def test_add_text():
# this will generate an event file under _LOGDIR and
# a json file called tensors.json under _LOGDIR/plugins/tensorboard_text/tensors.json
sw = SummaryWriter(logdir=_LOGDIR)
sw.add_text(tag='test_add_text', text='Hello MXNet!')
sw.close()
check_and_remove_logdir_for_text()
class LogTB(object):
def __init__(self, args):
print('--- Initializing Tensorboard')
self.tb = SummaryWriter(logdir=os.path.join(
args.ckpt_dir, 'log', 'train'))
self.tb.add_text(tag='config', text=str(args), global_step=0)
def log(self,
student,
context_str,
mlm_loss,
mlm_acc,
teacher_ce,
teacher_mse,
throughput,
lr,
duration,
latency,
n_total_iter):
logging.info(f"{context_str}loggging to Tensorboard at {n_total_iter}")
context_str = context_str.strip()
self.tb.add_scalar(tag=f"{context_str}/losses/mlm_loss", value=mlm_loss, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/losses/mlm_acc", value=mlm_acc, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/losses/teacher_ce", value=teacher_ce, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/losses/teacher_mse", value=teacher_mse, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/latency/throughput", value=throughput, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/latency/duration", value=duration, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/latency/latency", value=latency, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/learning_rate/lr", value=lr, global_step=n_total_iter)
self.tb.add_scalar(tag=f"{context_str}/global/memory_usage", value=psutil.virtual_memory()._asdict()['used'] / 1_000_000, global_step=n_total_iter)