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First of all, I would like to thank you! Browsing around the net could not find a seq2seq model as clear as yours. Nonetheless, I believe there is a minor issue in ipython-notebooks/tf/TF tutorial.ipynb In [26] the line:
dec_inp = ([tf.zeros_like(enc_inp[0], dtype=np.int32, name="GO")]+ enc_inp[:-1])
Should be:
dec_inp = ([tf.zeros_like(labels[0], dtype=np.int32, name="GO")] + labels[:-1])
This will enable you to have different sequence lengths and vocab sizes for dec_inp and enc_inp.
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