reconstruction error

[q-learning-trader]

Hi, nice project.
Thanks for sharing.
I am looking around and testing.
It seems get_loaders function does not fit run_reconstruction.
In particular the following line:

X_train, X_test, y_train, y_test = self.preprocess_data()

it is not correct for reconstruction. For reconstruction we do not need y values.

[JulesBelveze]

Hey @q-learning-trader thanks for pointing that out.

You're actually right, this doesn't seem right to me either.

Would you like opening a PR to fix this? 😃

[q-learning-trader]

I might try if I have time @JulesBelveze .
I had a look to the model and the model seems it fits prediction but not reconstruction.
In reconstruction you should have same shape for features and labels while in prediction labels has shape one because you are trying to predict a time series.
Do you agree?

[JulesBelveze]

You are totally right @q-learning-trader
I think the model is fine, the problem is the way the data is processed and the Dataset is built.

[q-learning-trader]

I have tried to make some simple changes in the Dataset and I am now getting the following error:

RuntimeError: size mismatch, m1: [16 x 77], m2: [65 x 1] at /opt/conda/conda-bld/pytorch_1591914880026/work/aten/src/TH/generic/THTensorMath.cpp:41

For instance in the the decoder, the following forward return I do not think it fits the reconstruction:

return self.fc_out(torch.cat((h_t[0], context.to(device)), dim=1)) # predicting value at t=self.seq_length+1

dim=1 I do not think is good in this case.
What do you think?

[JulesBelveze]

@q-learning-trader I haven't looked at that code for a while so I would need to investigate further.
But you definitely pointed something that seems weird.

I would be grateful if you can look into that otherwise I will try to spend some on this :)

[MatthewWaller]

Ha! I ran into this issue too. Couldn’t make reconstruction work in the sample config setup. Also tried removing the y values and ran into the size mismatch. Hmmm

[JulesBelveze]

Hey @MatthewWaller,
Thanks for using this repo! I'm planning on addressing the opened issues at the beginning of next month. Will keep you posted 😃

[afcarzero1]

Is this still open? It looks to me that the problem is into the definition of y_hist.

I think y is defined correctly because it should be the target but y_hist looks weird to me.

                y_hist.append(torch.FloatTensor(X[i - 1: i + self.seq_length - 1, :]).unsqueeze(0))
                target.append(
                    torch.FloatTensor(X[i + self.seq_length:i + self.seq_length + self.prediction_window, :]))

I think it should be

 y_hist.append(torch.FloatTensor(X[i : i + self.seq_length, :]).unsqueeze(0))

(Maybe I am missing something)