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Add deriv-balancer at output of embedding.
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@ -57,6 +57,8 @@ class Conv2dSubsampling(nn.Module):
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)
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self.out = ScaledLinear(odim * (((idim - 1) // 2 - 1) // 2), odim)
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self.out_norm = BasicNorm(odim)
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# constrain mean of output to be close to zero.
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self.out_balancer = DerivBalancer(channel_dim=-1, min_positive=0.4, max_positive=0.6)
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self._reset_parameters()
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def _reset_parameters(self):
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@ -84,6 +86,7 @@ class Conv2dSubsampling(nn.Module):
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x = self.out(x.transpose(1, 2).contiguous().view(b, t, c * f))
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# Now x is of shape (N, ((T-1)//2 - 1))//2, odim)
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x = self.out_norm(x)
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x = self.out_balancer(x)
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return x
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@ -110,7 +110,7 @@ def get_parser():
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parser.add_argument(
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"--exp-dir",
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type=str,
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default="transducer_stateless/randcombine1_expscale3_rework2c_maxabs1000_maxp0.95_noexp_convderiv3warmup",
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default="transducer_stateless/randcombine1_expscale3_rework2c_maxabs1000_maxp0.95_noexp_convderiv3warmup_embed",
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help="""The experiment dir.
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It specifies the directory where all training related
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files, e.g., checkpoints, log, etc, are saved
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