def _output_actual(self):
"""Output actual usage so far."""
energy_usages = self.tracker.total_energy_per_epoch()
energy = energy_usages.sum()
times = self.tracker.epoch_times
time = np.sum(times)
_co2eq = self._co2eq(energy)
conversions = co2eq.convert(_co2eq) if self.interpretable else None
self._output_energy(
f"Actual consumption for {self.epoch_counter} epoch(s):", time,
energy, _co2eq, conversions)
def _output_pred(self):
"""Output predicted usage for full training epochs."""
epoch_energy_usages = self.tracker.total_energy_per_epoch()
epoch_times = self.tracker.epoch_times
pred_energy = predictor.predict_energy(self.epochs,
epoch_energy_usages)
pred_time = predictor.predict_time(self.epochs, epoch_times)
pred_co2eq = self._co2eq(pred_energy, pred_time)
conversions = co2eq.convert(pred_co2eq) if self.interpretable else None
self._output_energy(
f"Predicted consumption for {self.epochs} epoch(s):", pred_time,
pred_energy, pred_co2eq, conversions)