On deterministic weighted graph isomorphism from randomized
Consider first the case of two colors. We can identify with each vertex $x$ its color distribution $a$, which is the number of edges of color 1. The distribution of $a$ is $\mathrm{Bin}(n,1/2)$, and so if we divide the vertices into bins according to their color distribution, the heaviest bin will contain $O(\sqrt{n})$ vertices with high probability. If we repeat the process, we the heaviest will contain $O(\log n)$ vertices with high probability. Once more, and we expect all bins to have size 1.

What this sketch suggests is that even if you have a constant number of colors (in this case, 8) then with high probability, every vertex will have a unique color distribution (histogram of colors of the edges adjacent to it). This makes graph isomorphism very easy for such graphs. 

Of course, this sketch isn't rigorous. To know for sure, you will have to make it rigorous, and find whether it indeed works; perhaps a constant number of rounds isn't enough, but $\alpha\log n$ rounds (as in your case) are.