code: def tucker_normalize(tucker_tensor):
      core, factors = tucker_tensor
      normalized_factors = []
      for i, factor in enumerate(factors):
          scales = ivy.sqrt(ivy.sum(ivy.abs(factor) ** 2, axis=0))
          scales_non_zero = ivy.where(
              scales == 0,
              ivy.ones(ivy.shape(scales), dtype=factor[0].dtype),
              scales,
          )
          core = core * ivy.reshape(
              scales,
              (1,) * i + (-1,) + (1,) * (len(core.shape) - i - 1),
          )
          normalized_factors.append(
              factor / ivy.reshape(scales_non_zero, (1, -1))
          )
      return TuckerTensor((core, normalized_factors))
  
imports: from .base import FactorizedTensor
  import ivy
  from copy import deepcopy
  import warnings
label_desc: Use image node_id 15 for calling the TuckerTensor obj's underlying member method code with example usage: obj.tucker_normalize(tucker_tensor) and returns: TuckerTensor