Add typical training script and some bug fixes

1. Resolve deprecated scheduler stepping issue
2. Make losses in the same scale(replace mean with sum in separate triplet loss, enlarge pose similarity loss 10x)
3. Add ReLU when compute distance in triplet loss
4. Remove classes except Model from `models` package init

1 files changed, 3 insertions, 3 deletions

diff --git a/models/model.py b/models/model.py
index bf8b5fb..1dc0f23 100644
--- a/models/model.py
+++ b/models/model.py
@@ -9,7 +9,7 @@ from torch.utils.data import DataLoader
 from torch.utils.data.dataloader import default_collate
 from torch.utils.tensorboard import SummaryWriter
 
-from models import RGBPartNet
+from models.rgb_part_net import RGBPartNet
 from utils.configuration import DataloaderConfiguration, \
     HyperparameterConfiguration, DatasetConfiguration, ModelConfiguration, \
     SystemConfiguration
@@ -116,7 +116,7 @@ class Model:
             loss.backward()
             self.optimizer.step()
             # Step scheduler
-            self.scheduler.step(self.curr_iter)
+            self.scheduler.step()
 
             # Write losses to TensorBoard
             self.writer.add_scalar('Loss/all', loss.item(), self.curr_iter)
@@ -129,7 +129,7 @@ class Model:
                 print('{0:5d} loss: {1:.3f}'.format(self.curr_iter, loss),
                       '(xrecon = {:f}, pose_sim = {:f},'
                       ' cano_cons = {:f}, ba_trip = {:f})'.format(*metrics),
-                      'lr:', self.scheduler.get_last_lr())
+                      'lr:', self.scheduler.get_last_lr()[0])
 
             if self.curr_iter % 1000 == 0:
                 torch.save({