From db103d5b8bda9dd7794396964f6e0636692fef63 Mon Sep 17 00:00:00 2001
From: Hyeongmin Moon <mohomin123@gmail.com>
Date: Fri, 11 Feb 2022 11:36:13 +0900
Subject: [PATCH] fix log

I found total_loss is accumulated during the whole epochs(100 epochs).
fixed this so that log can print right loss per epoch.
---
 08-AutoEncoder/conv_autoencoder.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/08-AutoEncoder/conv_autoencoder.py b/08-AutoEncoder/conv_autoencoder.py
index 005f9c0..144f3be 100644
--- a/08-AutoEncoder/conv_autoencoder.py
+++ b/08-AutoEncoder/conv_autoencoder.py
@@ -64,8 +64,9 @@ def forward(self, x):
 criterion = nn.MSELoss()
 optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate,
                              weight_decay=1e-5)
-total_loss = 0
+
 for epoch in range(num_epochs):
+    total_loss = 0
     for data in dataloader:
         img, _ = data
         img = Variable(img).cuda()
@@ -76,8 +77,8 @@ def forward(self, x):
         optimizer.zero_grad()
         loss.backward()
         optimizer.step()
+        total_loss += loss.data
     # ===================log========================
-    total_loss += loss.data
     print('epoch [{}/{}], loss:{:.4f}'
           .format(epoch+1, num_epochs, total_loss))
     if epoch % 10 == 0: