I’m trying to implement an autoencoder in pytorch but all my outputs are zero and i don’t know why

here is my code for the autoencoder:

```
class autoencoder(nn.Module):
def __init__(self):
super(autoencoder, self).__init__()
self.encoder = nn.Sequential(
nn.Linear(686, 256),
nn.ReLU(),
nn.Linear(256, 64),
nn.ReLU())
self.decoder = nn.Sequential(
nn.Linear(64, 256),
nn.ReLU(),
nn.Linear(256, 686),
nn.ReLU())
def forward(self, x):
x = self.encoder(x)
x = self.decoder(x)
return x
```

and here is the training process:

```
iterations = 10
learning_rate = 0.98
criterion = nn.MSELoss()
optimizer = torch.optim.Adam(
net.parameters(), lr=learning_rate, weight_decay=1e-5)
for epoch in range(iterations):
runningLoss = 0.0
for i, data in enumerate(train_dl, 0):
inputs, labels = data
if use_gpu:
inputs = Variable(inputs.view(-1,686).double()).cuda()
else:
inputs = Variable(inputs.view(-1,686).double())
outputs = net(inputs)
loss = criterion(outputs, inputs)
optimizer.zero_grad()
loss.backward()
optimizer.step()
runningLoss += loss.data.item()
print(f'at iteration: {epoch+1}/{iterations}; BC Error: {runningLoss}')
print('Finished Training')
```