Hi Team,
I have trained an image regression model using EfficientNetB5.
I wanted to extract the weights from it’s previous layers because i want to use those weights to further train a boosting model.
Previously I used Densenet and I was able to extract it’s weights using below function and code:
class SaveFeatures():
features=None
def __init__(self, m):
self.hook = m.register_forward_hook(self.hook_fn)
self.features = None
def hook_fn(self, module, input, output):
out = output.detach().cpu().numpy()
if isinstance(self.features, type(None)):
self.features = out
else:
self.features = np.row_stack((self.features, out))
def remove(self):
self.hook.remove()
sf = SaveFeatures(learn.model[1][4]) # using 4 because i wanted to extract the fourth layer from the bottom
Now since EfficientNet models doesn’t support indexing.
Is their any way to extract the weights from the previous layers?
Any help would be really appreciated 
Regards,
Akshat