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Using "uniform" Xavier strategy to initialize the weight for VGG network (a trial solution to issue#9866)#9867
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sxjscience merged 4 commits intoapache:masterfrom Feb 28, 2018
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Using "uniform" Xavier strategy to initialize the weight for VGG network (a trial solution to issue#9866)#9867sxjscience merged 4 commits intoapache:masterfrom juliusshufan:master
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… when loss argument is not set
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@szha May I have any comments on review from you or other domain owner, I understand normally it is the user to decide the weight initialization method. For this case, as the current implementation of the example explicitly uses a different initialization method for Alexnet to avoid convergence issue, it might be possible to follow similar way for VGG... What do you think? Thanks for your time. BR, |
rahul003
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…ork (a trial solution to issue#9866) (apache#9867) * Enable the reporting of cross-entropy or nll loss value during training * Set the default value of loss as a '' to avoid a Python runtime issue when loss argument is not set * Applying the Xavier with "uniform" type to initialize weight when network is VGG
zheng-da
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Jun 28, 2018
…ork (a trial solution to issue#9866) (apache#9867) * Enable the reporting of cross-entropy or nll loss value during training * Set the default value of loss as a '' to avoid a Python runtime issue when loss argument is not set * Applying the Xavier with "uniform" type to initialize weight when network is VGG
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Description
This PR provide a potential solution for issue #9866
For detailed information, please check the issue.
Checklist
Essentials
make lint)Changes
example/image-classification/common/fit.py
Comments
This PR has been verified on Nvidia P40 and CPU machine