train_offset = np.zeros(dimension)
  train_offset[0] = 1 / np.sqrt(dimension)
  test_offset = np.zeros(dimension)
  test_offset[1] = 1 / np.sqrt(dimension)
  if dimension > 2:
    test_offset[2] = 1 / np.sqrt(dimension)
  train_dataset = Dataset(
      dataset_size=config.batch_size * 500,
      pattern_density=SETUPS[Dataset][dimension]['pattern_density'],
      noise_density=SETUPS[Dataset][dimension]['noise_density'],
      normal_offset=train_offset,
      quantization_size=0.025,
      dimension=dimension)
  test_dataset = Dataset(
      dataset_size=400,
      pattern_density=SETUPS[Dataset][dimension]['pattern_density'],
      noise_density=SETUPS[Dataset][dimension]['noise_density'],
      normal_offset=test_offset,
      quantization_size=0.025,
      dimension=dimension)