My data and responses have the same sequence length although the error says otherwise.
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My data is a 360x1 cell filled with 3x769 arrays
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/761586/image.png)
and my response data is a cell array of categorical sequences that are 1x769
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/761591/image.png)
I am able to make this data go through the sample sequence-sequence network that Matlab has in the deep network designer
Although using my network it provides this error
Error using trainNetwork (line 184)
Invalid training data. Sequence responses must have the same sequence length as the corresponding predictors.
5 Commenti
Sahil Jain
il 21 Ott 2021
From my understanding, the issue is that for every 3x769 input, your network should output a 5x769 array. However, your network's output is a vector of length 5. This is because you are passing the entire 3x769 sequence as one image. The reason your data works with the sample sequence-to-sequence LSTM is because in that network, you are passing only a vector of length 3 to the network for every time step and therefore, it is able to generate an output vector of length 5 for all 769 time steps. Have a look at the difference between the parameters of the "sequenceInputLayer" in the sample network and your network.
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