test_loop.py

def test_loop_fn(loader):
  loss_,iou_,acc_=0.,0.,0.,
  model.eval()
  with torch.no_grad():
    for image, mask in  loader:
      image = image.to(device)
      mask=mask.to(device)
      y_pred= model(image)
      loss = loss_fn(y_pred, mask)
      loss_+= loss.item()
      ACC=acc(y_pred,mask)
      IOU= iou_metric(y_pred,mask)
      acc_+=ACC.item()
      iou_+=IOU.item()
  loss_ /=len(loader)
  iou_/=len(loader)
  acc_/=(len(val)*1.0*101*101
  early_stopping(iou_,model)
  print('Validation: Loss={:.5f},IOU={:.3f} ACC={:.3f}'.format(
      loss_,iou_,acc_))
  return loss_,iou_,acc_