package code of pytorch 0.4.1 and 1.1.0

Author: AlexHex7

demo_MNIST.py renamed to Non-Local_pytorch_0.4.1_to_1.1.0/demo_MNIST.py

@@ -6,10 +6,10 @@
 import time
 
 
-def calc_acc(x, y):
-    x = torch.max(x, dim=-1)[1]
-    accuracy = sum(x == y) / x.size(0)
-    return accuracy
+# def calc_acc(x, y):
+#     x = torch.max(x, dim=-1)[1]
+#     accuracy = sum(x == y) / x.size(0)
+#     return accuracy
 
 
 train_data = torchvision.datasets.MNIST(root='./mnist', train=True,
@@ -44,7 +44,7 @@ def calc_acc(x, y):
             label_batch = label_batch.cuda()
 
         predict = net(img_batch)
-        acc = calc_acc(predict.cpu().data, label_batch.cpu().data)
+        # acc = calc_acc(predict.cpu().data, label_batch.cpu().data)
         loss = loss_func(predict, label_batch)
 
         net.zero_grad()

lib/network.py renamed to Non-Local_pytorch_0.4.1_to_1.1.0/lib/network.py

@@ -9,8 +9,8 @@ in **lib/network.py**.
 
 
 ## Environment
-- python 3.6 or python 3.7.3
-- pytorch 0.4.1 or pytorch 1.1.0
+- python 3.7.3
+- pytorch 1.2.0
 
 
 ## Update Records
@@ -25,6 +25,7 @@ old versions (**lib/non_loca.py** and **lib/non_local_simple_version.py**) into
 5. Modify the code to support pytorch 0.4.1, and move the code supporting pytorch 0.3.1 \
 to **Non-Local_pytorch_0.3.1/**.
 6. Test the code with pytorch 1.1.0 and it works.
+7. Move the code supporting pytorch 0.4.1 and 1.1.0 to **Non-Local_pytorch_0.4.1_to_1.1.0/**.
 
 ## Running Steps
 1. Select the type of non-local block in **lib/network.py**.