code: def negative_normal_likelihood(self, F, y, mu, sigma):
      return (
          F.log(sigma)
          + 0.5 * math.log(2 * math.pi)
          + 0.5 * F.square((y - mu) / sigma)
      )
  
file_path: gluonts/src/gluonts/mx/model/deep_factor/_network.py
imports: from typing import Tuple
  import math
  from mxnet.gluon import HybridBlock, nn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.block.feature import FeatureEmbedder
label_desc: Use image node_id 4 for calling the DeepFactorNetworkBase obj's underlying member method code with example usage: obj.negative_normal_likelihood(F, y, mu, sigma) and returns: unknown