How to get back the model from flattened network?

Hi, I am using following function to flatten the network:

#############################################################################
# Flattening the NET
#############################################################################
def flattenNetwork(net):
    flatNet = []
    shapes = []
    for param in net.parameters():
        #if its WEIGHTS
        curr_shape = param.cpu().data.numpy().shape
        shapes.append(curr_shape)
        if len(curr_shape) == 2:
            param = param.cpu().data.numpy().reshape(curr_shape[0]*curr_shape[1])
            flatNet.append(param)
        elif len(curr_shape) == 4:
            param = param.cpu().data.numpy().reshape(curr_shape[0]*curr_shape[1]*curr_shape[2]*curr_shape[3])
            flatNet.append(param)
        else:
            param = param.cpu().data.numpy().reshape(curr_shape[0])
            flatNet.append(param)
    finalNet = []
    for obj in flatNet:
        for x in obj:
            finalNet.append(x)
    finalNet = np.array(finalNet)
    return finalNet,shapes

I manipulate the weights given by finalNet and I don’t change the shape of the network. How can I get back the original network with manipulated weights? Later I want to see the effect of weight manipulations on the accuracy. Please help. Thank you.

@MariosOreo Sir, can you please help me with my question? Thanks.