torch.snippets (698B)
1 snippet torch "import torch" b 2 import torch 3 import torch.nn as nn 4 import torch.optim as optim 5 import torch.nn.functional as F 6 $0 7 endsnippet 8 9 10 snippet device "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" b 11 device = torch.device("cuda" if not torch.cuda.is_available() else "cpu") 12 endsnippet 13 14 15 snippet no_grad "with torch.no_grad()" b 16 with torch.no_grad(): 17 ${0:${VISUAL:pass}} 18 endsnippet 19 20 21 snippet loss "zero_grad, backward, step" b 22 loss = criterion(${3:input}, ${4:target}) 23 optimizer.zero_grad() 24 loss.backward() 25 # nn.utils.clip_grad_norm_(${1:model}.parameters(), max_norm=${2:1}) 26 # nn.utils.clip_grad_value_($1.parameters(), clip_value=$2) 27 optimizer.step() 28 $0 29 endsnippet