Add Semi-Random Weighting to AutoScaler Node Scheduler

[fogerd]

Why are these changes needed?

When trying to utilize spot instance types, we noticed the Autoscaler would get stuck attempting to scale up a node type with no availability and never recover / move on to try other node types. This change introduces some randomness, with weighting, so that the Autoscaler will try different node types on each loop and prevent the described scenario.

Related issue number

Checks

• I've signed off every commit(by using the -s flag, i.e., git commit -s) in this PR.
• I've run scripts/format.sh to lint the changes in this PR.
• I've included any doc changes needed for https://docs.ray.io/en/master/.
  • I've added any new APIs to the API Reference. For example, if I added a
    method in Tune, I've added it in doc/source/tune/api/ under the
    corresponding .rst file.
• I've made sure the tests are passing. Note that there might be a few flaky tests, see the recent failures at https://flakey-tests.ray.io/
• Testing Strategy
  • Unit tests
  • Release tests
  • This PR is not tested :(