diff --git a/torchreid/engine/image/triplet.py b/torchreid/engine/image/triplet.py index 406f378..abf5ead 100644 --- a/torchreid/engine/image/triplet.py +++ b/torchreid/engine/image/triplet.py @@ -126,20 +126,18 @@ def train(self, epoch, max_epoch, trainloader, fixbase_epoch=0, open_layers=None # write to Tensorboard & comet.ml - ''' - self.writer.add_scalars('optim/accs',accs.val,global_step) + #self.writer.add_scalars('optim/accs',accs.val,global_step) self.experiment.log_metric('optim/accs',accs.val,step=global_step) - self.writer.add_scalar('optim/loss',losses.val,global_step) # loss, loss.item() or losses.val ?? + #self.writer.add_scalar('optim/loss',losses.val,global_step) # loss, loss.item() or losses.val ?? self.experiment.log_metric('optim/loss',losses.val,step=global_step) - self.writer.add_scalar('optim/loss_triplet',losses_t.val,global_step) + #self.writer.add_scalar('optim/loss_triplet',losses_t.val,global_step) self.experiment.log_metric('optim/loss_triplet',losses_t.val,step=global_step) - self.writer.add_scalar('optim/loss_softmax',losses_x.val,global_step) + #self.writer.add_scalar('optim/loss_softmax',losses_x.val,global_step) self.experiment.log_metric('optim/loss_softmax',losses_x.val,step=global_step) - self.writer.add_scalar('optim/lr',self.optimizer.param_groups[0]['lr'],global_step) + #self.writer.add_scalar('optim/lr',self.optimizer.param_groups[0]['lr'],global_step) self.experiment.log_metric('optim/lr',self.optimizer.param_groups[0]['lr'],step=global_step) - ''' if (batch_idx+1) % print_freq == 0: # estimate remaining time