feat: integrate ray tune to hyperopt

[kaushikb11]

Description

The motivation for this Pull Request is to integrate Ray Tune with Ludwig's Hyperopt design. This will support the samplers provided by Ray Tune by using the RayTuneExecutor.

Resource Allocation, support for Search Algorithms & Trial Schedulers, tests & docs.

Example Config for RayTuneExecutor

hyperopt:
  sampler:
    type: ray
    search_alg:
      type: bayesopt
	num_samples: 2
  executor:
    type: ray
    cpu_resources_per_trial: 2
	gpu_resources_per_trial: 1
  parameters:
    training.learning_rate:
      space: uniform
      lower: 0.001
      upper: 0.1
    combiner.num_fc_layers:
      space: qrandint
      lower: 2
      upper: 6
      q: 2
    utterance.cell_type:
      space: grid_search
      values: [rnn, gru, lstm]
  goal: minimize

[tgaddair]

Sweet!

cc @richardliaw

[richardliaw]

this is awesome! I'll take a look later.