I’m trying to save the encoder for the following language model after training which has been defined here in the book:
class Dropout(Module):
def __init__(self, p): self.p = p
def forward(self, x):
if not self.training: return x
mask = x.new(*x.shape).bernoulli_(1-p)
return x * mask.div_(1-p)
class LMModel7(Module):
def __init__(self, vocab_sz, n_hidden, n_layers, p=0):
self.i_h = nn.Embedding(vocab_sz, n_hidden)
self.rnn = nn.LSTM(n_hidden, n_hidden, n_layers, batch_first=True)
self.drop = nn.Dropout(p)
self.h_o = nn.Linear(n_hidden, vocab_sz)
self.h_o.weight = self.i_h.weight
self.h = [torch.zeros(n_layers, bs, n_hidden) for _ in range(2)]
def forward(self, x):
raw,h = self.rnn(self.i_h(x), self.h)
out = self.drop(raw)
self.h = [h_.detach() for h_ in h]
return self.h_o(out),raw,out
def reset(self):
for h in self.h: h.zero_()
learn = TextLearner(dls, LMModel7(len(vocab), 64, 2),
loss_func=CrossEntropyLossFlat(), metrics=accuracy)
learn.fit_one_cycle(1, 1e-2, wd=0.1)
learn.save_encoder('lang_model_enc')
But I’m getting the following error:
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-48-bb00513b4b05> in <module> ----> 1 learn.save_encoder('lang_model_enc') /opt/conda/lib/python3.7/site-packages/fastai/text/learner.py in save_encoder(self, file) 93 "Save the encoder to `file` in the model directory" 94 if rank_distrib(): return # don't save if child proc ---> 95 encoder = get_model(self.model)[0] 96 if hasattr(encoder, 'module'): encoder = encoder.module 97 torch.save(encoder.state_dict(), join_path_file(file, self.path/self.model_dir, ext='.pth')) TypeError: 'LMModel7' object is not subscriptable
Doing type(LMModel7) gives fastcore.meta.PrePostInitMeta.
Could someone please help me out?
How do I get rid of this and save the encoder so that I can load and use it later in some other file?