RNNVAE

Reference:

Bowman et al. “Generating Sentences from a Continuous Space” in CoNLL 2016.

class textbox.model.VAE.rnnvae.RNNVAE(config, dataset)

Bases: UnconditionalGenerator

LSTMVAE is the first text generation model with VAE, we modify its architecture to fit all RNN type, and rename it as RNNVAE

calculate_nll_test(corpus, epoch_idx=0)

forward(corpus, epoch_idx=0, nll_test=False)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

generate(batch_data, eval_data)

Predict the texts conditioned on a noise or sequence.

Parameters

• batch_data (Corpus) – Corpus class of a single batch.

• eval_data – Common data of all the batches.

Returns

Generated text, shape: [batch_size, max_len]

Return type

torch.Tensor

training: bool