RNN=None causes error at line 171 in snli_rnn.py (Theano) about keras_snli HOT 4 CLOSED

Odd. I use the TensorFlow backend for Keras and whilst it shouldn't matter I was able to reproduce your exception using the Theano backend. Given that the actual RNNs (GRU / LSTM) work, this suggests the issues lies with:
SumEmbeddings = keras.layers.core.Lambda(lambda x: K.sum(x, axis=1))

Turns out that Theano requires output_shape be provided by the Lambda layer whilst TensorFlow can infer it.

I'd also note to try both backends. I may have a buggy setup but the Theano backend is far slower for the summation of word embeddings, which is strange given the relative simplicity.

Thanks for noting the bug! Hugely important if I want to merge this in as a Keras example! :)

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Confirmed working now on my setup. Will try both backends as you suggest. Thanks so much for the quick turnaround; this example is very useful (to me at least) from a pedagogical point of view and would be great merged into Keras.

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Just to follow up, FWIW I ran both Sum and GRU on my setup (AWS EC2 g2.2xlarge, Bitfusion Ubuntu 14 Theano AMI, Theano 0.8.2, TensorFlow 0.10.0rc0, Keras 1.0.8) using both backends. Results were:

... which is consistent with your observation, with the caveat that, due to an incompatibility between Keras 1.0.8 and the package structure of TensorFlow 0.7.1, I had to use the bleeding edge TensorFlow build (0.10.0rc0) in comparison with the current but older Theano 0.8.2 release.

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Thanks for the follow up - and glad it's working for you now! ^_^

I'd be curious where the slowdown comes from. For sum(word vectors) I could easily imagine that they way Keras's Lambda is implemented between backends is the difference.

Also, +1 for the 83.1 test accuracy! I got some higher numbers like that for sum(word vectors) on a few runs but decided to report 82.4 as that was the consistent average over runs.

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