code: def instance_norm(data, gamma, beta, axis, epsilon=1e-5):
      """Instance normalization operator.
  
      Parameters
      ----------
      data : tvm.te.Tensor
          N-D with shape (d_0, d_1, ..., d_{N-1})
  
      gamma: tvm.te.Tensor
          K-D with shape (r_0, r_1, ..., r_{K-1}) where K == len(axis) and d_{axis_k} == r_k
  
      beta: tvm.te.Tensor
          Optional, K-D with shape (r_0, r_1, ..., r_{K-1}) where K == len(axis) and d_{axis_k} == r_k
  
      axis : list of int
          Axis over the normalization applied (the axis along which the mean and variance are
          computed)
  
      epsilon : float
          The epsilon value to avoid division by zero.
  
      Returns
      -------
      result : tvm.te.Tensor
          N-D with shape (d_0, d_1, ..., d_{N-1})
      """
      return cpp.nn.instance_norm(data, gamma, beta, axis, epsilon)
  
label_desc: Use image node_id 1 for calling a global function with example usage: instance_norm(data, gamma, beta, axis, epsilon) and returns: cpp