

"""simple docstring"""





def   _A  (  UpperCamelCase_     :       Union[str, Any])	->						Dict:
   '''simple docstring'''


   __lowercase								=						[]
   __lowercase								=						[]
   __lowercase								=						{
       "^": 3,
       "*": 2,
       "/": 2,
       "%": 2,
       "+": 1,
       "-": 1,
   }  # Priority of each operator
   __lowercase								=						len(UpperCamelCase_) if (len(UpperCamelCase_) > 7) else 7

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

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

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

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

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




def   _A  (  UpperCamelCase_     :       Union[str, Any])	->						List[Any]:
   '''simple docstring'''


   __lowercase								=						list(infix[::-1])  # reverse the infix equation

   for i in range(len(UpperCamelCase_)):
      if infix[i] == "(":
         __lowercase								=						")"  # change "(" to ")"
      elif infix[i] == ")":
         __lowercase								=						"("  # change ")" to "("

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


if __name__ == "__main__":
   _a       =							input('\nEnter an Infix Equation = ')  # Input an Infix equation
   _a       =							''.join(Infix.split())  # Remove spaces from the input
   print('\n\t', Infix, '(Infix) -> ', infix_2_prefix(Infix), '(Prefix)')









"""simple docstring"""
import random
import unittest

import torch

from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin
@skip_mps
class 							_UpperCAmelCase							( a		,a		,unittest.TestCase      ):





     '''simple docstring'''



     a__									=IFImgaImgSuperResolutionPipeline
     a__									=TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {'''width''', '''height'''}
     a__									=TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS.union({'''original_image'''}      )
     a__									=PipelineTesterMixin.required_optional_params - {'''latents'''}





     def  __lowerCAmelCase	(					self		)							->					List[str]:
         return self._get_superresolution_dummy_components()





     def  __lowerCAmelCase	(					self       ,	A       ,	A=0		)							->					Union[str, Any]:
         if str(A		).startswith('''mps'''		):
             _UpperCAmelCase							:  Any											=    torch.manual_seed(A		)
         else:
             _UpperCAmelCase							:  int											=    torch.Generator(device=A		).manual_seed(A		)

         _UpperCAmelCase							:  str											=    floats_tensor((1, 3, 3_2, 3_2)       ,	rng=random.Random(A		)		).to(A		)
         _UpperCAmelCase							:  Dict											=    floats_tensor((1, 3, 1_6, 1_6)       ,	rng=random.Random(A		)		).to(A		)

         _UpperCAmelCase							:  List[Any]											=    {
             '''prompt''': '''A painting of a squirrel eating a burger''',
             '''image''': image,
             '''original_image''': original_image,
             '''generator''': generator,
             '''num_inference_steps''': 2,
             '''output_type''': '''numpy''',
         }

         return inputs





     @unittest.skipIf(
         torch_device != '''cuda''' or not is_xformers_available()       ,	reason='''XFormers attention is only available with CUDA and `xformers` installed'''       ,	)
     def  __lowerCAmelCase	(					self		)							->					List[Any]:
         self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3		)





     def  __lowerCAmelCase	(					self		)							->					List[str]:
         self._test_save_load_optional_components()





     @unittest.skipIf(torch_device != '''cuda'''       ,	reason='''float16 requires CUDA'''		)
     def  __lowerCAmelCase	(					self		)							->					Optional[Any]:
         # Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
         super().test_save_load_floataa(expected_max_diff=1E-1		)





     def  __lowerCAmelCase	(					self		)							->					int:
         self._test_attention_slicing_forward_pass(expected_max_diff=1E-2		)





     def  __lowerCAmelCase	(					self		)							->					Union[str, Any]:
         self._test_save_load_local()





     def  __lowerCAmelCase	(					self		)							->					Union[str, Any]:
         self._test_inference_batch_single_identical(
             expected_max_diff=1E-2       ,	)


