code: def calculate_loss(input1, input2):
      output = pairwise_distance(input1, input2)
      loss = torch.sum(output, 1)
      loss = torch.sqrt(loss)
      return loss
  
imports: import argparse
  import numpy
  import torch
  import torch.nn
  import torch.optim
  import torchvision
  from torch.optim.lr_scheduler import StepLR
  from torch.utils.data import DataLoader, Dataset
  from torchvision import datasets
  from ignite.contrib.handlers import ProgressBar
  from ignite.engine import Engine, Events
  from ignite.handlers.param_scheduler import LRScheduler
  from ignite.metrics import Accuracy, RunningAverage
  from ignite.utils import manual_seed
label_desc: Use image node_id 2 for calling a global function with example usage: calculate_loss(input1, input2) and returns: loss