92d566ab31e5e341d79209d96aef2c2e5d54fd0e,snli/train.py,,,#,15

Before Change

train, val, test = datasets.SNLI.splits(inputs, answers)

inputs.build_vocab(train)
answers.build_vocab(train)

train_iter, val_iter, test_iter = data.BucketIterator.splits(
            (train, val, test), batch_size=args.batch_size, device=args.gpu)

After Change

train, val, test = datasets.SNLI.splits(inputs, answers)

inputs.build_vocab(train, vectors=(args.data_cache, args.word_vectors, args.d_embed))
answers.build_vocab(train)

train_iter, val_iter, test_iter = data.BucketIterator.splits(
            (train, val, test), batch_size=args.batch_size, device=args.gpu)

config = args
config.n_embed = len(inputs.vocab)
config.d_out = len(answers.vocab)
config.n_cells = config.n_layers
if config.bidirectional:
    config.n_cells *= 2

model = SNLIClassifier(config)
if args.wv_path:
    model.embed.weight = inputs.vocab.vectors
model.cuda()
criterion = nn.CrossEntropyLoss()
opt = O.Adam(model.parameters(), lr=args.lr)

Instances