RNNEncDec

Reference:

Sutskever et al. “Sequence to Sequence Learning with Neural Networks” in NIPS 2014.

class textbox.model.Seq2Seq.rnnencdec.RNNEncDec(config, dataset)

Bases: Seq2SeqGenerator

RNN-based Encoder-Decoder architecture is a basic framework for Seq2Seq text generation.

forward(corpus, epoch_idx=0)

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