Remove 2/3 StructuredLinear/StructuredConv1d modules, use linear/conv1d

egs/librispeech/ASR/pruned_transducer_stateless7/conformer.py

@@ -466,7 +466,7 @@ class RelPositionMultiheadAttention(nn.Module):
             self.head_dim * num_heads == self.embed_dim
         ), "embed_dim must be divisible by num_heads"
 
-        self.in_proj = StructuredLinear((embed_dim,), (3, embed_dim), bias=True)
+        self.in_proj = nn.Linear(embed_dim, 3 * embed_dim, bias=True)
         self.in_balancer = ActivationBalancer(channel_dim=-1, max_abs=5.0)
         self.proj_balancer = ActivationBalancer(channel_dim=-1, min_positive=0.0,
                                                 max_positive=1.0, max_abs=10.0)
@@ -544,8 +544,8 @@ class RelPositionMultiheadAttention(nn.Module):
             pos_emb,
             self.embed_dim,
             self.num_heads,
-            self.in_proj.get_weight(),
-            self.in_proj.get_bias(),
+            self.in_proj.weight,
+            self.in_proj.bias,
             self.dropout,
             self.out_proj.weight,
             self.out_proj.bias,
@@ -881,9 +881,9 @@ class ConvolutionModule(nn.Module):
         # kernerl_size should be a odd number for 'SAME' padding
         assert (kernel_size - 1) % 2 == 0
 
-        self.pointwise_conv1 = StructuredConv1d(
-            (channels,),
-            (2, channels),
+        self.pointwise_conv1 = nn.Conv1d(
+            channels,
+            2 * channels,
             kernel_size=1,
             stride=1,
             padding=0,