COMP9444, CSE, UNSW
from __future__ import print_function
import torch
import torch.nn as nn
import torch.nn.functional as F
class NetLin(nn.Module):
# linear function followed by log_softmax
def __init__(self):
super(NetLin, self).__init__()
# INSERT CODE HERE
def forward(self, x):
return 0 # CHANGE CODE HERE
class NetFull(nn.Module):
# two fully connected tanh layers followed by log softmax
def __init__(self):
super(NetFull, self).__init__()
# INSERT CODE HERE
def forward(self, x):
return 0 # CHANGE CODE HERE
class NetConv(nn.Module):
# two convolutional layers and one fully connected layer,
# all using relu, followed by log_softmax
def __init__(self):
super(NetConv, self).__init__()
# INSERT CODE HERE
def forward(self, x):
return 0 # CHANGE CODE HERE