code: def sampled_predictions():
      predictions = np.stack(
          [
              np.histogram(
                  np.random.rand(5),
                  bins=np.linspace(-0.5, 0.5, NUM_CLASSES + 1),
              )[0]
              for _ in range(BATCH_SIZE * NUM_ITERATIONS)
          ]
      ).reshape([BATCH_SIZE, NUM_ITERATIONS, NUM_CLASSES])
      return np.rollaxis(predictions, -1, 1)
  
imports: import numpy
  import pytest
  from scipy.stats import entropy
  from baal.active.heuristics import BALD, Entropy
  from baal.active.heuristics.stochastics import GibbsSampling, RankBasedSampling, PowerSampling
label_desc: Use image node_id 1 for calling a global function with example usage: sampled_predictions() and returns: np