From a7c41ca5ddb9ef341a79dbf789910b28b32ab417 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Sat, 10 Dec 2022 13:08:48 +0900
Subject: [PATCH] from local

---
 .../.train.py.swp                             | Bin 65536 -> 65536 bytes
 .../train.py                                  |   4 ----
 2 files changed, 4 deletions(-)

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 742ca4b0344f293c771d4b2b832ef0486795c4d4..f3a2f079b74ccad60bd3b75639de2096550d3ea1 100644
GIT binary patch
delta 441
zcmXxgPbkB27{~Dk`(xv`{U+_e#YJ{nJ4j@c)kek~rEM2manfAoPY(OJ3Z<{KQcmQi
z*6-rXQlx~Nt07BTIbc%W$WyPLPd(4+V;C00uz1sfiII3mpFbdsE>f~?WqR(5-kM&Q
zGCiJGzxGrwlC%6>Q_3^gpTE^aR*^;wKD;!GlyQd>6p%#}K2)1T9#DjVWrPug8!l9w
zBFC6R7TvJn+##}obu2g}FY|;PCJ{nA-Wo+NU}6`Gn87rL5JfAV?IKq=!amk8iwt_9
z!;N>F$PKQsgDis3ZNoeeKCL1(e4vao9AE`g2%!a!ba#n8{PdVa7+vOOc)MO{k+y%P
i7Fn{ZSkk2qN2|a4bgZD9374uQ22?5DX*P_16~6&h5>bKx

delta 461
zcmXZY!7GDt7{Kvo>)qZBFI#HkMq%x;#-xN;sWr25+F=f6Q^JLVo9s>QGcRkWB?prn
z@ZOx9oE#js14Z!{tSA}bTd$`+_4NJyPLHlDx~}-L;Z!`?Ga3pD;}MD34|2D!m%gUQ
zmNC8Fw~)4B7ts{!HDh?E#_}(k$PLz!LI^&*w~1Wi0wo+`6Eo<=N2|yqj#0)o;^;yr
z9$G|dsNw`WNW%pccW#l2Tk?`+89+Ze&<+g^mq;BZ3Rpq{Bk<r?75Tw4o^Xy`tY8ik
z=z{}aPLX?@qKZANVbvKEiLj`sIrxAo4D6$bEi7UZ-T35wb(|rOWsIA}XvuCCrWaIW
rwW2A3;Xu%c&ijq;M8gV^|InN*TVaS`OZ$zZWX=kMfuPw;I<Ni!ZK71$

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 99a35df64..8dac60025 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py
@@ -736,16 +736,13 @@ def compute_loss(
                 token_ids=token_ids,
             )
         
-        logging.info('1')
         # Works with a BPE model
         decoding_graph = k2.ctc_graph(token_ids, modified=False, device=device)
-        logging.info('2')
         dense_fsa_vec = k2.DenseFsaVec(
             ctc_output,
             supervision_segments,
             allow_truncate=params.subsampling_factor - 1,
         )
-        logging.info('3')
 
         ctc_loss = k2.ctc_loss(
             decoding_graph=decoding_graph,
@@ -754,7 +751,6 @@ def compute_loss(
             reduction="sum",
             use_double_scores=params.use_double_scores,
         )
-        logging.info('4')
         assert ctc_loss.requires_grad == is_training
         loss += params.ctc_loss_scale * ctc_loss