class_docstr: Dummy clustering estimator.
      
docstr: Get cluster ids
docstr_tok: ["Get","cluster","ids"]
code: def predict(self, X):
      """Get cluster ids"""
      if self.type == 1:
          p = np.ones(X.shape[0])
          n = int(np.floor(X.shape[0] / 2))
          p[:n] = 0
      elif self.type == 2:
          p = np.arange(X.shape[0]) % 3
      return p
  
imports: import os
  import subprocess
  import numpy
  from mlens import config
  from mlens.utils import IdTrain
  from mlens.index import FoldIndex, BlendIndex, SubsetIndex, TemporalIndex, ClusteredSubsetIndex, FullIndex
  from mlens.index.base import partition, prune_train
label_desc: Use image node_id 3 for calling the ClusterEstimator obj's underlying member method code with example usage: obj.predict(X) and returns: p