optimizer.add_param_group 194 would be what you want. This will unfreeze the previously frozen layer, by adding the parameters to new dict elements of param_groups (list) of the optimizer:
# let's unfreeze the fc2 layer this time for extra tuning
net.fc2.weight.requires_grad = True
net.fc2.bias.requires_grad = True

# add the unfrozen fc2 weight to the current optimizer
optimizer.add_param_group({'params': net.fc2.parameters()})