def reconstruction_eval()

in embed.py [0:0]

• 17 lines of code
• 2 McCabe index (conditional complexity)

def reconstruction_eval(adj, opt, epoch, elapsed, loss, pth, best):
    chkpnt = th.load(pth, map_location='cpu')
    model = build_model(opt, chkpnt['embeddings'].size(0))
    model.load_state_dict(chkpnt['model'])

    meanrank, maprank = eval_reconstruction(adj, model)
    sqnorms = model.manifold.norm(model.lt)
    return {
        'epoch': epoch,
        'elapsed': elapsed,
        'loss': loss,
        'sqnorm_min': sqnorms.min().item(),
        'sqnorm_avg': sqnorms.mean().item(),
        'sqnorm_max': sqnorms.max().item(),
        'mean_rank': meanrank,
        'map_rank': maprank,
        'best': bool(best is None or loss < best['loss']),
    }