code: def loss_function(pred, label):
      """
      Compute loss.
      """
      loss = F.mean(F.softmax_cross_entropy(pred, label))
      return loss
  
file_path: nnabla/tutorial/finetuning.py
imports: import os
  import importlib
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  import nnabla.solvers
  import numpy
  from nnabla.ext_utils import get_extension_context
  from nnabla.monitor import Monitor, MonitorSeries, MonitorTimeElapsed
  from nnabla.utils.nnp_graph import NnpLoader, NnpNetworkPass
  from nnabla.utils.image_utils import imread
  from nnabla.utils.data_iterator import data_iterator_simple
  import argparse
label_desc: Use image node_id 3 for calling a global function with example usage: loss_function(pred, label) and returns: loss