class_docstr: Module for calculating RKD Distance Loss
  
  :param dist_ratio (float): Distance ratio for RKD loss if used
  :param angle_ratio (float): Angle ratio for RKD loss if used
  :param normalize (boolean): Normalize the input before calculating loss.
class_docstr_tok: ["Module","for","calculating","RKD","Distance","Loss",":","param","dist_ratio","(","float",")",":","Distance","ratio","for","RKD","loss","if","used",":","param","angle_ratio","(","float",")",":","Angle","ratio","for","RKD","loss","if","used",":","param","normalize","(","boolean",")",":","Normalize","the","input","before","calculating","loss","."]
code: def __init__(self, dist_ratio=0.5, angle_ratio=0.5, normalize=True):
      super(RKDLoss, self).__init__()
      self.dist_ratio = dist_ratio
      self.angle_ratio = angle_ratio
      self.normalize = normalize
  
file_path: KD_Lib/KD_Lib/KD/vision/RKD/loss_metric.py
imports: import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 1 to create a new RKDLoss object from inherited base classes: nn with example: obj = RKDLoss(dist_ratio, angle_ratio, normalize)