From 31c9c401615b722f983956c2bf70f074b935c474 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Thu, 16 Feb 2023 00:58:03 +0900
Subject: [PATCH] from local

---
 .../ASR/conformer_ctc3/.decode.py.swp         | Bin 49152 -> 49152 bytes
 egs/tedlium2/ASR/conformer_ctc3/.train.py.swp | Bin 69632 -> 69632 bytes
 egs/tedlium2/ASR/conformer_ctc3/train.py      |  56 ------------------
 3 files changed, 56 deletions(-)

diff --git a/egs/tedlium2/ASR/conformer_ctc3/.decode.py.swp b/egs/tedlium2/ASR/conformer_ctc3/.decode.py.swp
index 03ea403b1e22329a261c9f3327c65ac9018e5868..2f9ba22fe522937ee2df0fc4ebe679300b84646b 100644
GIT binary patch
delta 33
ncmZo@U~Xt&7E3Y+^Ym4))H7fJ0s#hw^m}iT<yLPLd$k_`lRyeD

delta 33
ncmZo@U~Xt&7E3Y+^Ym4))H7fJ0s#hw{6%k)XLW59d$k_`leY?1

diff --git a/egs/tedlium2/ASR/conformer_ctc3/.train.py.swp b/egs/tedlium2/ASR/conformer_ctc3/.train.py.swp
index ea41fd5603dc7bd812747a4c005aa4ff370f504e..547e2af731c2c7257fb41ed1256269e6c81f6808 100644
GIT binary patch
delta 648
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zQu<b01@#R$q(i4Ft%6&ZLWZiKB05Q3#BWpzfgXHb?tbrc_r7;G>sqs}weFAjY*P|B
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zCN$!zRQikG_=FKu<C0D10~u+7&I~3oj>2j5q6aDLaYEm)h6y}J7zZWN2Hs#8ooK-$
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X3-)^_?0aaAy6ery?HVs}y&t^+rt5bV

delta 545
zcmXZZL1>a;9LMp$zOQaMeR~ZGY0id@#6#Mwi?^a=!!hbq;DQD_j7o`J3L;R*T~>ki
zAOuCd9U|Ci_>Ot8!y@W1kRsR)Bd9~Li)rL;S$#_%`0)Qf&mW!#eoxWTi<Z9TG#!T0
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O)${j<?32Gg`2PaE1!0T;

diff --git a/egs/tedlium2/ASR/conformer_ctc3/train.py b/egs/tedlium2/ASR/conformer_ctc3/train.py
index 991b5c0e7..e41ffeebd 100755
--- a/egs/tedlium2/ASR/conformer_ctc3/train.py
+++ b/egs/tedlium2/ASR/conformer_ctc3/train.py
@@ -688,62 +688,6 @@ def compute_loss(
                 use_double_scores=params.use_double_scores,
             )
 
-            '''
-            dense_fsa_vec = k2.DenseFsaVec(
-                nnet_output[0],
-                supervision_segments,
-                allow_truncate=params.subsampling_factor - 1,
-            )
-            
-            dense_fsa_vec_inter = [
-                #k2.DenseFsaVec(
-                #    nnet_output[1][2],
-                #    supervision_segments,
-                #    allow_truncate=params.subsampling_factor - 1,
-                #),
-                #k2.DenseFsaVec(
-                #    nnet_output[1][5],
-                #    supervision_segments,
-                #    allow_truncate=params.subsampling_factor - 1,
-                #),
-                k2.DenseFsaVec(
-                    nnet_output[1][8],
-                    supervision_segments,
-                    allow_truncate=params.subsampling_factor - 1,
-                ),
-                #k2.DenseFsaVec(
-                #    nnet_output[1][11],
-                #    supervision_segments,
-                #    allow_truncate=params.subsampling_factor - 1,
-                #),
-                #k2.DenseFsaVec(
-                #    nnet_output[1][14],
-                #    supervision_segments,
-                #    allow_truncate=params.subsampling_factor - 1,
-                #)
-            ]
-
-            ctc_loss = k2.ctc_loss(
-                decoding_graph=decoding_graph,
-                dense_fsa_vec=dense_fsa_vec,
-                output_beam=params.beam_size,
-                reduction=params.reduction,
-                use_double_scores=params.use_double_scores,
-            ) 
-            
-            inter_ctc_loss = 0
-            for fsa in dense_fsa_vec_inter:
-                inter_ctc_loss += k2.ctc_loss(
-                    decoding_graph=decoding_graph,
-                    dense_fsa_vec=fsa,
-                    output_beam=params.beam_size,
-                    reduction=params.reduction,
-                    use_double_scores=params.use_double_scores,
-                ) 
-            
-            ctc_loss = (1-params.interctc_weight) * ctc_loss + params.interctc_weight * inter_ctc_loss
-            '''
-
         if params.att_rate > 0.0:
             with torch.set_grad_enabled(is_training):
                 mmodel = model.module if hasattr(model, "module") else model