Creating an MLP in TF, and extracting a single runs’ seed.

Lurked Reddit for a while but need some help with something I’m programming. I’m trying to create a multilayer perceptron in Tensorflow – from what I can understand an MLP is almost like a basic form of neural network that can be built upon and become other networks (adding in convolution layers turning it into a CNN). In Tensorflow/Keras I am creating a sequential object and then adding layers to it – is this how an MLP is meant to be created by those libraries or is there a more direct way?

Also, I know that whenever my model is compiled it generates random weight distributions from a seed – is there a way I can extract the seed used from a trained model so I can keep the one that produces the smallest loss value?