From 40a3e35eb77ae53f0d76a75ac98888b3046ee2cf Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Mon, 9 Jan 2023 11:31:27 +0900
Subject: [PATCH] from local

---
 .../.conformer_randomcombine.py.swp           | Bin 102400 -> 102400 bytes
 .../conformer_randomcombine.py                |  23 +++++++++++++-----
 2 files changed, 17 insertions(+), 6 deletions(-)

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer_randomcombine.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.conformer_randomcombine.py.swp
index 05be579f8c43ef17fee197ed1cb992729e11dc5e..785f07df7e4c2f72c8746ecce6176ec5c07b62fe 100644
GIT binary patch
delta 443
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delta 353
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BUSI$K

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer_randomcombine.py b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer_randomcombine.py
index 0d80f918e..121254ec6 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer_randomcombine.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/conformer_randomcombine.py
@@ -211,14 +211,25 @@ class Conformer(EncoderInterface):
             )  # (T, N, C)
 
         x = x.permute(1, 0, 2)  # (T, N, C) ->(N, T, C)
-        
+         
         layer_outputs = [x.permute(1, 0, 2) for x in layer_outputs]
-        x = self.layer_norm(1/4*(self.sigmoid(self.alpha[0])*layer_outputs[2] + \
-                                 self.sigmoid(self.alpha[1])*layer_outputs[5] + \
-                                 self.sigmoid(self.alpha[2])*layer_outputs[8] + \
-                                 self.sigmoid(self.alpha[3])*layer_outputs[11]
+        if self.group_num == 4:
+            x = self.layer_norm(1/4*(self.sigmoid(self.alpha[0])*layer_outputs[2] + \
+                                     self.sigmoid(self.alpha[1])*layer_outputs[5] + \
+                                     self.sigmoid(self.alpha[2])*layer_outputs[8] + \
+                                     self.sigmoid(self.alpha[3])*layer_outputs[11]
+                                    )
                                 )
-                            )
+        elif self.group_num == 6:
+            x = self.layer_norm(1/6*(self.sigmoid(self.alpha[0])*layer_outputs[1] + \
+                                     self.sigmoid(self.alpha[1])*layer_outputs[3] + \
+                                     self.sigmoid(self.alpha[2])*layer_outputs[5] + \
+                                     self.sigmoid(self.alpha[3])*layer_outputs[7] + \
+                                     self.sigmoid(self.alpha[4])*layer_outputs[9] + \
+                                     self.sigmoid(self.alpha[5])*layer_outputs[11]
+                                    )
+                                )
+
 
         '''
         x = self.layer_norm(1/12*(self.sigmoid(self.alpha[0])*layer_output[0] + \