I’m new in pytorch
I’ve created a simple mlp as folow:
class MLP(nn.Module):
    def __init__(self):
        super(MLP, self).__init__()
        self.L1 = nn.Linear(6,4)
        self.l1_drop = nn.Dropout(p=0.2)
        self.L2 = nn.Linear(4, 2)
        self.l3_drop = nn.Dropout(p=0.1)
        self.out = nn.Linear(2,1)


    def forward(self,x):
        x= F.relu(self.L1(x))
        x = F.relu(self.L2(x))
        x = F.sigmoid(self.out(x))
        return x


model = MLP().to("cuda:0")
crit = nn.BCELoss()
optimizer = optim.Adam(model.parameters(), lr = 0.1)

train = pd.read_csv('train.txt',low_memory=False,dtype= float,header=None)
tensorTrain = torch.tensor(train.values, dtype=torch.float32)
inputN = tensorTrain[:,2:-1]
inp = inputN.view(len(inputN),-1,6)
label = tensorTrain[:,-1]
label = label.view([len(label),1])

train_tensor = TensorDataset(inp, label)
train_loader = DataLoader(dataset = train_tensor, batch_size = 1, shuffle = True)
for epoch in range(10):
    for i, (images, labels) in enumerate(train_loader):
        images1 = Variable(images).to("cuda:0")
        print(images1)
        labels = Variable(labels).to("cuda:0")
        labels.float()
        optimizer.zero_grad()
        outputs = model(images1)
        loss = crit(outputs, labels)
        loss.backward()
        optimizer.step()
    print('Epoch [%d/%d], Loss: %.4f'% (epoch + 1, 80, loss.item()))

the input file is :
1,2,1,1,1,1,1,1,1
1,3,1,1,1,1,1,0,0
2,2,1,1,1,1,0,1,0
2,3,1.3,3.2,1,1,1,1,1

but network wont train
is there any problem?