language model used in code search

language_model.py

# create data loaders
trn_dl = LanguageModelLoader(trn_indexed, bs, bptt)
val_dl = LanguageModelLoader(val_indexed, bs, bptt)

# create lang model data
md = LanguageModelData(mpath, 1, vocab_size, trn_dl, val_dl, bs=bs, bptt=bptt)

# build learner. some hyper-params borrowed from fast.ai examples
opt_fn = partial(optim.Adam, betas=(0.8, 0.99))
drops = np.array([0.25, 0.1, 0.2, 0.02, 0.15]) * 0.7

learner = md.get_model(opt_fn, em_sz, nh, nl,
                       dropouti=drops[0],
                       dropout=drops[1],
                       wdrop=drops[2],
                       dropoute=drops[3],
                       dropouth=drops[4])

# borrowed these parameters from fastai
learner.fit(lr,
            n_cycle=n_cycle,
            wds=wd,
            cycle_len=cycle_len,
            use_clr=(32, 10),
            cycle_mult=cycle_mult,
            best_save_name='langmodel_best')