diff --git a/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py b/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
index bcdf859a8..76493678e 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless7/zipformer.py
@@ -1442,6 +1442,7 @@ class NonlinAttentionModule(nn.Module):
             min_abs=0.2, max_abs=10.0,
             min_prob=0.05,
         )
+        self.pre_sigmoid = Identity()  # for diagnostics.
         self.sigmoid = nn.Sigmoid()
 
         self.activation = Identity()  # for diagnostics.
@@ -1484,6 +1485,7 @@ attn_weights: a Tensor of shape (num_heads, batch_size, seq_len, seq_len)
 
         v = self.whiten1(v)
         # GLU mechanism
+        s = self.pre_sigmoid(s)
         x = self.sigmoid(s) * v
         x = self.balancer(x)
 
@@ -1546,6 +1548,9 @@ class ConvolutionModule(nn.Module):
             max_abs=10.0, min_positive=0.05, max_positive=1.0
         )
 
+        self.pre_sigmoid = Identity()  # before sigmoid; for diagnostics.
+        self.sigmoid = nn.Sigmoid()
+
         self.depthwise_conv = nn.Conv1d(
             channels,
             channels,
@@ -1594,7 +1599,13 @@ class ConvolutionModule(nn.Module):
 
         x = self.in_proj(x)  # (time, batch, 2*channels)
         x = self.deriv_balancer1(x)
-        x = nn.functional.glu(x, dim=-1)  # (time, batch, channels)
+
+        x, s = x.chunk(2, dim=-1)
+        s = self.pre_sigmoid(s)
+        s = self.sigmoid(s)
+        x = x * s
+
+        # (time, batch, channels)
 
         # exchange the temporal dimension and the feature dimension
         x = x.permute(1, 2, 0)  # (#batch, channels, time).