main() {
  Execution directory: seg.out
  Reading examples {
    sample-data/seg.raw (0 examples so far)
  }
  Create phrase index from 2 examples
  Stats {
    numExamples = 2
    numWords = 14
    numPhrases = 324
  }
  Init parameters: random {
    AParams.output(seg.out/init.params)
  }
  Train: stage1
  Train: stage2 {
    Iteration 0/5: temperature = 1 {
      E-step {
        Example 0/2: train: logZ = NaN, logVZ = NaN, logCZ = NaN, elogZ = NaN, entropy = NaN, objective = NaN, accuracy = NaN
      }
      Inference complexity: 27/ << 27~0 >> /27 (2)
      train: logZ = -3.330, logVZ = -3.559, logCZ = -0.229, elogZ = NaN, entropy = NaN, objective = NaN, accuracy = NaN
      ... 1 lines omitted ...
    }
    Iteration 1/5: temperature = 1 {
      E-step {
        Example 0/2: train: logZ = NaN, logVZ = NaN, logCZ = NaN, elogZ = NaN, entropy = NaN, objective = NaN, accuracy = NaN
      }
      Inference complexity: 27/ << 27~0 >> /27 (2)
      train: logZ = -3.060, logVZ = -3.223, logCZ = -0.163, elogZ = NaN, entropy = NaN, objective = NaN, accuracy = 0.091
      ... 1 lines omitted ...
    }
    Iteration 2/5: temperature = 1 {
      E-step {
        Example 0/2: train: logZ = NaN, logVZ = NaN, logCZ = NaN, elogZ = NaN, entropy = NaN, objective = NaN, accuracy = NaN
      }
      Inference complexity: 27/ << 27~0 >> /27 (2)
      train: logZ = -2.961, logVZ = -3.060, logCZ = -0.099, elogZ = NaN, entropy = NaN, objective = NaN, accuracy = 0.417
      ... 1 lines omitted ...
    }
    ... 3 lines omitted ...
  }
  Execution directory: seg.out
}
