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From 460->461, revert change about balancing output of attention_squeeze module.
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@ -1343,17 +1343,10 @@ class AttentionSqueeze(nn.Module):
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self.out_proj = ScaledLinear(embed_dim, embed_dim,
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bias=False, initial_scale=0.05)
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self.out_whiten = Whiten(num_groups=1,
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whitening_limit=10.0,
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prob=(0.01, 0.1),
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grad_scale=0.01)
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self.out_balancer = ActivationBalancer(
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embed_dim, channel_dim=-1,
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min_positive=0.45, max_positive=0.55,
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min_abs=0.005, max_abs=2.0,
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min_prob=0.05,
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)
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def forward(self,
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x: Tensor,
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@ -1388,7 +1381,6 @@ attn_weights: a Tensor of shape (num_heads, batch_size, seq_len, seq_len)
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x = self.activation(x) # Identity only. For diagnostics.
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x = self.out_proj(x)
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x = self.out_whiten(x)
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x = self.out_balancer(x)
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return x
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