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Thanks for the code and the paper. Awesome work :)
While initialising the individualTF model why does the decoder_input/decoder_output have size 3 whereas the the encoder_input size is 2. Hence the ouput of the decoder is of the shape [N,Steps,3]. What is the third value we are trying to predict per step ? I was assuming we are trying to predict only the relative displacements in the cartesian coordinates ?
Also what does the extra term in the loss signify ? torch.mean(torch.abs(pred[:,:,2])
Would be great if you could clarify this doubt.
Thanks
The text was updated successfully, but these errors were encountered:
Thanks for the code and the paper. Awesome work :)
While initialising the individualTF model why does the decoder_input/decoder_output have size 3 whereas the the encoder_input size is 2. Hence the ouput of the decoder is of the shape [N,Steps,3]. What is the third value we are trying to predict per step ? I was assuming we are trying to predict only the relative displacements in the cartesian coordinates ?
Also what does the extra term in the loss signify ? torch.mean(torch.abs(pred[:,:,2])
Hi
Thanks for the code and the paper. Awesome work :)
While initialising the individualTF model why does the decoder_input/decoder_output have size 3 whereas the the encoder_input size is 2. Hence the ouput of the decoder is of the shape [N,Steps,3]. What is the third value we are trying to predict per step ? I was assuming we are trying to predict only the relative displacements in the cartesian coordinates ?
Also what does the extra term in the loss signify ?
torch.mean(torch.abs(pred[:,:,2])
Would be great if you could clarify this doubt.
Thanks
The text was updated successfully, but these errors were encountered: