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unroll print loss

This commit is contained in:
chenzomi 2020-06-30 10:16:45 +08:00
parent 412e4580d4
commit ff042b92ce
1 changed files with 3 additions and 7 deletions
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10
mindspore/train/callback/_loss_monitor.py
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@ -67,7 +67,6 @@ class LossMonitor(Callback):
def step_end(self, run_context):
cb_params = run_context.original_args()
step_mseconds = (time.time() - self.step_time) * 1000
step_loss = cb_params.net_outputs
if isinstance(step_loss, (tuple, list)) and isinstance(step_loss[0], Tensor):
@ -85,9 +84,6 @@ class LossMonitor(Callback):
cur_step_in_epoch, cb_params.batch_num))
if self._per_print_times != 0 and cb_params.cur_step_num % self._per_print_times == 0:
print("Epoch: [{:3d}/{:3d}], step: [{:5d}/{:5d}], "
"loss: [{:5.4f}/{:5.4f}], time: [{:5.4f}]".format(
cb_params.cur_epoch_num, cb_params.epoch_num,
cur_step_in_epoch, int(cb_params.batch_num),
step_loss, np.mean(self.losses),
step_mseconds), flush=True)
print("epoch: {} step {}, loss is {}".format(cb_params.cur_epoch_num,
cur_step_in_epoch,
step_loss), flush=True)