

"""simple docstring"""






from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_vision_available():
	import PIL


_lowerCamelCase     =  logging.get_logger(__name__)


class 			lowerCamelCase_		(			lowercase   ):





				"""simple docstring"""







				_lowerCAmelCase      :      Tuple      							=					["pixel_values"]



				def __init__(						self       ,		UpperCAmelCase__ = True       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = PILImageResampling.BICUBIC       ,		UpperCAmelCase__ = True       ,		UpperCAmelCase__ = 1 / 255       ,		UpperCAmelCase__ = True       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = True       ,		**UpperCAmelCase__       ,		):
								super().__init__(**UpperCAmelCase__     )
								SCREAMING_SNAKE_CASE__     							=				size if size is not None else {"height": 384, "width": 384}
								SCREAMING_SNAKE_CASE__     							=				get_size_dict(UpperCAmelCase__       ,		default_to_square=UpperCAmelCase__     )

								SCREAMING_SNAKE_CASE__     							=				do_resize
								SCREAMING_SNAKE_CASE__     							=				size
								SCREAMING_SNAKE_CASE__     							=				resample
								SCREAMING_SNAKE_CASE__     							=				do_rescale
								SCREAMING_SNAKE_CASE__     							=				rescale_factor
								SCREAMING_SNAKE_CASE__     							=				do_normalize
								SCREAMING_SNAKE_CASE__     							=				image_mean if image_mean is not None else OPENAI_CLIP_MEAN
								SCREAMING_SNAKE_CASE__     							=				image_std if image_std is not None else OPENAI_CLIP_STD
								SCREAMING_SNAKE_CASE__     							=				do_convert_rgb



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = PILImageResampling.BICUBIC       ,		UpperCAmelCase__ = None       ,		**UpperCAmelCase__       ,		):
								SCREAMING_SNAKE_CASE__     							=				get_size_dict(UpperCAmelCase__       ,		default_to_square=UpperCAmelCase__     )
								if "height" not in size or "width" not in size:
												raise ValueError(f'''The `size` dictionary must contain the keys `height` and `width`. Got {size.keys()}'''     )
								SCREAMING_SNAKE_CASE__     							=				(size["height"], size["width"])
								return resize(UpperCAmelCase__       ,		size=UpperCAmelCase__       ,		resample=UpperCAmelCase__       ,		data_format=UpperCAmelCase__       ,		**UpperCAmelCase__     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = None       ,		**UpperCAmelCase__       ,		):
								return rescale(UpperCAmelCase__       ,		scale=UpperCAmelCase__       ,		data_format=UpperCAmelCase__       ,		**UpperCAmelCase__     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = None       ,		**UpperCAmelCase__       ,		):
								return normalize(UpperCAmelCase__       ,		mean=UpperCAmelCase__       ,		std=UpperCAmelCase__       ,		data_format=UpperCAmelCase__       ,		**UpperCAmelCase__     )






				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = ChannelDimension.FIRST       ,		**UpperCAmelCase__       ,		):
								SCREAMING_SNAKE_CASE__     							=				do_resize if do_resize is not None else self.do_resize
								SCREAMING_SNAKE_CASE__     							=				resample if resample is not None else self.resample
								SCREAMING_SNAKE_CASE__     							=				do_rescale if do_rescale is not None else self.do_rescale
								SCREAMING_SNAKE_CASE__     							=				rescale_factor if rescale_factor is not None else self.rescale_factor
								SCREAMING_SNAKE_CASE__     							=				do_normalize if do_normalize is not None else self.do_normalize
								SCREAMING_SNAKE_CASE__     							=				image_mean if image_mean is not None else self.image_mean
								SCREAMING_SNAKE_CASE__     							=				image_std if image_std is not None else self.image_std
								SCREAMING_SNAKE_CASE__     							=				do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

								SCREAMING_SNAKE_CASE__     							=				size if size is not None else self.size
								SCREAMING_SNAKE_CASE__     							=				get_size_dict(UpperCAmelCase__       ,		default_to_square=UpperCAmelCase__     )

								SCREAMING_SNAKE_CASE__     							=				make_list_of_images(UpperCAmelCase__     )

								if not valid_images(UpperCAmelCase__     ):
												raise ValueError(
												    "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
												    "torch.Tensor, tf.Tensor or jax.ndarray."     )

								if do_resize and size is None or resample is None:
												raise ValueError("Size and resample must be specified if do_resize is True."     )

								if do_rescale and rescale_factor is None:
												raise ValueError("Rescale factor must be specified if do_rescale is True."     )

								if do_normalize and (image_mean is None or image_std is None):
												raise ValueError("Image mean and std must be specified if do_normalize is True."     )

								# PIL RGBA images are converted to RGB
								if do_convert_rgb:
												SCREAMING_SNAKE_CASE__     							=				[convert_to_rgb(UpperCAmelCase__     ) for image in images]

								# All transformations expect numpy arrays.
								SCREAMING_SNAKE_CASE__     							=				[to_numpy_array(UpperCAmelCase__     ) for image in images]

								if do_resize:
												SCREAMING_SNAKE_CASE__     							=				[self.resize(image=UpperCAmelCase__       ,		size=UpperCAmelCase__       ,		resample=UpperCAmelCase__     ) for image in images]

								if do_rescale:
												SCREAMING_SNAKE_CASE__     							=				[self.rescale(image=UpperCAmelCase__       ,		scale=UpperCAmelCase__     ) for image in images]

								if do_normalize:
												SCREAMING_SNAKE_CASE__     							=				[self.normalize(image=UpperCAmelCase__       ,		mean=UpperCAmelCase__       ,		std=UpperCAmelCase__     ) for image in images]

								SCREAMING_SNAKE_CASE__     							=				[to_channel_dimension_format(UpperCAmelCase__       ,		UpperCAmelCase__     ) for image in images]

								SCREAMING_SNAKE_CASE__     							=				BatchFeature(data={"pixel_values": images}       ,		tensor_type=UpperCAmelCase__     )

								return encoded_outputs




"""simple docstring"""






def __lowercase     (      lowerCamelCase_  :      Tuple  ):
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__     							=				{
				    "^": 3,
				    "*": 2,
				    "/": 2,
				    "%": 2,
				    "+": 1,
				    "-": 1,
				}  # Priority of each operator
				SCREAMING_SNAKE_CASE__     							=				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 __lowercase     (      lowerCamelCase_  :      str  ):
				SCREAMING_SNAKE_CASE__     							=				list(infix[::-1]  )  # reverse the infix equation

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

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


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