Padding mesh data

I am trying to train the mesh segmentation code here in tensorflow graphics with my own dataset. My dataset has some meshes with varying vertex count and edge count. I tried to zero-pad the vertices and faces array for each mesh so that all the meshes in my dataset will have the same number of vertices and faces.

However, I am running into issue of

1. not able to view the mesh from the colab ipython notebook. (My vertices are between 0 and 1, so I know without padding I can view them)
2. Since the padding for faces did not allow any negative values (pytorch3d sets the padding value for faces to be -1 and I believe here I have to pad it with 0), I had to pad the faces with a 0 which obviously pointed to the first vertex in the list.

Can you someone clearly point a way to pad custom mesh datasets and feed it into the network. An example to do this is very much appreciated. Thanks in advance

NOTE: The network is training with this zero padded dataset, but not really learning anything.

Start with the mesh segmentation code and the Colab/IPython notebook mentioned in the issue, then trace how custom vertex and face arrays enter the network. Reproduce the zero-padded dataset case and compare rendering and training behavior with an unpadded mesh; done means a documented padding approach that renders correctly and allows the network to learn.