code: def __init__(self, *args, **kwargs):
      self.mean = kwargs["mean"]
      self.std = kwargs["std"]
      self.to_bgr255 = kwargs["to_bgr255"]
      self.pad_size = kwargs["pad_size"]
      if self.pad_size > 0:
          warnings.warn(
              f"You are setting pad_size > 0, tensor will be padded to a fix size of"
              f"{self.pad_size}. "
              f"The image_mask will cover the pad_size of {self.pad_size} instead of"
              "the original size."
          )
  
imports: import collections
  import math
  import random
  import warnings
  import torch
  from mmf.common.constants import INCEPTION_IMAGE_NORMALIZE
  from mmf.common.registry import registry
  from mmf.datasets.processors.processors import BaseProcessor
  from omegaconf import OmegaConf
  from torchvision import transforms
  from torchvision.transforms import Compose, Normalize, Resize, ToTensor
label_desc: Use image node_id 1 to create a new NormalizeBGR255 object from inherited base classes: BaseProcessor with example: obj = NormalizeBGR255()