wangwei created SINGA-329:
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Summary: Support layer freezing during training (fine-tuning)
Key: SINGA-329
URL: https://issues.apache.org/jira/browse/SINGA-329
Project: Singa
Issue Type: New Feature
Reporter: wangwei
Assignee: wangwei
During fine-tuning (e.g. fine tune the CNN trained over ImageNet on our own
dataset), we may want to fix some layers (e.g. bottom layers0 and train other
layers (e.g top layers).
This ticket adds an argument (i.e a layer name( for the forward and backward
function of FeedForwardNet. The training will freeze the layers before that
layer and compute the gradients of parameters after that layer (inclusive).
If you want to freeze the top layers, you don't need to use this argument.
Instead, you just ignore the gradients of parameters of the top layers from the
backward function.
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