code: def main():
      conf = {"batch_size": 20}
  
      with experiment.record(
          name="sample", exp_conf=conf, writers={"web_api", "screen"}
      ):
          for i in range(10_000):
              values = {"loss": random()}
              # if i > 1000:
              #     raise RuntimeError('Testing error')
              # for j in range(0, 100):
              #     values[f'grad.fc.{j}.l1'] = random()
              #     values[f'grad.fc.{j}.l2'] = random()
              #     values[f'grad.fc.{j}.mean'] = random()
              #
              #     # values[f'param.fc.{j}.l1'] = random()
              #     # values[f'param.fc.{j}.l2'] = random()
              #     # values[f'param.fc.{j}.mean'] = random()
              #     #
              #     # values[f'module.fc.{j}.l1'] = random()
              #     # values[f'module.fc.{j}.l2'] = random()
              #     # values[f'module.fc.{j}.mean'] = random()
              #     #
              #     # values[f'time.fc.{j}.l1'] = random()
              #     # values[f'time.fc.{j}.l2'] = random()
              #     # values[f'time.fc.{j}.mean'] = random()
              tracker.save(i, values)
  
              if i % 1000 == 0:
                  tracker.new_line()
  
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types