Skip to content
This repository has been archived by the owner on Nov 17, 2023. It is now read-only.

Optimization of metric evaluation #13471

Merged
merged 9 commits into from
Dec 13, 2018
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions python/mxnet/callback.py
Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,7 @@ def _callback(param):
logging.info('Iter[%d] Batch[%d] Train-%s=%f',
param.epoch, param.nbatch, name, value)
if auto_reset:
param.eval_metric.reset()
param.eval_metric.reset_local()
return _callback


Expand Down Expand Up @@ -164,7 +164,7 @@ def __call__(self, param):
if param.eval_metric is not None:
name_value = param.eval_metric.get_name_value()
if self.auto_reset:
param.eval_metric.reset()
param.eval_metric.reset_local()
msg = 'Epoch[%d] Batch [%d-%d]\tSpeed: %.2f samples/sec'
msg += '\t%s=%f'*len(name_value)
logging.info(msg, param.epoch, count-self.frequent, count, speed, *sum(name_value, ()))
Expand Down
Loading