crslab.data.dataset.tgredial package¶

Submodules¶

TGReDial¶

References

Zhou, Kun, et al. “Towards Topic-Guided Conversational Recommender System.” in COLING 2020.

class crslab.data.dataset.tgredial.tgredial.TGReDialDataset(opt, tokenize, restore=False, save=False)[source]¶

Bases: crslab.data.dataset.base.BaseDataset

train_data¶: train dataset.

valid_data¶: valid dataset.

test_data¶: test dataset.

vocab¶

{
    'tok2ind': map from token to index,
    'ind2tok': map from index to token,
    'topic2ind': map from topic to index,
    'ind2topic': map from index to topic,
    'entity2id': map from entity to index,
    'id2entity': map from index to entity,
    'word2id': map from word to index,
    'vocab_size': len(self.tok2ind),
    'n_topic': len(self.topic2ind) + 1,
    'n_entity': max(self.entity2id.values()) + 1,
    'n_word': max(self.word2id.values()) + 1,
}

Type: dict

Notes

'unk' and 'pad_topic' must be specified in 'special_token_idx' in resources.py.

Specify tokenized resource and init base dataset.

Parameters

opt (Config or dict) – config for dataset or the whole system.
tokenize (str) – how to tokenize dataset.
restore (bool) – whether to restore saved dataset which has been processed. Defaults to False.
save (bool) – whether to save dataset after processing. Defaults to False.

crslab.data.dataset.tgredial package¶

Submodules¶

TGReDial¶

Module contents¶