[FIXED] How do I write a PyTorch sequential model?

Issue

How do I write a sequential model in PyTorch, just like what we can do with Keras? I tried:

import torch
import torch.nn as nn

net = nn.Sequential()
net.add(nn.Linear(3, 4))
net.add(nn.Sigmoid())
net.add(nn.Linear(4, 1))
net.add(nn.Sigmoid())
net.float()

But I get the error:

AttributeError: 'Sequential' object has no attribute 'add'

Solution

As described by the correct answer, this is what it would look as a sequence of arguments:

device = torch.device('cpu')
if torch.cuda.is_available():
    device = torch.device('cuda')
 
net = nn.Sequential(
      nn.Linear(3, 4),
      nn.Sigmoid(),
      nn.Linear(4, 1),
      nn.Sigmoid()
      ).to(device)

print(net)

Sequential(
  (0): Linear(in_features=3, out_features=4, bias=True)
  (1): Sigmoid()
  (2): Linear(in_features=4, out_features=1, bias=True)
  (3): Sigmoid()
  )

Answered By - Chris Palmer