OCDocker.OCScore.Dimensionality.future package

Submodules

• OCDocker.OCScore.Dimensionality.future.AETrainer module
  • EarlyStopping
    • EarlyStopping.__init__()
    • EarlyStopping.step()
  • AETrainer
    • AETrainer.__init__()
    • AETrainer.evaluate()
    • AETrainer.fit()
• OCDocker.OCScore.Dimensionality.future.Autoencoder module
  • ForwardOutput
    • ForwardOutput.reconstruction
    • ForwardOutput.latent
    • ForwardOutput.mu
    • ForwardOutput.logvar
    • ForwardOutput.energy
  • MLP
    • MLP.__init__()
    • MLP.forward()
  • EncoderModule
    • EncoderModule.__init__()
    • EncoderModule.forward()
    • EncoderModule.reparameterize()
  • Autoencoder
    • Autoencoder.__init__()
    • Autoencoder.encode()
    • Autoencoder.forward()
    • Autoencoder.get_decoder()
    • Autoencoder.get_decoder_topology()
    • Autoencoder.get_encoder()
    • Autoencoder.get_encoder_topology()
    • Autoencoder.load_encoder()
    • Autoencoder.reconstruct()
    • Autoencoder.sanity_check()
    • Autoencoder.save_encoder()
• OCDocker.OCScore.Dimensionality.future.AutoencoderOptimizer module
  • AutoencoderOptimizer
    • AutoencoderOptimizer.__init__()
    • AutoencoderOptimizer.objective()
    • AutoencoderOptimizer.optimize()
    • AutoencoderOptimizer.set_random_seed()
• OCDocker.OCScore.Dimensionality.future.datasets module
  • AutoencoderDataset
    • AutoencoderDataset.__getitem__()
    • AutoencoderDataset.__init__()
    • AutoencoderDataset.__len__()
• OCDocker.OCScore.Dimensionality.future.losses module
  • contractive_penalty()
  • energy_loss()
  • kl_divergence()
  • reconstruction_loss()
• OCDocker.OCScore.Dimensionality.future.utils module
  • apply_noise()
  • embedding_stats()
  • ramp_weight()
  • spearman_corr()

Module contents

Future autoencoder pipeline modules (denoising, multi-task).

Usage:

import OCDocker.OCScore.Dimensionality.future as ocdim_future

Modules

• AETrainer: Experimental autoencoder trainer.

• Autoencoder: Experimental autoencoder model.

• AutoencoderOptimizer: Experimental autoencoder optimizer.

• datasets: Experimental dataset helpers.

• losses: Experimental loss functions.

• utils: Experimental utility helpers.