"num_workers": 8, } }) config.test_set = Config({ "type": "utterance_with_cands", "kwargs": { "train": False, }, "loader": { "batch_size": 1, "shuffle": False, } }) config.corpus_set = Config( {"loader": { "batch_size": 30, "shuffle": False, "num_workers": 8 }}) config.model = Config({ "embedding": { "vocab_size": vocab_size, "path": "./data/glove/glove.twitter.27B.{}d.txt".format(embedding_dim), "dim": embedding_dim, }, "context_encoder": { "type": "nn.GRU", "kwargs": { "input_size": embedding_dim, "hidden_size": 300, "bidirectional": True,