From 94882fb1c94850709ec348c0a67cf507fafdde40 Mon Sep 17 00:00:00 2001 From: Reuben Morais Date: Sat, 18 Jan 2020 18:07:55 +0000 Subject: [PATCH] Mention use of CuDNN RNN in release checkpoints X-DeepSpeech: NOBUILD --- doc/TRAINING.rst | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/doc/TRAINING.rst b/doc/TRAINING.rst index c38e34ff..ca0160e1 100644 --- a/doc/TRAINING.rst +++ b/doc/TRAINING.rst @@ -207,7 +207,11 @@ For example, if you want to fine tune the entire graph using your own data in `` 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 -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 ^^^^^^^^^^^^^^^^^^^^^^^^^^