code: def batch_stats():
      train_cli = tw.WatcherClient()
      stream = train_cli.create_stream(
          event_name="batch",
          expr="lambda v:(v.metrics.epochf, v.metrics.batch_loss)",
          throttle=0.75,
      )
  
      train_loss = tw.Visualizer(
          stream,
          clear_after_end=False,
          vis_type="mpl-line",
          xtitle="Epoch",
          ytitle="Train Loss",
      )
  
      # train_acc = tw.Visualizer('lambda v:(v.metrics.epochf, v.metrics.epoch_loss)', event_name="batch",
      #                     xtitle='Epoch', ytitle='Train Accuracy', clear_after_end=False, yrange=(0,1),
      #                     vis=train_loss, vis_type='mpl-line')
  
      train_loss.show()
      tw.plt_loop()
  
file_path: tensorwatch/test/mnist/cli_mnist.py
imports: import tensorwatch
  import time
  import math
  from tensorwatch import utils
label_desc: Use image node_id 7 for calling a global function with example usage: batch_stats() without return types