class_docstr: _EfficientKMeans is primarily used by palettization to perform a k-means operation. This class also has an in-house
  implementation of k-means, called ``kmeans_pp`` which runs entirely on GPU and is ~10x faster than sklearn's API.
code: def backtrace(self, P, T, i, m):
      if m >= 0:
          P = [m] + P
  
      if m == 0:
          return P
  
      return self.backtrace(P, T, i - 1, T[i - 1][m - 1])
  
file_path: coremltools/coremltools/optimize/torch/palettization/_efficient_kmeans.py
imports: import numpy
  import torch
  import torch.distributed
label_desc: Use image node_id 6 for calling the _EfficientKMeans obj's underlying member method code with example usage: obj.backtrace(P, T, i, m) and returns: self, P