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RES-863: Use 'Layer Norm' instead of 'Batch Norm' on linear networks #967
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This doesn’t affect any of our existing sparse networks right? |
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If affects |
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However we cannot use |
subutai
suggested changes
Mar 8, 2019
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| self.bn = None | ||
| if useBatchNorm: | ||
| self.bn = nn.BatchNorm1d(self.n, affine=False) | ||
| self.bn = nn.LayerNorm(self.n) |
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How would this affect GSC results?
| @@ -81,10 +81,12 @@ def __init__(self, | |||
| self.l1 = nn.Linear(inputFeatures, self.n) | |||
| self.weightSparsity = weightSparsity | |||
| self.learningIterations = 0 | |||
| if self.k <= 0: | |||
| self.k = self.n | |||
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| self.bn = None | |||
| if useBatchNorm: | |||
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Should probably change the name of the parameter too.
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@subutai Please review.
The main change in this PR is the switch from
BatchNormtoLayerNormonLinearSDRmodule.See https://arxiv.org/abs/1607.06450