




from typing import List, Optional, Union

import numpy as np
import PIL.Image

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
    ChannelDimension,
    PILImageResampling,
    get_image_size,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, logging


_lowerCamelCase     :		Union[str, Any]								=      logging.get_logger(__name__)


class     UpperCamelCase_   (			lowerCamelCase_					):

    '''simple docstring'''






    UpperCAmelCase__							  =				["""pixel_values"""]


    def __init__(      self				:     List[str] ,			UpperCAmelCase__				:     List[str] = True ,			UpperCAmelCase__				:     Tuple = 32 ,			UpperCAmelCase__				:     Optional[Any]=PILImageResampling.BILINEAR ,			UpperCAmelCase__				:     Optional[int] = True ,			**UpperCAmelCase__				:     List[Any] ,			)						->None:





           '''simple docstring'''

           A__							=   do_resize
           A__							=   do_rescale
           A__							=   size_divisor
           A__							=   resample
           super().__init__(**lowerCAmelCase__)


    def 	SCREAMING_SNAKE_CASE							(      self				:     Dict ,			UpperCAmelCase__				:     Optional[int] ,			UpperCAmelCase__				:     int ,			UpperCAmelCase__				:     Any ,			UpperCAmelCase__				:     str = None ,			**UpperCAmelCase__				:     List[Any])						->np.ndarray:





           '''simple docstring'''

           A__			,							A__							=   get_image_size(lowerCAmelCase__)
           # Rounds the height and width down to the closest multiple of size_divisor
           A__							=   height // size_divisor * size_divisor
           A__							=   width // size_divisor * size_divisor
           A__							=   resize(lowerCAmelCase__ ,			(new_h, new_w) ,			resample=lowerCAmelCase__ ,			data_format=lowerCAmelCase__ ,			**lowerCAmelCase__)
           return image


    def 	SCREAMING_SNAKE_CASE							(      self				:     Any ,			UpperCAmelCase__				:     Optional[int] ,			UpperCAmelCase__				:     Optional[Any] ,			UpperCAmelCase__				:     Optional[int] = None ,			**UpperCAmelCase__				:     Tuple)						->np.ndarray:





           '''simple docstring'''

           return rescale(image=lowerCAmelCase__ ,			scale=lowerCAmelCase__ ,			data_format=lowerCAmelCase__ ,			**lowerCAmelCase__)





    def 	SCREAMING_SNAKE_CASE							(      self				:     Any ,			UpperCAmelCase__				:     Tuple ,			UpperCAmelCase__				:     Optional[Any] = None ,			UpperCAmelCase__				:     Optional[Any] = None ,			UpperCAmelCase__				:     List[Any]=None ,			UpperCAmelCase__				:     List[str] = None ,			UpperCAmelCase__				:     Optional[int] = None ,			UpperCAmelCase__				:     List[str] = ChannelDimension.FIRST ,			**UpperCAmelCase__				:     List[Any] ,			)						->BatchFeature:





           '''simple docstring'''

           A__							=   do_resize if do_resize is not None else self.do_resize
           A__							=   do_rescale if do_rescale is not None else self.do_rescale
           A__							=   size_divisor if size_divisor is not None else self.size_divisor
           A__							=   resample if resample is not None else self.resample

           if do_resize and size_divisor is None:
                  raise ValueError('''size_divisor is required for resizing''')

           A__							=   make_list_of_images(lowerCAmelCase__)

           if not valid_images(lowerCAmelCase__):
                  raise ValueError('''Invalid image(s)''')

           # All transformations expect numpy arrays.
           A__							=   [to_numpy_array(lowerCAmelCase__) for img in images]

           if do_resize:
                  A__							=   [self.resize(lowerCAmelCase__ ,			size_divisor=lowerCAmelCase__ ,			resample=lowerCAmelCase__) for image in images]

           if do_rescale:
                  A__							=   [self.rescale(lowerCAmelCase__ ,			scale=1 / 255) for image in images]

           A__							=   [to_channel_dimension_format(lowerCAmelCase__ ,			lowerCAmelCase__) for image in images]

           A__							=   {'''pixel_values''': images}
           return BatchFeature(data=lowerCAmelCase__ ,			tensor_type=lowerCAmelCase__)








def SCREAMING_SNAKE_CASE    (	lowercase_						)       ->	str:



       """simple docstring"""

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

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

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

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

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

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







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



       """simple docstring"""

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

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

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


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


