def make_fc(num_layers, num_features, num_targets=1, activation_fn=nn.ReLU, intermediate_size=50, regularizers=True):
    net_layers = [nn.Linear(num_features, intermediate_size), activation_fn()]
    for hidden in range((num_layers - 2)):
        net_layers.append(nn.Linear(intermediate_size, intermediate_size))
        net_layers.append(activation_fn())
    net_layers.append(nn.Linear(intermediate_size, num_targets))
    net_layers.append(nn.ReLU())
    return nn.Sequential(*net_layers)
def make_fc(num_layers, num_features, num_targets=1, activation_fn=nn.ReLU, intermediate_size=50, regularizers=True):
    net_layers = [nn.Linear(num_features, intermediate_size), activation_fn()]
    for hidden in range((num_layers - 2)):
        net_layers.append(nn.Linear(intermediate_size, intermediate_size))
        net_layers.append(activation_fn())
    net_layers.append(nn.Linear(intermediate_size, num_targets))
    net_layers.append(nn.ReLU())
    return nn.Sequential(*net_layers)