Implemented batching for TicTacToe AI

This commit is contained in:
Clemens Dautermann 2020-01-28 14:45:00 +01:00
parent 55cff9b18f
commit 56ee2635b5
96 changed files with 8426 additions and 7 deletions

View file

@ -0,0 +1,9 @@
wandb_version: 1
_wandb:
desc: null
value:
cli_version: 0.8.22
framework: torch
is_jupyter_run: false
python_version: 3.7.5

View file

@ -0,0 +1,135 @@
diff --git a/TicTacToe_AI/Net/pytorch_ai.py b/TicTacToe_AI/Net/pytorch_ai.py
index efea5ae..8334765 100644
--- a/TicTacToe_AI/Net/pytorch_ai.py
+++ b/TicTacToe_AI/Net/pytorch_ai.py
@@ -4,6 +4,11 @@ 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")
+
+BATCH_SIZE = 15
def to_set(raw_list):
@@ -35,6 +40,40 @@ def to_set(raw_list):
return out_set
+def to_batched_set(raw_list):
+ counter = 0
+ out_set = []
+ boardtensor = torch.zeros((BATCH_SIZE, 1, 9))
+ labeltensor = torch.zeros(BATCH_SIZE, dtype=torch.long)
+ for line in tqdm(raw_list):
+ line = line.replace('\n', '')
+ raw_board, raw_label = line.split('|')[0], line.split('|')[1]
+
+ if not (int(raw_label) is -1):
+ labeltensor[counter] = int(raw_label)
+ else:
+ labeltensor[counter] = 9
+
+ raw_board = raw_board.split(',')
+ for n, block in enumerate(raw_board):
+ if int(block) is -1:
+ boardtensor[counter][0][n] = 0
+ elif int(block) is 0:
+ boardtensor[counter][0][n] = 0.5
+ elif int(block) is 1:
+ boardtensor[counter][0][n] = 1
+
+ if counter == (BATCH_SIZE - 1):
+ out_set.append([boardtensor, labeltensor])
+ boardtensor = torch.zeros((BATCH_SIZE, 1, 9))
+ labeltensor = torch.zeros(BATCH_SIZE, dtype=torch.long)
+ counter = 0
+ else:
+ counter += 1
+
+ return out_set
+
+
def buildsets():
with open('boards.bds', 'r') as infile:
print('Loading file...')
@@ -43,10 +82,10 @@ def buildsets():
random.shuffle(alllines)
print('Generating testset...')
- testset = to_set(alllines[0:10000])
+ testset = to_batched_set(alllines[0:10000])
print('Generating trainset...')
- trainset = to_set(alllines[10001:200000])
+ trainset = to_batched_set(alllines[10001:20000])
return trainset, testset
@@ -60,6 +99,7 @@ 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 +119,15 @@ 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 +135,18 @@ trainset, testset = buildsets()
for epoch in range(100):
print('Epoch: ' + str(epoch))
+ wandb.log({'epoch': epoch})
for X, label in tqdm(trainset):
+ print(X.shape)
+ print(label.shape)
net.zero_grad()
+ X.to(device)
output = net(X)
- loss = F.nll_loss(output.view(1, 10), label[0])
+ output.cpu()
+ loss = F.nll_loss(output.view(-1, 10), label)
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)
diff --git a/other_scripts/setcounter.py b/other_scripts/setcounter.py
index 9735f20..e9eb00c 100644
--- a/other_scripts/setcounter.py
+++ b/other_scripts/setcounter.py
@@ -7,9 +7,12 @@ data = datasets.MNIST('../datasets', train=True, download=True,
transforms.ToTensor()
]))
-loader = torch.utils.data.DataLoader(data, batch_size=1, shuffle=False)
+loader = torch.utils.data.DataLoader(data, batch_size=15, shuffle=False)
set = {'0': 0, '1': 0, '2': 0, '3': 0, '4': 0, '5': 0, '6': 0, '7': 0, '8': 0, '9': 0}
+for data in loader:
+ print(data[1].shape)
+
for _, label in tqdm(loader):
set[str(label[0].item())] += 1

View file

@ -0,0 +1,238 @@
running on cpu
Loading file...
986410
Generating testset...
0%| | 0/10000 [00:00<?, ?it/s] 3%|█▎ | 347/10000 [00:00<00:02, 3461.95it/s] 6%|██▏ | 580/10000 [00:00<00:03, 3018.65it/s] 9%|███▍ | 938/10000 [00:00<00:02, 3166.71it/s] 13%|████▋ | 1300/10000 [00:00<00:02, 3289.18it/s] 16%|█████▊ | 1622/10000 [00:00<00:02, 3266.47it/s] 20%|███████▏ | 1995/10000 [00:00<00:02, 3392.21it/s] 23%|████████▍ | 2343/10000 [00:00<00:02, 3416.22it/s] 27%|█████████▌ | 2660/10000 [00:00<00:02, 3314.88it/s] 30%|██████████▋ | 2981/10000 [00:00<00:02, 3280.43it/s] 33%|███████████▉ | 3326/10000 [00:01<00:02, 3327.29it/s] 37%|█████████████▎ | 3696/10000 [00:01<00:01, 3429.18it/s] 40%|██████████████▌ | 4038/10000 [00:01<00:01, 3423.89it/s] 44%|███████████████▊ | 4378/10000 [00:01<00:01, 3236.97it/s] 47%|████████████████▉ | 4702/10000 [00:01<00:01, 3117.76it/s] 50%|██████████████████ | 5015/10000 [00:01<00:02, 2461.36it/s] 53%|███████████████████ | 5284/10000 [00:01<00:01, 2479.04it/s] 55%|███████████████████▉ | 5548/10000 [00:01<00:02, 2187.80it/s] 58%|████████████████████▊ | 5784/10000 [00:02<00:02, 2036.79it/s] 60%|█████████████████████▌ | 6002/10000 [00:02<00:01, 2004.67it/s] 62%|██████████████████████▎ | 6213/10000 [00:02<00:02, 1505.19it/s] 64%|███████████████████████▏ | 6449/10000 [00:02<00:02, 1686.85it/s] 68%|████████████████████████▌ | 6808/10000 [00:02<00:01, 2005.53it/s] 71%|█████████████████████████▍ | 7073/10000 [00:02<00:01, 2163.20it/s] 74%|██████████████████████████▌ | 7384/10000 [00:02<00:01, 2379.31it/s] 77%|███████████████████████████▊ | 7719/10000 [00:02<00:00, 2605.07it/s] 80%|████████████████████████████▊ | 8015/10000 [00:02<00:00, 2692.98it/s] 83%|█████████████████████████████▉ | 8305/10000 [00:03<00:00, 2388.68it/s] 87%|███████████████████████████████▏ | 8663/10000 [00:03<00:00, 2652.11it/s] 90%|████████████████████████████████▍ | 9001/10000 [00:03<00:00, 2834.74it/s] 94%|█████████████████████████████████▋ | 9374/10000 [00:03<00:00, 3053.79it/s] 97%|███████████████████████████████████ | 9742/10000 [00:03<00:00, 3217.94it/s]Generating trainset...
100%|███████████████████████████████████| 10000/10000 [00:03<00:00, 2781.54it/s]
0%| | 0/9999 [00:00<?, ?it/s] 3%|█▏ | 323/9999 [00:00<00:03, 3224.48it/s] 6%|██▏ | 591/9999 [00:00<00:03, 3038.62it/s] 8%|███▏ | 845/9999 [00:00<00:03, 2867.57it/s] 10%|███▊ | 1033/9999 [00:00<00:03, 2474.68it/s] 13%|████▋ | 1277/9999 [00:00<00:03, 2439.35it/s] 15%|█████▍ | 1476/9999 [00:00<00:03, 2257.23it/s] 18%|██████▌ | 1769/9999 [00:00<00:03, 2424.05it/s] 21%|███████▊ | 2095/9999 [00:00<00:03, 2625.03it/s] 24%|████████▊ | 2374/9999 [00:00<00:02, 2670.86it/s] 26%|█████████▊ | 2637/9999 [00:01<00:02, 2590.42it/s] 29%|██████████▊ | 2923/9999 [00:01<00:02, 2665.49it/s] 32%|███████████▊ | 3189/9999 [00:01<00:02, 2491.89it/s] 34%|████████████▋ | 3440/9999 [00:01<00:03, 1682.45it/s] 36%|█████████████▍ | 3645/9999 [00:01<00:04, 1561.25it/s] 38%|██████████████▏ | 3828/9999 [00:01<00:03, 1575.58it/s] 40%|██████████████▉ | 4031/9999 [00:01<00:03, 1682.11it/s] 42%|███████████████▌ | 4215/9999 [00:02<00:03, 1578.92it/s] 44%|████████████████▏ | 4385/9999 [00:02<00:03, 1503.72it/s] 46%|████████████████▉ | 4584/9999 [00:02<00:03, 1621.80it/s] 48%|█████████████████▉ | 4837/9999 [00:02<00:02, 1817.52it/s] 51%|██████████████████▊ | 5071/9999 [00:02<00:02, 1927.99it/s] 54%|███████████████████▊ | 5356/9999 [00:02<00:02, 2134.97it/s] 57%|█████████████████████▏ | 5710/9999 [00:02<00:01, 2422.42it/s] 61%|██████████████████████▍ | 6078/9999 [00:02<00:01, 2698.46it/s] 64%|███████████████████████▊ | 6446/9999 [00:02<00:01, 2932.54it/s] 68%|█████████████████████████▏ | 6817/9999 [00:02<00:01, 3127.88it/s] 72%|██████████████████████████▌ | 7179/9999 [00:03<00:00, 3260.02it/s] 75%|███████████████████████████▊ | 7521/9999 [00:03<00:00, 3059.46it/s] 79%|█████████████████████████████ | 7867/9999 [00:03<00:00, 3168.65it/s] 82%|██████████████████████████████▍ | 8219/9999 [00:03<00:00, 3261.91it/s] 86%|███████████████████████████████▋ | 8554/9999 [00:03<00:00, 3164.81it/s] 89%|████████████████████████████████▊ | 8877/9999 [00:03<00:00, 3029.40it/s] 92%|█████████████████████████████████▉ | 9186/9999 [00:03<00:00, 3027.90it/s] 95%|███████████████████████████████████▏ | 9504/9999 [00:03<00:00, 3070.60it/s] 98%|████████████████████████████████████▎| 9814/9999 [00:03<00:00, 2988.52it/s] 100%|█████████████████████████████████████| 9999/9999 [00:03<00:00, 2520.75it/s]
Epoch: 0
torch.Size([15, 1, 9])
torch.Size([15])
0%| | 0/666 [00:00<?, ?it/s]torch.Size([15, 1, 9])
0%| | 1/666 [00:00<03:41, 3.00it/s]torch.Size([15])
0%|▏ | 2/666 [00:00<02:56, 3.75it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
1%|▎ | 4/666 [00:00<02:22, 4.65it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
1%|▎ | 5/666 [00:00<01:59, 5.54it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
1%|▍ | 7/666 [00:00<01:41, 6.47it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
1%|▌ | 8/666 [00:01<01:30, 7.23it/s]torch.Size([15, 1, 9])
torch.Size([15])
2%|▋ | 10/666 [00:01<01:20, 8.10it/s]torch.Size([15, 1, 9])
torch.Size([15])
2%|▋ | 11/666 [00:01<01:16, 8.56it/s]torch.Size([15, 1, 9])
torch.Size([15])
2%|▊ | 12/666 [00:01<01:13, 8.95it/s]torch.Size([15, 1, 9])
torch.Size([15])
2%|▊ | 13/666 [00:01<01:10, 9.24it/s]torch.Size([15, 1, 9])
torch.Size([15])
2%|▉ | 14/666 [00:01<01:08, 9.45it/s]torch.Size([15, 1, 9])
torch.Size([15])
2%|▉ | 15/666 [00:01<01:07, 9.61it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
3%|█ | 17/666 [00:01<01:06, 9.72it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
3%|█▏ | 19/666 [00:02<01:03, 10.14it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
3%|█▎ | 21/666 [00:02<01:03, 10.10it/s]torch.Size([15, 1, 9])
torch.Size([15])
3%|█▍ | 23/666 [00:02<01:02, 10.24it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
4%|█▌ | 25/666 [00:02<01:04, 10.00it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
4%|█▋ | 27/666 [00:02<01:08, 9.37it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
4%|█▊ | 28/666 [00:03<01:34, 6.76it/s]torch.Size([15, 1, 9])
torch.Size([15])
4%|█▊ | 29/666 [00:03<01:25, 7.48it/s]torch.Size([15, 1, 9])
torch.Size([15])
5%|█▉ | 31/666 [00:03<01:18, 8.09it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
5%|██ | 33/666 [00:03<01:12, 8.71it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
5%|██▏ | 35/666 [00:03<01:09, 9.06it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
6%|██▎ | 37/666 [00:04<01:07, 9.32it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
6%|██▍ | 39/666 [00:04<01:08, 9.10it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
6%|██▌ | 40/666 [00:04<01:07, 9.28it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
6%|██▋ | 42/666 [00:04<01:03, 9.79it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
7%|██▊ | 44/666 [00:04<01:01, 10.07it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
7%|██▉ | 46/666 [00:04<01:02, 10.00it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
7%|███ | 48/666 [00:05<01:00, 10.16it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
8%|███▏ | 50/666 [00:05<01:00, 10.11it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
8%|███▎ | 52/666 [00:05<01:06, 9.30it/s]torch.Size([15, 1, 9])
torch.Size([15])
8%|███▎ | 53/666 [00:05<01:06, 9.21it/s]torch.Size([15, 1, 9])
torch.Size([15])
8%|███▍ | 54/666 [00:05<01:06, 9.15it/s]torch.Size([15, 1, 9])
torch.Size([15])
8%|███▍ | 55/666 [00:05<01:09, 8.82it/s]torch.Size([15, 1, 9])
torch.Size([15])
8%|███▌ | 56/666 [00:06<01:22, 7.35it/s]torch.Size([15, 1, 9])
9%|███▌ | 57/666 [00:06<01:32, 6.58it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
9%|███▋ | 59/666 [00:06<01:20, 7.52it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
9%|███▊ | 61/666 [00:06<01:13, 8.24it/s]torch.Size([15, 1, 9])
torch.Size([15])
9%|███▉ | 63/666 [00:06<01:07, 8.96it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
10%|████ | 64/666 [00:06<01:05, 9.21it/s]torch.Size([15, 1, 9])
torch.Size([15])
10%|████▏ | 66/666 [00:07<01:02, 9.59it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
10%|████▎ | 68/666 [00:07<01:00, 9.86it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
11%|████▍ | 70/666 [00:07<00:59, 10.07it/s]torch.Size([15, 1, 9])
torch.Size([15])
11%|████▌ | 72/666 [00:07<00:57, 10.36it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
11%|████▋ | 74/666 [00:07<00:59, 9.94it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
11%|████▊ | 76/666 [00:08<01:01, 9.64it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
12%|████▉ | 78/666 [00:08<01:00, 9.74it/s]torch.Size([15, 1, 9])
torch.Size([15])
12%|████▉ | 79/666 [00:08<00:59, 9.82it/s]torch.Size([15, 1, 9])
torch.Size([15])
12%|█████ | 81/666 [00:08<00:57, 10.20it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
12%|█████▏ | 83/666 [00:08<01:00, 9.65it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
13%|█████▎ | 85/666 [00:09<00:57, 10.07it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
13%|█████▍ | 87/666 [00:09<00:58, 9.89it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
13%|█████▌ | 88/666 [00:09<00:58, 9.92it/s]torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
14%|█████▋ | 90/666 [00:09<00:56, 10.26it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
14%|█████▊ | 92/666 [00:09<00:55, 10.36it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
14%|█████▉ | 94/666 [00:09<00:54, 10.43it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
14%|██████ | 96/666 [00:10<00:54, 10.48it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
15%|██████▏ | 98/666 [00:10<00:56, 9.98it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
15%|██████▏ | 100/666 [00:10<00:54, 10.32it/s]torch.Size([15, 1, 9])
torch.Size([15])
15%|██████▎ | 102/666 [00:10<00:55, 10.22it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
16%|██████▍ | 104/666 [00:10<00:56, 9.98it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
16%|██████▌ | 106/666 [00:11<00:54, 10.32it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
16%|██████▋ | 108/666 [00:11<00:52, 10.59it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
17%|██████▊ | 110/666 [00:11<00:51, 10.78it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
17%|██████▉ | 112/666 [00:11<00:51, 10.72it/s]torch.Size([15, 1, 9])
torch.Size([15])
torch.Size([15, 1, 9])
torch.Size([15])
17%|███████ | 114/666 [00:11<00:50, 10.87it/s]torch.Size([15, 1, 9])
torch.Size([15])

View file

@ -0,0 +1,109 @@
apturl==0.5.2
argh==0.26.2
asn1crypto==0.24.0
bcrypt==3.1.6
binwalk==2.1.2
blinker==1.4
brlapi==0.6.7
certifi==2018.8.24
chardet==3.0.4
click==7.0
command-not-found==0.3
configparser==4.0.2
cryptography==2.6.1
cupshelpers==1.0
cycler==0.10.0
dbus-python==1.2.12
decorator==4.3.0
defer==1.0.6
distro-info==0.21ubuntu4
distro==1.3.0
docker-pycreds==0.4.0
duplicity==0.8.4
entrypoints==0.3
fasteners==0.12.0
future==0.16.0
gitdb2==2.0.6
gitpython==3.0.5
gql==0.2.0
graphql-core==1.1
httplib2==0.11.3
idna==2.6
keyring==18.0.1
keyrings.alt==3.1.1
kiwisolver==1.0.1
language-selector==0.1
launchpadlib==1.10.7
lazr.restfulclient==0.14.2
lazr.uri==1.0.3
lockfile==0.12.2
louis==3.10.0
macaroonbakery==1.2.3
mako==1.0.7
markupsafe==1.1.0
matplotlib==3.0.2
monotonic==1.5
netifaces==0.10.4
numpy==1.16.2
nvidia-ml-py3==7.352.0
oauth==1.0.1
oauthlib==2.1.0
olefile==0.46
paramiko==2.6.0
pathtools==0.1.2
pexpect==4.6.0
pillow==6.1.0
pip==18.1
promise==2.3
protobuf==3.6.1
psutil==5.6.7
pycairo==1.16.2
pycrypto==2.6.1
pycups==1.9.73
pygments==2.3.1
pygobject==3.34.0
pyjwt==1.7.0
pymacaroons==0.13.0
pynacl==1.3.0
pyopengl==3.1.0
pyparsing==2.2.0
pyqt5==5.12.3
pyqtgraph==0.11.0.dev0
pyrfc3339==1.1
python-apt==1.9.0+ubuntu1.3
python-dateutil==2.7.3
python-debian==0.1.36
pytz==2019.2
pyxdg==0.25
pyyaml==5.1.2
reportlab==3.5.23
requests-unixsocket==0.1.5
requests==2.21.0
scipy==1.2.2
secretstorage==2.3.1
sentry-sdk==0.14.0
setuptools==41.1.0
shortuuid==0.5.0
simplejson==3.16.0
sip==4.19.18
six==1.12.0
smmap2==2.0.5
subprocess32==3.5.4
system-service==0.3
systemd-python==234
torch==1.3.1+cpu
torchvision==0.4.2+cpu
tqdm==4.41.0
ubuntu-advantage-tools==19.5
ubuntu-drivers-common==0.0.0
ufw==0.36
unattended-upgrades==0.1
urllib3==1.24.1
usb-creator==0.3.7
virtualenv==15.1.0
wadllib==1.3.3
wandb==0.8.22
watchdog==0.9.0
wheel==0.32.3
xkit==0.0.0
zope.interface==4.3.2

View file

@ -0,0 +1 @@
{"system.cpu": 79.26, "system.memory": 48.27, "system.disk": 8.1, "system.proc.memory.availableMB": 3985.83, "system.proc.memory.rssMB": 148.22, "system.proc.memory.percent": 1.92, "system.proc.cpu.threads": 3.92, "system.network.sent": 163319, "system.network.recv": 297606, "_wandb": true, "_timestamp": 1580206890, "_runtime": 23}

File diff suppressed because one or more lines are too long

View file

@ -0,0 +1,23 @@
{
"root": "/home/clemens/repositorys/pytorch-ai",
"program": "pytorch_ai.py",
"git": {
"remote": "git@github.com:Clemens-Dautermann/pytorch-ai.git",
"commit": "55cff9b18f8558ae7a9170e56a3d5c6f6665d9ab"
},
"email": "clemens.dautermann@gmail.com",
"startedAt": "2020-01-28T10:21:06.610593",
"host": "ubuntu-laptop",
"username": "clemens",
"executable": "/usr/bin/python3",
"os": "Linux-5.3.0-26-generic-x86_64-with-Ubuntu-19.10-eoan",
"python": "3.7.5",
"cpu_count": 2,
"args": [],
"state": "killed",
"jobType": null,
"mode": "run",
"project": "tictactoe",
"heartbeatAt": "2020-01-28T10:21:30.645370",
"exitcode": 255
}

File diff suppressed because one or more lines are too long