From 83123c3baaf9d937bc93f6aeb370bc9f6d3344b1 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Tue, 13 Dec 2022 17:04:56 +0900
Subject: [PATCH] from local

---
 egs/librispeech/ASR/.run_v3.sh.swp            | Bin 12288 -> 12288 bytes
 .../.train.py.swp                             | Bin 73728 -> 73728 bytes
 .../train.py                                  |   5 +----
 3 files changed, 1 insertion(+), 4 deletions(-)

diff --git a/egs/librispeech/ASR/.run_v3.sh.swp b/egs/librispeech/ASR/.run_v3.sh.swp
index 265a5bb2f7213ed2206c0d8d0e92f431d244e236..c769b208bdc33e2a5a911543926b482a42cbd99a 100644
GIT binary patch
delta 30
kcmZojXh;xEG6?hZRj|}EU;qLE28N3gGm=|2ioVtd0D8FyV*mgE

delta 30
kcmZojXh;xEG6?hZRj|}EU;qLE28J~fGm^tMioVtd0C<ZC5dZ)H

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp
index cd7d73fdba0ace31cd7c498a06d2ffcafc4cc966..566bf3a2b9389f5d53c9cfbb81c989add6a8dc10 100644
GIT binary patch
delta 255
zcmXBO!HPj)90l<6l}lXL+;57lowA{8Gc|>*G&@CEdIK8|K(k{ZbHCyNX2W8N?m`sZ
zvXvoug0a53Jis_|>eu=AU!9H{=(vHYDMd+1nG`9<lE<}?4gwz`047j!<o;G{pTa;l
z@_eOOk1St+1vM#4UJUr5PpZ=!8T4lWHdQG>mniT{6B^TiDpa66X>`>ApU$+?k-;~Q
z2Gz)-SMoV%OKV!ulpZ5n^O-3&Vf8-LmHQu5UtU5*deS~d9q%ACbtuP2{iMj<0d)^F
Al>h($

delta 282
zcmXBOJxjx27=_{ULW<TVHbD?nFd0*ag3h8?=qCOJiERflAXrp%v7;a0k|CqcN=3;a
zE)sEaDO!Jnlju?$bn+GtT%3nzI-T6=<kq$8nOfp`z6rBg@AcmKDo7JUl3b~ldC!Bz
zgQKEUANhZU)L;5#DaQ`BF@yI}=>qFmz!(OO^n^34pp3pPUE%~SG_edDKPBlK54b|N
zq^iz2j<Jd<xcFdD4_zE$AA5*zZ(Q?O%syXCA-(gBlLT*863h>$J>Se(0ZEqXlj-TS
ZvBw)x+zR8(cDqttiy9ld(N;68=obV1IOG5T

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
index 33bc35195..be454c04d 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
@@ -1009,10 +1009,7 @@ def train_one_epoch(
 
             # NOTE: We use reduction==sum and loss is computed over utterances
             # in the batch and there is no normalization to it so far.
-            if scaler._scale.item() >= 1.0e-05:
-                scaler.scale(loss).backward()
-            else:
-                logging.warning(f"Grad scale is small: {cur_grad_scale}")
+            logging.warning(f"Grad scale is small: {cur_grad_scale}")
 
             if params.multi_optim and batch_idx % params.accum_grads == 0:
                 set_batch_count(model, params.batch_idx_train)