def run_word_language_model(self, model_name):
ntokens = 50
emsize = 5
nhid = 5
nlayers = 5
dropout = 0.2
tied = False
batchsize = 5
model = word_language_model.RNNModel(model_name, ntokens, emsize, nhid,
nlayers, dropout, tied, batchsize)
x = torch.arange(0, ntokens).long().view(-1, batchsize)
# Only support CPU version, since tracer is not working in GPU RNN.
self.run_test(model, (x, model.hidden))
def run_word_language_model(self, model_name):
ntokens = 50
emsize = 5
nhid = 5
nlayers = 5
dropout = 0.2
tied = False
batchsize = 5
model = word_language_model.RNNModel(model_name, ntokens, emsize,
nhid, nlayers, dropout, tied,
batchsize)
x = Variable(torch.arange(0, ntokens).long().view(-1, batchsize),
requires_grad=False)
# Only support CPU version, since tracer is not working in GPU RNN.
self.run_model_test(model, train=False, input=(x, model.hidden),
batch_size=batchsize, use_gpu=False)
