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@thirdwing can you review this? |
ziyeqinghan
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LGTM. This is mostly refactoring work. Sorry for the delay. I was caught in a bad cold while in Texas. @terrytangyuan I will merge this if you agree. |
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@thirdwing Go ahead. Looks good. @ziyeqinghan You might need to rebase. |
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The branch is rebased. |
zjf
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Jun 18, 2016
* refactor lstm model to seperate reusable rnn function like training from lstm model * add Custom RNN model in R * modify the documentation to add explanation of RNN and fix some typos * remove some unuseful comments * fix typo
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* Update warpctc-inl.h avoid compile error in cpu-only mode * [OP] Support softmax with probability label (#2456) * don't run char rnn test in R (#2459) * [OP] add slice_axis (#2458) * [OP] add slice * optimization * fix some typos (#2450) * add warpctc config to config.mk (#2451) * update lstm.py reshape using shape (#2446) changing target_shape to shape * fix worker node could not exit (#2440) * add target_shape and adj to deconv for friendly using (#2445) * add target_shape and adj to deconv for friendly using * fix typo * Add RNN model in R (#2417) * refactor lstm model to seperate reusable rnn function like training from lstm model * add Custom RNN model in R * modify the documentation to add explanation of RNN and fix some typos * remove some unuseful comments * fix typo
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I add Custom RNN model and some high-level reusable APIs is provided which is similar to the APIs for LSTM in [#2329]
mx.rnnTraining RNN Unrolled Modelmx.rnn.inference Create a RNN Inference Modelmx.rnn.forwardForward function for RNN inference model