Implemented batching for TicTacToe AI

TicTacToe_AI/Net/wandb/run-20200128_092953-yloo6l66/diff.patch

@@ -0,0 +1,67 @@
+diff --git a/TicTacToe_AI/Net/pytorch_ai.py b/TicTacToe_AI/Net/pytorch_ai.py
+index efea5ae..701918f 100644
+--- a/TicTacToe_AI/Net/pytorch_ai.py
++++ b/TicTacToe_AI/Net/pytorch_ai.py
+@@ -4,6 +4,9 @@ import torch.optim as optim
+ from torch import nn
+ import torch.nn.functional as F
+ from tqdm import tqdm
++import wandb
++
++wandb.init(project="tictactoe")
+ 
+ 
+ def to_set(raw_list):
+@@ -46,7 +49,7 @@ def buildsets():
+         testset = to_set(alllines[0:10000])
+ 
+         print('Generating trainset...')
+-        trainset = to_set(alllines[10001:200000])
++        trainset = to_set(alllines[10001:])
+ 
+     return trainset, testset
+ 
+@@ -60,6 +63,7 @@ def testnet(net, testset):
+             if torch.argmax(output) == label[0]:
+                 correct += 1
+             total += 1
++    wandb.log({'test_accuracy': correct / total})
+     print("Accuracy: ", round(correct / total, 3))
+ 
+ 
+@@ -79,7 +83,15 @@ class Net(torch.nn.Module):
+         return F.log_softmax(x, dim=1)
+ 
+ 
+-net = torch.load('./nets/net_3.pt')
++device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
++print('running on %s' % device)
++
++# net = torch.load('./nets/net_3.pt')
++
++net = Net()
++wandb.watch(net)
++
++net.to(device)
+ 
+ optimizer = optim.Adam(net.parameters(), lr=0.001)
+ 
+@@ -87,13 +99,16 @@ trainset, testset = buildsets()
+ 
+ for epoch in range(100):
+     print('Epoch: ' + str(epoch))
++    wandb.log({'epoch': epoch})
+     for X, label in tqdm(trainset):
+         net.zero_grad()
++        X.to(device)
+         output = net(X)
++        output.cpu()
+         loss = F.nll_loss(output.view(1, 10), label[0])
+         loss.backward()
+         optimizer.step()
++        wandb.log({'loss': loss})
+ 
+-    print(loss)
+-    torch.save(net, './nets/net_' + str(epoch + 3) + '.pt')
++    torch.save(net, './nets/gpunets/net_' + str(epoch) + '.pt')
+     testnet(net, testset)