update code

Rynnn1024 · Feb 18, 2020 · 30c4d8a · 30c4d8a
1 parent 0eacea3
commit 30c4d8a
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Showing 2 changed files with 6 additions and 5 deletions.
diff --git a/pytorch_learning/Test4_googlenet/model.py b/pytorch_learning/Test4_googlenet/model.py
@@ -10,6 +10,7 @@ def __init__(self, num_classes=1000, aux_logits=True, init_weights=False):
 
         self.conv1 = BasicConv2d(3, 64, kernel_size=7, stride=2, padding=3)
         self.maxpool1 = nn.MaxPool2d(3, stride=2, ceil_mode=True)
+
         self.conv2 = BasicConv2d(64, 64, kernel_size=1)
         self.conv3 = BasicConv2d(64, 192, kernel_size=3, padding=1)
         self.maxpool2 = nn.MaxPool2d(3, stride=2, ceil_mode=True)
@@ -23,12 +24,12 @@ def __init__(self, num_classes=1000, aux_logits=True, init_weights=False):
         self.inception4c = Inception(512, 128, 128, 256, 24, 64, 64)
         self.inception4d = Inception(512, 112, 144, 288, 32, 64, 64)
         self.inception4e = Inception(528, 256, 160, 320, 32, 128, 128)
-        self.maxpool4 = nn.MaxPool2d(2, stride=2, ceil_mode=True)
+        self.maxpool4 = nn.MaxPool2d(3, stride=2, ceil_mode=True)
 
         self.inception5a = Inception(832, 256, 160, 320, 32, 128, 128)
         self.inception5b = Inception(832, 384, 192, 384, 48, 128, 128)
 
-        if aux_logits:
+        if self.aux_logits:
             self.aux1 = InceptionAux(512, num_classes)
             self.aux2 = InceptionAux(528, num_classes)
 

diff --git a/pytorch_learning/Test4_googlenet/train.py b/pytorch_learning/Test4_googlenet/train.py
@@ -47,8 +47,8 @@
                                               batch_size=batch_size, shuffle=False,
                                               num_workers=0)
 
-test_data_iter = iter(validate_loader)
-test_image, test_label = test_data_iter.next()
+# test_data_iter = iter(validate_loader)
+# test_image, test_label = test_data_iter.next()
 
 # net = torchvision.models.googlenet(num_classes=5)
 # model_dict = net.state_dict()
@@ -66,7 +66,7 @@
 
 best_acc = 0.0
 save_path = './googleNet.pth'
-for epoch in range(2):
+for epoch in range(30):
     # train
     net.train()
     running_loss = 0.0