Training takes too long in GPU may be a Blocks problem

[dpappas]

I tried running a the algorithm with the cnn dataset

specifically i run

`
python ./text_comprehension/as_reader.py
-b 32
--train ~/cnn_like_train_dataset.txt
--valid ~/cnn_like_valid_dataset.txt
--test ~/cnn_like_test_dataset.txt
--save_path ~/asreader_data/model.blocks.pkl
--output_dir ~/asreader_data/
--dataset_type cnn
--no_html
-ehd 64
-sed 64

`

Unfortunately training takes forever
the training file is ~20000000 lines long

The program also printed this :

Blocks tried to match the sources (['candidates_mask', 'question_mask', 'question', 'context_mask', 'candidates', 'context', 'answer']) of the training dataset to the names of the Theano variables (['answer', 'context_mask', 'context', 'question_mask', 'question', 'candidates']), but failed to do so. If you want to train on a subset of the sources that your dataset provides, pass the sources` keyword argument to its constructor. Or pass on_unused_sources='warn' or
on_unused_sources='ignore' to the GradientDescent algorithm.

`

I don't really know if this is a problem but "candidates_mask" is missing from the second set.