Attempted an implementation
scottleith opened this issue · comments
I really enjoyed your "Advanced dynamic seq2seq with TensorFlow" tutorial, and decided to try it out myself! I wanted to take a corpus of english quotes, and create an encoder-decoder that could reconstruct the quotes from the meaning vector (the hidden state).
I've run into an error in the softmax_entropy_with_logits:
InvalidArgumentError (see above for traceback): logits and labels must be same size: logits_size=[1000,27994] labels_size=[500,27994] ( sequences have 5 timesteps, batch size is 100, vocab size is 27994).
I've been looking over my code for hours now, but can't find the mistake. I know it's a long shot, but would you be willing to take a look to see where I've gone wrong?
The code is here, and the 'problem' might be around line 246:
https://github.com/scottleith/lstm/blob/master/Attempted%20encoder-decoder%20LSTM.py
The raw data can be downloaded here: https://github.com/alvations/Quotables/blob/master/author-quote.txt
I also apologize if this is an inappropriate place to ask - I wanted to contact you, but github doesn't make it easy!