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Mention use of CuDNN RNN in release checkpoints

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X-DeepSpeech: NOBUILD
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Reuben Morais 2020-01-18 18:07:55 +00:00 committed by GitHub
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doc/TRAINING.rst
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@ -207,7 +207,11 @@ For example, if you want to fine tune the entire graph using your own data in ``
mkdir fine_tuning_checkpoints mkdir fine_tuning_checkpoints
python3 DeepSpeech.py --n_hidden 2048 --checkpoint_dir path/to/checkpoint/folder --epochs 3 --train_files my-train.csv --dev_files my-dev.csv --test_files my_dev.csv --learning_rate 0.0001 python3 DeepSpeech.py --n_hidden 2048 --checkpoint_dir path/to/checkpoint/folder --epochs 3 --train_files my-train.csv --dev_files my-dev.csv --test_files my_dev.csv --learning_rate 0.0001
Note: the released models were trained with ``--n_hidden 2048``\ , so you need to use that same value when initializing from the release models. Note: the released models were trained with ``--n_hidden 2048``\ , so you need to use that same value when initializing from the release models. Since v0.6.0, the release models are also trained with ``--use_cudnn_rnn``\ , so you'll need to specify that as well. If you don't have a CUDA compatible GPU, then you can workaround it by using the ``--cudnn_checkpoint`` flag. Use ``--helpfull`` to get more information on how the flags work. If you try to load a release model without following these steps, you'll get an error similar to this:
.. code-block::
Key cudnn_lstm/rnn/multi_rnn_cell/cell_0/cudnn_compatible_lstm_cell/bias/Adam not found in checkpoint
Training with augmentation Training with augmentation
^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^