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jerrybai1995 avatar jerrybai1995 commented on August 15, 2024

Hi,

The input is represented as a Tx2 tensor; in the output layer (which has length T), we only take the last time step to produce a scalar.

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HilmiiKumdakci avatar HilmiiKumdakci commented on August 15, 2024

Thanks for your explanation.

What I do not understand is, number of classes is 1, does not that mean output length is equal to 1 ? If not so, where do you take last time step to produce scalar value of adding problem?

I would expect something like seq_length sized array with full of zeros and sum value appended into that as a ground truth. By matching size with that I would add one zero to the end of input as well.

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jerrybai1995 avatar jerrybai1995 commented on August 15, 2024

The number of classes is one means the width (the # of channels is 1), and the length is 1. But a TCN outputs a tensor with the same length as the input. There we only take the last time step of this full-length output, using x[:,:,-1].

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