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created weight_norm option for deep cnn representation #809
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Summary: Pull Request resolved: facebookresearch#809 Weight norm decouples a weight matrix into its magnitude and direction and optimizes them separately -- this is very helpful in speeding up convergence and getting better performance overall. This diff adds an option to use weight norm as a normalization strategy on conv1d layers. Differential Revision: D16403533 fbshipit-source-id: b2b737b3dbfa43ed4f2893295df3afdfe6b59df0
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Summary: Pull Request resolved: facebookresearch#809 Weight norm decouples a weight matrix into its magnitude and direction and optimizes them separately -- this is very helpful in speeding up convergence and getting better performance overall. This diff adds an option to use weight norm as a normalization strategy on conv1d layers. Differential Revision: D16403533 fbshipit-source-id: 4c6d7546408b4d18c80b2348bcf8299943292ee2
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Summary: Pull Request resolved: facebookresearch#809 Weight norm decouples a weight matrix into its magnitude and direction and optimizes them separately -- this is very helpful in speeding up convergence and getting better performance overall. This diff adds an option to use weight norm as a normalization strategy on conv1d layers. Differential Revision: D16403533 fbshipit-source-id: 52ae2d815d6c2f7f41eb320dec8fdc451c1e2f0f
Summary: Pull Request resolved: facebookresearch#809 Weight norm decouples a weight matrix into its magnitude and direction and optimizes them separately -- this is very helpful in speeding up convergence and getting better performance overall. This diff adds an option to use weight norm as a normalization strategy on conv1d layers. Reviewed By: geof90 Differential Revision: D16403533 fbshipit-source-id: 4ef3141c59d3c02b95cde33da1dba0b1ebc5ba28
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This pull request has been merged in 50ef702. |
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Differential Revision: D16403533