Custom training routines

[dribnet]

These series of commits adds two new experiments which act as general purpose tools as discussed in #2, which this pull request is meant to replace. It adds a more generic version of train_classifier and train_vae, which are intended to be compatible with the celeba versions but with many additional options.

• Command line options for things that were hard coded like
  • --oldmodel to start training from a previously saved state
  • --classifier to use a different classifier filename
  • --model to use a different model filename
  • --batch-size to use different batch-sizes (generally smaller for memory reasons)
  • --z-dim to change network architecture allowing different sized latent space
  • --monitor-every and --checkpoint-every to change frequency of those events
• Split out discriminative_term in the cost function so it could be monitored separately
• Ability to scale relative cost of reconstruction, kl, and discriminative
• Classifier can train on a subset of labels given at runtime
• Can train against compatible fuel datasets other than CelebA

[vdumoulin]

@dribnet I did a first review pass. Could you also flake8 the files and fix issues that might have been introduced by your changes?

[dribnet]

Thanks @vdumoulin for the constructive feedback, glad to hear you think overall this would be a welcome addition. I'll be reviewing and updating this PR over the next week.

[dribnet]

@vdumoulin - I've addressed most issues in the previous review including a general flake8 code cleanup.