class_docstr: Resize to size.
  
  Args:
      size: Size (h, w) in pixels of the resized region or just one side.
      side: Which side to resize, if size is only of type int.
      resample: Resampling mode.
      align_corners: interpolation flag.
      antialias: if True, then image will be filtered with Gaussian before downscaling. No effect for upscaling.
      keepdim: whether to keep the output shape the same as input (True) or broadcast it
          to the batch form (False).
class_docstr_tok: ["Resize","to","size",".","Args",":","size",":","Size","(","h",",","w",")","in","pixels","of","the","resized","region","or","just","one","side",".","side",":","Which","side","to","resize",",","if","size","is","only","of","type","int",".","resample",":","Resampling","mode",".","align_corners",":","interpolation","flag",".","antialias",":","if","True",",","then","image","will","be","filtered","with","Gaussian","before","downscaling",".","No","effect","for","upscaling",".","keepdim",":","whether","to","keep","the","output","shape","the","same","as","input","(","True",")","or","broadcast","it","to","the","batch","form","(","False",")","."]
code: def __init__(
      self,
      size: Union[int, Tuple[int, int]],
      side: str = "short",
      resample: Union[str, int, Resample] = Resample.BILINEAR.name,
      align_corners: bool = True,
      antialias: bool = False,
      p: float = 1.0,
      keepdim: bool = False,
  ) -> None:
      super().__init__(
          p=1.0, same_on_batch=True, p_batch=p, keepdim=keepdim
      )
      self._param_generator = rg.ResizeGenerator(
          resize_to=size, side=side
      )
      self.flags = {
          "size": size,
          "side": side,
          "resample": Resample.get(resample),
          "align_corners": align_corners,
          "antialias": antialias,
      }
  
file_path: kornia/kornia/augmentation/_2d/geometric/resize.py
imports: from typing import Any, Dict, Optional, Tuple, Union
  import torch
  from kornia.augmentation import random_generator
  from kornia.augmentation._2d.geometric.base import GeometricAugmentationBase2D
  from kornia.constants import Resample
  from kornia.core import Tensor
  from kornia.geometry.transform import crop_by_transform_mat, get_perspective_transform, resize
  from kornia.utils import eye_like
label_desc: Use image node_id 1 to create a new Resize object from inherited base classes: GeometricAugmentationBase2D with example: obj = Resize(size, side, resample, align_corners, antialias, p, keepdim)