VAE

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VAE(
   datamodule, encoder, decoder, optimizer, scheduler = None
)

---

Variational autoencoder model that learns to generate sequences with a stability similar to wt

Args

• datamodule : pytorch lightning datamodule with sequences and labels
• encoder : encoder model
• measurement : measurement model (options: Linear, General Epistasis Model)
• optimizer : optimizer
• loss_function : loss function model( options: )
• scheduler : scheduler

Attributes

• dataset : pytorch lightning datamodule
• encoder : encoder model
• measurement : measurement model
• optimizer : optimizer
• loss_function : loss function
• scheduler : scheduler
• optimizer_params : optimizer parameters
• scheduler_params : scheduler parameters

Methods:

.factory

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.factory(
   cls, datamodule, **kwargs
)

.forward

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.forward(
   batch
)

.configure_optimizers

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.configure_optimizers()

---

Configure the optimizer.

.training_step

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.training_step(
   batch, batch_idx
)

.validation_step

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.validation_step(
   batch, batch_idx
)

.on_training_epoch_end

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.on_training_epoch_end(
   outputs: Any
)