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Reduce min of scale in Conv2dSubsampling from 0.01 to 0.2
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@ -1720,7 +1720,7 @@ class Conv2dSubsampling(nn.Module):
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self.scale = nn.Parameter(torch.ones(out_height * layer3_channels))
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self.scale_max = 1.0
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self.scale_min = ScheduledFloat((0.0, 0.9), (4000.0, 0.01))
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self.scale_min = ScheduledFloat((0.0, 0.9), (4000.0, 0.2))
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self.out = LinearWithAuxLoss(out_height * layer3_channels, out_channels,
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aux_grad_scale=_aux_grad_scale(), prob=_aux_grad_prob_out())
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