[Python] Convert PyTorch to CoreML

I have this model: https://github.com/williamyang1991/DualStyleGAN and try to convert it to CoreML. So far I create copy of original Colab notebook and append at the end two blocks:

!pip install coremltools
import coremltools as ct


and

#@title Convert inverted image.
inverted_latent = torch.Tensor(result_latents[0][4]).cuda().unsqueeze(0).unsqueeze(1)

with torch.no_grad():
net.eval()

[sampled_src, sampled_dst] = net(inverted_latent, input_is_latent=True)[0]

traced_model = torch.jit.trace(net, inverted_latent)
mlmodel = ct.convert(traced_model, inputs=[ct.ImageType(name="input", shape=inverted_latent.shape,bias=[-1,-1,-1],scale=2.0/255.0)])
mlmodel.save("modelsaved.mlmodel")


To run it, you should put any image with face to /content and in /usr/local/lib/python3.7/dist-packages/torchvision/transforms/functional.py replace round method at 545, 546 lines with np.round

But then it fails at

mlmodel = ct.convert(...
​

with:

RuntimeError: PyTorch convert function for op 'pythonop' not implemented.
​

I suggest that there the way to rewrite this module with methods that could be convert, am I right? But I can't to figure out how to find the source of this module.

So my question is: If I think in a right way, how I can find the source of module? And if I wrong, please advise me the right way to do it.

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