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# torch-rnn | ||
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](https://github.com/karpathy/char-rnn). | ||
language modeling similar to [char-rnn](https://github.com/karpathy/char-rnn). You can find documentation for the modules | ||
[here](modules.md). | ||
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Compared to char-rnn, torch-rnn is up to **1.9x faster** and uses up to **7x less memory**. | ||
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](#Benchmarks) section below. | ||
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# TODOs | ||
- CPU support | ||
- OpenCL support | ||
- Documentation | ||
- Dependencies / installation | ||
- VanillaRNN | ||
- LSTM | ||
- LanguageModel | ||
- preprocess.py | ||
- train.lua | ||
- sample.lua | ||
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# Setup | ||
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# Usage | ||
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# Benchmarks | ||
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<img src='imgs/lstm_time_benchmark.png' width="400px"> | ||
<img src='imgs/lstm_memory_benchmark.png' width="400px"> |
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# VanillaRNN | ||
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# LSTM | ||
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# LanguageModel |