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Docs: Training: Add note about GPU memory.

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Brandon Amos 2015-11-09 12:35:29 -05:00
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docs/training-new-models.md
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@ -1,8 +1,8 @@
# Training new models
This repository also contains our training infrastructure to promote an
open ecosystem and enable quicker bootstrapping for new research and development.
Warning: Training is computationally expensive and takes a few
weeks on our Tesla K40 GPU.
Warning: Training is computationally and memory expensive and takes a
few weeks on our Tesla K40 GPU.
Because of this, the training code assumes CUDA is installed.
A rough overview of training is:
@ -46,6 +46,8 @@ Run [training/main.lua](https://github.com/cmusatyalab/openface/blob/master/trai
Edit the dataset options in [training/opts.lua](https://github.com/cmusatyalab/openface/blob/master/training/opts.lua) or
pass them as command-line parameters.
This will output the loss and in-progress models to `training/work`.
The default minibatch size (parameter `-batchSize`) is 100 and requires
about 10GB of GPU memory.
Warning: Metadata about the on-disk data is cached in
`training/work/{train,test}Cache.t7` and assumes