def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						Dict:




      """simple docstring"""

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

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

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

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

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

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






def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						Optional[Any]:




      """simple docstring"""

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

      for i in range(len(SCREAMING_SNAKE_CASE      )      ):
            if infix[i] == "(":
                  snake_case_ =   ''')'''  # change "(" to ")"
            elif infix[i] == ")":
                  snake_case_ =   '''('''  # change ")" to "("

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


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



import unittest

import numpy as np

from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)

from ..test_pipelines_onnx_common import OnnxPipelineTesterMixin


if is_onnx_available():
   import onnxruntime as ort







class lowerCAmelCase_		(				lowerCamelCase__      ,		unittest.TestCase ):

 '''simple docstring'''

 pass







@nightly
@require_onnxruntime
@require_torch_gpu
class lowerCAmelCase_		(				unittest.TestCase ):

 '''simple docstring'''

 @property
 def 		UpperCamelCase__  (			self      ):
       return (
           "CUDAExecutionProvider",
           {
               "gpu_mem_limit": "15000000000",  # 15GB
               "arena_extend_strategy": "kSameAsRequested",
           },
       )



 @property
 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   ort.SessionOptions()
       snake_case_ =   False
       return options



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   load_image(
           '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
           '''/in_paint/overture-creations-5sI6fQgYIuo.png'''      )
       snake_case_ =   load_image(
           '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
           '''/in_paint/overture-creations-5sI6fQgYIuo_mask.png'''      )
       snake_case_ =   OnnxStableDiffusionInpaintPipeline.from_pretrained(
           '''runwayml/stable-diffusion-inpainting'''	,   revision='''onnx'''	,   safety_checker=_UpperCAmelCase	,   feature_extractor=_UpperCAmelCase	,   provider=self.gpu_provider	,   sess_options=self.gpu_options	,   )
       pipe.set_progress_bar_config(disable=_UpperCAmelCase      )

       snake_case_ =   '''A red cat sitting on a park bench'''

       snake_case_ =   np.random.RandomState(0      )
       snake_case_ =   pipe(
           prompt=_UpperCAmelCase	,   image=_UpperCAmelCase	,   mask_image=_UpperCAmelCase	,   guidance_scale=7.5	,   num_inference_steps=10	,   generator=_UpperCAmelCase	,   output_type='''np'''	,   )
       snake_case_ =   output.images
       snake_case_ =   images[0, 2_55:2_58, 2_55:2_58, -1]

       assert images.shape == (1, 5_12, 5_12, 3)
       snake_case_ =   np.array([0.2_514, 0.3_007, 0.3_517, 0.1_790, 0.2_382, 0.3_167, 0.1_944, 0.2_273, 0.2_464]      )

       assert np.abs(image_slice.flatten() - expected_slice      ).max() < 1E-3





 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   load_image(
           '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
           '''/in_paint/overture-creations-5sI6fQgYIuo.png'''      )
       snake_case_ =   load_image(
           '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
           '''/in_paint/overture-creations-5sI6fQgYIuo_mask.png'''      )
       snake_case_ =   LMSDiscreteScheduler.from_pretrained(
           '''runwayml/stable-diffusion-inpainting'''	,   subfolder='''scheduler'''	,   revision='''onnx'''      )
       snake_case_ =   OnnxStableDiffusionInpaintPipeline.from_pretrained(
           '''runwayml/stable-diffusion-inpainting'''	,   revision='''onnx'''	,   scheduler=_UpperCAmelCase	,   safety_checker=_UpperCAmelCase	,   feature_extractor=_UpperCAmelCase	,   provider=self.gpu_provider	,   sess_options=self.gpu_options	,   )
       pipe.set_progress_bar_config(disable=_UpperCAmelCase      )

       snake_case_ =   '''A red cat sitting on a park bench'''

       snake_case_ =   np.random.RandomState(0      )
       snake_case_ =   pipe(
           prompt=_UpperCAmelCase	,   image=_UpperCAmelCase	,   mask_image=_UpperCAmelCase	,   guidance_scale=7.5	,   num_inference_steps=20	,   generator=_UpperCAmelCase	,   output_type='''np'''	,   )
       snake_case_ =   output.images
       snake_case_ =   images[0, 2_55:2_58, 2_55:2_58, -1]

       assert images.shape == (1, 5_12, 5_12, 3)
       snake_case_ =   np.array([0.0_086, 0.0_077, 0.0_083, 0.0_093, 0.0_107, 0.0_139, 0.0_094, 0.0_097, 0.0_125]      )

       assert np.abs(image_slice.flatten() - expected_slice      ).max() < 1E-3