Fastai reset34 model has numbers and not names in state_dict

Edit: Ok, I THINK this is due to that ConvLearner.pretrained
is not actually using resnet34 straight, it seems to add some more layers to it so it will become a different network.

So either I have to figure out how to save the model architecture so I can load it in pytorch (I failed so far),
or
I have to figure out how to recreate the same kind of network in pytorch.

Anyone gone through this before?


If I look at the resnet34 model in fastai:
learn = ConvLearner.pretrained(resnet34, data, precompute=True) learn.model.state_dict()

it contains entries like this

OrderedDict([('0.weight', 
               0.0111
               0.2668
               0.8734
                 ⋮   
               0.6134
               0.2887
               0.3314
              [torch.cuda.FloatTensor of size 1024 (GPU 0)]), ('0.bias', 
               0
               0
...

if I compare that to a resnet34 model created directly in pytorch
resnet34(True).state_dict()

it contains entries like this
OrderedDict([('conv1.weight', (0 ,0 ,.,.) = 5.4109e-03 -6.9092e-03 7.8839e-03 ... 4.9072e-02 3.0660e-02 2.5398e-02 4.1081e-02 3.1296e-02 3.2265e-02 ... 3.3145e-02 2.9754e-02 4.1735e-02 4.9519e-

This causes me problem when I want to train a model in fastai and use it in pytorch.
Anyone got an idea why the fastai state_dict has just prefix numbers like 0.weight and not conv1.weight ?