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writing style transfer using cycle gan
Hi, thanks a lot for your contribution
I was trying to load the saved models
d_a = torch.load(path)
but then the way it is loaded is different when compared to the model you created in the google collab network
Can you please let me know if there is any other way to load the saved models?
Thank you!
Hey,
I have a custom dataset wherein I have some text data in the X domain and some in the Y domain in the form of text files. I want to train this model on my custom dataset. Can you please tell me what changes need to be done to incorporate this?
Hello, thanks for your amazing work! Currently I am trying to extend your work and add some experiment on it. How I can cite your work?
Thanks!
Hello! First of all, thank you for the contribution!
I was trying to see what the model comes up to, so I went for the Google Colab linked.
However, there may be a torch
version problem (just my hypothesis), as I am getting a **dimension mismatch error while initializing the generators and discriminators (the cells to "Prepare the networks"). See log below.
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-15-a6589232276f> in <module>()
----> 1 g_ab, g_ba, d_a, d_b = get_cycle_gan_network(G_INPUT_DIM, G_OUTPUT_DIM, device, PAD_IDX, SOS_IDX, True, True)
2 frames
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in load_state_dict(self, state_dict, strict)
845 if len(error_msgs) > 0:
846 raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
--> 847 self.__class__.__name__, "\n\t".join(error_msgs)))
848 return _IncompatibleKeys(missing_keys, unexpected_keys)
849
RuntimeError: Error(s) in loading state_dict for Seq2Seq:
size mismatch for encoder.embedding.weight: copying a param with shape torch.Size([9887, 256]) from checkpoint, the shape in current model is torch.Size([9889, 256]).
size mismatch for decoder.embedding.weight: copying a param with shape torch.Size([9887, 256]) from checkpoint, the shape in current model is torch.Size([9889, 256]).
size mismatch for decoder.out.weight: copying a param with shape torch.Size([9887, 512]) from checkpoint, the shape in current model is torch.Size([9889, 512]).
size mismatch for decoder.out.bias: copying a param with shape torch.Size([9887]) from checkpoint, the shape in current model is torch.Size([9889]).
The Colab notebook should be updated in order for it to be useful. Do you have any idea what may be happening here? @eliorav
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