BaseEncoderMaskerDecoder instance cannot be converted to TorchScript? #646
Description
🐛 Bug
When trying to convert a pre-trained instance of BaseEncoderMaskerDecoder to TorchScript a RuntimeError is thrown, seemingly because of incompatible code inside asteroid's Conv1DBlocks class.
To Reproduce
Run this bit of code where asteroid v0.6.0 is installed:
from asteroid.models.base_models import BaseEncoderMaskerDecoder
model = BaseEncoderMaskerDecoder.from_pretrained("JorisCos/ConvTasNet_Libri3Mix_sepnoisy_16k")
model_scripted = torch.jit.script(model)
Expected behavior
model_scripted should contain the TorchScript equivalent of the model.
Actual behavior
A RuntimeError is raised from the last line of code:
Previous return statement returned a value of type Tensor but this return statement returns a value of type Tuple[Tensor, Tensor]:
File "C:\dev\github\SilentiumIsrael\ResearchML\.venv\lib\site-packages\asteroid\masknn\convolutional.py", line 97
return res_out
skip_out = self.skip_conv(shared_out)
return res_out, skip_out
~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
Examining https://github.com/asteroid-team/asteroid/blob/v0.6.0/asteroid/masknn/convolutional.py#L90 indeed shows two return statements each returning a different type.
Environment
Package versions
Asteroid 0.6.0
PyTorch 1.9.0+cpu
PyTorch-Lightning 1.7.7
Additional info
Reproduced on Windows with Python 3.9.6.