snake_case_  , atol=1E-2   )   )







 @slow
 def 						_A(       self   ):
   lowercase									=FlaxBeitForImageClassification.from_pretrained('''microsoft/beit-base-patch16-224'''   )

   lowercase									=self.default_image_processor
   lowercase									=prepare_img()
   lowercase									=image_processor(images=snake_case_  , return_tensors='''np'''   )

   # forward pass
   lowercase									=model(**snake_case_   )
   lowercase									=outputs.logits

   # verify the logits
   lowercase									=(1, 10_00)
   self.assertEqual(logits.shape  , snake_case_   )

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

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

   lowercase									=2_81
   self.assertEqual(logits.argmax(-1   ).item()  , snake_case_   )







 @slow
 def 						_A(       self   ):
   lowercase									=FlaxBeitForImageClassification.from_pretrained('''microsoft/beit-large-patch16-224-pt22k-ft22k'''   )

   lowercase									=self.default_image_processor
   lowercase									=prepare_img()
   lowercase									=image_processor(images=snake_case_  , return_tensors='''np'''   )

   # forward pass
   lowercase									=model(**snake_case_   )
   lowercase									=outputs.logits

   # verify the logits
   lowercase									=(1, 2_18_41)
   self.assertEqual(logits.shape  , snake_case_   )

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

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

   lowercase									=23_96
   self.assertEqual(logits.argmax(-1   ).item()  , snake_case_   )







def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Union[str, Any] 						=      []
		lowerCamelCase_	:     Tuple 						=      []
		lowerCamelCase_	:     Dict 						=      {
		    '^': 3,
		    '*': 2,
		    '/': 2,
		    '%': 2,
		    '+': 1,
		    '-': 1,
		}  # Priority of each operator
		lowerCamelCase_	:     Optional[int] 						=      len(lowerCAmelCase__						) if (len(lowerCAmelCase__						) > 7) else 7

		# Print table header for output
		print(
		    'Symbol'.center(8						)							,'Stack'.center(lowerCAmelCase__						)							,'Postfix'.center(lowerCAmelCase__						)							,sep=' | '							,)
		print('-' * (print_width * 3 + 7)						)

		for x in infix:
				if x.isalpha() or x.isdigit():
						post_fix.append(lowerCAmelCase__						)  # if x is Alphabet / Digit, add it to Postfix
				elif x == "(":
						stack.append(lowerCAmelCase__						)  # if x is "(" push to Stack
				elif x == ")":  # if x is ")" pop stack until "(" is encountered
						while stack[-1] != "(":
								post_fix.append(stack.pop()						)  # Pop stack & add the content to Postfix
						stack.pop()
				else:
						if len(lowerCAmelCase__						) == 0:
								stack.append(lowerCAmelCase__						)  # If stack is empty, push x to stack
						else:  # while priority of x is not > priority of element in the stack
								while len(lowerCAmelCase__						) > 0 and priority[x] <= priority[stack[-1]]:
										post_fix.append(stack.pop()						)  # pop stack & add to Postfix
								stack.append(lowerCAmelCase__						)  # push x to stack

				print(
				    x.center(8						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,sep=' | '							,)  # Output in tabular format

		while len(lowerCAmelCase__						) > 0:  # while stack is not empty
				post_fix.append(stack.pop()						)  # pop stack & add to Postfix
				print(
				    ' '.center(8						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,(''.join(lowerCAmelCase__						)).ljust(lowerCAmelCase__						)							,sep=' | '							,)  # Output in tabular format

		return "".join(lowerCAmelCase__						)  # return Postfix as str


def 		_SCREAMING_SNAKE_CASE     ( lowerCAmelCase__						):
		lowerCamelCase_	:     Dict 						=      list(infix[::-1]						)  # reverse the infix equation

		for i in range(len(lowerCAmelCase__						)						):
				if infix[i] == "(":
						lowerCamelCase_	:     str 						=      ')'  # change "(" to ")"
				elif infix[i] == ")":
						lowerCamelCase_	:     Optional[Any] 						=      '('  # change ")" to "("

		return (infix_2_postfix(''.join(lowerCAmelCase__						)						))[
		    ::-1
		]  # call infix_2_postfix on Infix, return reverse of Postfix


if __name__ == "__main__":
		_lowercase		:  int			       =input("""\nEnter an Infix Equation = """)  # Input an Infix equation
		_lowercase		:  Optional[Any]			       ="""""".join(Infix.split())  # Remove spaces from the input
		print("""\n\t""", Infix, """(Infix) -> """, infix_2_prefix(Infix), """(Prefix)""")
