Great, it worked. Thank you kindly!
For anyone else reading this, I modified my network:
class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(28 * 28, hyperparams['l1_out'])
        self.dropout1 = nn.Dropout(hyperparams['l1_drop'])
        self.fc2 = nn.Linear(hyperparams['l1_out'], hyperparams['l2_out'])
        self.dropout2 = nn.Dropout(hyperparams['l2_drop'])
        self.fc3 = nn.Linear(hyperparams['l2_out'], 10)

    def forward(self, x):
        x = self.dropout1(F.relu(self.fc1(x)))
        x = self.dropout2(F.relu(self.fc2(x)))
        x = self.fc3(x)
        return F.log_softmax(x) #exponentiate logits to retrieve predicted probabilities