"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,
