torch-rnn provides high-performance, reusable RNN and LSTM modules for torch7, and uses these modules for character-level language modeling similar to char-rnn.
You can find documentation for the RNN and LSTM modules here; they have no dependencies other than
nn, so they should be easy to integrate into existing projects.
Compared to char-rnn, torch-rnn is up to 1.9x faster and uses up to 7x less memory. For more details see the Benchmark.
- Human GRCh38 reference genome (Adam)
- E. Coli reference genome (Eli)
-max_epochs 8 -rnn_size 128 -dropout 0.05 -num_layers 3
Blastn Alignment Results
See blast at: https://blast.ncbi.nlm.nih.gov/Blast.cgi
Sampling from the longest checkpoints