code: def __init__(self, size, fill=0, padding_mode="constant"):
      super().__init__()
      size = tuple(
          T._setup_size(
              size,
              error_msg="Please provide only two dimensions (h, w) for size.",
          )
      )
      self.crop_height = size[0]
      self.crop_width = size[1]
      self.fill = fill  # TODO: Fill is currently respected only on PIL. Apply tensor patch.
      self.padding_mode = padding_mode
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torchvision
  from torch import nn, Tensor
  from torchvision import ops
  from torchvision.transforms import functional, InterpolationMode, transforms
label_desc: Use image node_id 1 to create a new FixedSizeCrop object from inherited base classes: nn with example: obj = FixedSizeCrop(size, fill, padding_mode)