Readme

• python train_recomb.py --train --load='recomb_epoch_0.pth'
  • to continue training Recombinator
• python train_scan.py --train --load='scan_epoch_1499.pth'
  • to continue training SCAN
• python vae_disentangle.py
  • to see results of disentanglement
• python train_vae.py --train --load='vae_epoch_2900.pth'
  • to continue training VAE model of PART Ⅰ
• python train_dae.py --train --load='dae_epoch_2900.pth'
  • to continue training DAE model of SCAN
• beta-VAE/Peiyao_Sheng_beta_VAE.ipynb
  • to check the implementation about beta-VAE (on 2D-shape dataset)

Work Dairy

SCAN

• 0117

  • finish SCAN and Recombinator
  • results:

  wall_color = 0 wall_color = 0 & floor_color = 0

• 0108

  • finish beta-VAE and disentangled part

  • current results:

    z3: color and shape z4: color of floor z15: color of wall

• 0106 Implementing PART Ⅰ with Pytorch

  • denoising autoencoder(DAE)

    • continue training process by command

      python train_dae.py --train --load='dae_epoch_2900.pth'

    • current results:

      target reconstruction

  • beta-VAE
    • There is a problem about the reconstruction loss of this part, I'll figure out it soon. issue

• 0105 Review the paper of SCAN and observe that it includes three parts:

  • PART Ⅰ: beta-VAE to disentangle the primitives
  • PART Ⅱ: SCAN to abstract the concepts
  • PART Ⅲ: Recombinator to create new concepts

p.s. I didn't find the original dataset and use this mimic version to implement models

Some Ref: TensorFlow Version

beta-VAE

• 1219 read papers
  • VAE: framework & overall mathematical idea
  • beta-VAE: framework derivation & disentanglement metric
  • SCAN: disentantglement & hierarchical representation (primitive->concept->relationship)
    • every level implements a different version of VAE
• 1220 Implement Beta-VAE
• 1221 Analyze primitive experiments and write report
• 1222 Analyze the relations between given factors and latent representations z
  • train more epochs(500/1000/2000)
  • draw correlation curves between latent representations and given factors using better model
  • mathematical details of VAE
• 1223 train on more samples

More work to be done after Exam Week and Endless Coursework……

• to-do:
  • implement evaluation of disentanglement metric
  • further about SCAN

See beta-VAE/Peiyao_Sheng_beta_VAE.ipynb for more implementation details.