project deliverables

dysdsyd · Apr 28, 2020 · aff2bb8 · aff2bb8
1 parent 2990a24
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diff --git a/Eval.ipynb b/Eval.ipynb
diff --git a/data/Eval.ipynb b/data/Eval.ipynb
diff --git a/splits.ipynb → data/splits.ipynb b/splits.ipynb → data/splits.ipynb
diff --git a/tensorboard/p2m_gan/events.out.tfevents.1587601309.lh0033.arc-ts.umich.edu.21914.0 b/tensorboard/p2m_gan/events.out.tfevents.1587601309.lh0033.arc-ts.umich.edu.21914.0
diff --git a/tensorboard/p2m_gan/events.out.tfevents.1587610740.lh0033.arc-ts.umich.edu.14965.0 b/tensorboard/p2m_gan/events.out.tfevents.1587610740.lh0033.arc-ts.umich.edu.14965.0
diff --git a/tensorboard/p2m_randgan/events.out.tfevents.1587601355.lh0036.arc-ts.umich.edu.14887.0 b/tensorboard/p2m_randgan/events.out.tfevents.1587601355.lh0036.arc-ts.umich.edu.14887.0
diff --git a/tensorboard/p2m_randgan/events.out.tfevents.1587608224.lh0033.arc-ts.umich.edu.31729.0 b/tensorboard/p2m_randgan/events.out.tfevents.1587608224.lh0033.arc-ts.umich.edu.31729.0
diff --git a/...rboard/pixel2mesh_baseline/events.out.tfevents.1587601305.lh0033.arc-ts.umich.edu.21834.0 b/...rboard/pixel2mesh_baseline/events.out.tfevents.1587601305.lh0033.arc-ts.umich.edu.21834.0
diff --git a/train.py b/train.py
diff --git a/train_p2m_gan.py b/train_p2m_gan.py
@@ -196,7 +196,7 @@
         print("===> Epoch[{}]: Loss_D: {:.4f} Loss_G: {:.4f} Loss_Recon: {:.4f}".format(epoch, np.mean(D_losses), np.mean(G_losses), np.mean(trn_losses)))
         print("===> Epoch[{}]: Valid Loss: {:.4f}".format(epoch, np.mean(val_losses)))
         tb.add_scalar('data/Loss_G', np.mean(G_losses), epoch)
-        tb.add_scalar('data/loss_D', np.mean(D_losses), epoch)
+        tb.add_scalar('data/Loss_D', np.mean(D_losses), epoch)
         tb.add_scalar('data/Training_loss', np.mean(trn_losses), epoch) 
         tb.add_scalar('data/Validation_Loss',  np.mean(val_losses), epoch)
 

diff --git a/train_p2m_randgan.py b/train_p2m_randgan.py
@@ -215,8 +215,8 @@
 
 
         print("===> Epoch[{}]: Loss_D: {:.4f} Loss_G: {:.4f} Loss_Recon: {:.4f}".format(epoch, np.mean(D_losses), np.mean(G_losses), np.mean(trn_losses)))
-        tb.add_scalar('data/loss_G', np.mean(G_losses), epoch)
-        tb.add_scalar('data/loss_D', np.mean(D_losses), epoch)
+        tb.add_scalar('data/Loss_G', np.mean(G_losses), epoch)
+        tb.add_scalar('data/Loss_D', np.mean(D_losses), epoch)
         # tb.add_scalar('data/loss_E', np.mean(E_losses), epoch)
         tb.add_scalar('data/Training_loss', np.mean(trn_losses), epoch) 
         tb.add_scalar('data/Validation_Loss',  np.mean(val_losses), epoch)