docstr: @notice: avoid in-place ops.
  https://discuss.pytorch.org/t/encounter-the-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation/836/3
docstr_tok: ["@","notice",":","avoid","in-place","ops",".","https",":","\/\/discuss.pytorch.org\/t\/encounter-the-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation\/836\/3"]
code: def __init__(self, epsilon=1e-8):
      """
      @notice: avoid in-place ops.
      https://discuss.pytorch.org/t/encounter-the-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation/836/3
      """
      super(InstanceNorm, self).__init__()
      self.epsilon = epsilon
  
imports: import os
  import time
  import timm
  import glob
  import numpy
  import os.path
  import torch
  import torch.distributed
  from torch import nn
  import torch.nn.functional
  from .iresnet import get_model
label_desc: Use image node_id 1 to create a new InstanceNorm object from inherited base classes: nn with example: obj = InstanceNorm(epsilon)