code: def nll(self, sample, dims=[1, 2, 3]):
      if self.deterministic:
          return paddle.to_tensor([0.0])
      logtwopi = np.log(2.0 * np.pi)
      return 0.5 * paddle.sum(
          logtwopi
          + self.logvar
          + paddle.pow(sample - self.mean, 2) / self.var,
          axis=dims,
      )
  
imports: import numpy
  import paddle
  import paddle.nn
  from ..configuration_utils import ConfigMixin
  from ..configuration_utils import register_to_config
  from .unet_blocks import get_down_block
  from .unet_blocks import get_up_block
  from .unet_blocks import UNetMidBlock2D
label_desc: Use image node_id 4 for calling the DiagonalGaussianDistribution obj's underlying member method code with example usage: obj.nll(sample, dims) and returns: unknown, paddle