From 8f20ba4bd7e90966ba623c0d046e7d703a2876db Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Sun, 8 Jan 2023 18:05:59 +0900
Subject: [PATCH] from local

---
 .../incremental_transf/.identity_train.py.swp | Bin 57344 -> 57344 bytes
 .../ASR/incremental_transf/identity_train.py  |   5 ++++-
 2 files changed, 4 insertions(+), 1 deletion(-)

diff --git a/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp b/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp
index b727a9154a813b79edfb696d4cb306e954e8bdcb..2f9ecb4c5b8e391af4a924585b809fc5ce994309 100644
GIT binary patch
delta 414
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z2Tp4@Im{nGi4>9)2dyX<%Ehzf;#H4&*X#1?ZC0#i#p;<2PDdy7!9Y+*i->>YB>7tM
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z3}Xm3TsMdmv4>rln8z4e;l-Up@^b4C*?~d=e!SO<yx|3xIKm2+5rPGRN4v-|_OXB-
zbmOZ|<P#4#L=h<@F@P#BctTNQMVcc4Z@F`-YEvBrd--GJUQ?&B8x=MBRnBNr1*5As
lyO=UEGfQ(Z(f{SI(L=f~;0vU)^BGl&yOkOLF6WGO^9O@;Q0xEz

delta 338
zcmXBNJxc-s0LJm>@a;;?j&N#7A(x6YnhFZcslkY-3xX>sp}{^v;30xrgGWn2ghNwM
z#|^zq7F1JHlYN6;zCa|=AAH~k4?M%;c0z6^l-@1a%jL}6bU|cTN;L2H+J1V}GD^XW
z^|qMwBT_foA4{IKI#OFmNqHD}9g^x;K^aRZB8-=$^o%1^u!bCZ3F#M4IEI5w*eGHG
zCf?&b;}j>@z<OLYWhvi-(lxGdfflNm$1MH^q(?m990%CK6uwO96L+}98TR2IhjIMG
jq)W8nU=mq$qk$2=iFjizGsxI}%=5NCj7o60({TR*eLOmo

diff --git a/egs/librispeech/ASR/incremental_transf/identity_train.py b/egs/librispeech/ASR/incremental_transf/identity_train.py
index 25b3cf20f..4ebc01a48 100755
--- a/egs/librispeech/ASR/incremental_transf/identity_train.py
+++ b/egs/librispeech/ASR/incremental_transf/identity_train.py
@@ -972,11 +972,14 @@ def run(rank, world_size, args):
     for n, p in model.named_parameters():
         if 'layer' not in n:
             try: p.data = pre_trained_model[n]
-            except: print(f'pre-trained model has no parameterd named {n}.')
+            except: print(f'pre-trained model has no parameter named {n}.')
         else:
             layer_name_splited = n.split('.')
             if int(layer_name_splited[3]) % 2 == 0:
                 layer_name_splited[3] = str(int(layer_name_splited[3])//2)
+                old_name = '.'.join(layer_name_splited)
+                try: p.data = pre_trained_model[old_name]
+                except: print(f'pre-trained model has no parameter named {n}.')
                 print('.'.join(layer_name_splited))
 
     exit()