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I think it should work in general. But you might need to adjust the way you access and slice the dimensions, because the output of a bidirectional LSTM will have a different dimension than the output of a unidirectional LSTM, I suppose. See the PyTorch documentation for details. But I never tried it...
Also, using a bidirectional LSTM might lead to even more overfitting.
Is it possible to implement a bidirectional LSTM just by changing parameter 'bidirectional = True' in the code?
Please let me know if this works.
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