sjmikler / pytorch-symbolic Goto Github PK
View Code? Open in Web Editor NEWProvides symbolic API for model creation in PyTorch.
License: MIT License
Provides symbolic API for model creation in PyTorch.
License: MIT License
First of all, thank you for writing this library! It has been quite useful to me so far.
It would be useful if you could manually name the layers of a SymbolicModel
, perhaps via the interception of a specific keyword argument in the module call wrapper. For example (mockup):
>>> import torch.nn as nn
>>> from pytorch_symbolic import Input, SymbolicModel
>>>
>>> x = Input((1,1))
>>> y = nn.Conv2d(1,1,1)(x, name="MyCustomName")
>>> model = SymbolicModel(x, y)
>>>
>>> model.summary()
>>> print(model.state_dict().keys())
_________________________________________________
Layer Output shape Params Parent
=================================================
1 Input_1 (None, 1, 1) 0
2* MyCustomName (None, 1, 1) 2 1
=================================================
Total params: 2
Trainable params: 2
Non-trainable params: 0
_________________________________________________
odict_keys(['MyCustomName.weight', 'MyCustomName.bias'])
This would particularly help to improve clarity when using nested SymbolicModels.
I find there is no reshape layer in layers.py. please add this frequently used layer. thx
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