From 68be92565c35e0d42bb658da889b1a34c7f36a62 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Wed, 26 Apr 2023 12:17:21 +0900
Subject: [PATCH] from local

---
 .../.data2vec_audio.py.swp                    | Bin 40960 -> 40960 bytes
 .../data2vec_audio.py                         |   9 +--------
 2 files changed, 1 insertion(+), 8 deletions(-)

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.data2vec_audio.py.swp
index a90e44689c98b8a9121ae3b9ee21eab6148ea4d0..aaedea2d15b14fc5a575eecdb2901826378734b0 100644
GIT binary patch
delta 192
zcmZoTz|?SnNi@kI%+puFQqO<^2m}}yCQbK9@!2R^Ex>5Md7?nEKCcfO149ZsMACk;
zpu>I3Ya9#=i-0%}h$DfR5r|&`RV)DFav%n&_6K5BApQ*0eHw^Y0CD4HO~*vm$?0y&
zlQ*ccfN2<egEGtHEH|~uac(+bxd)nTK)&$g3^&oq;_lLn3X>nUh)!PNZnU}5-I8&$
IyywF(0Ah<VU;qFB

delta 346
zcmZoTz|?SnNi@kI%+puFQqO<^2m}}y%BFjyNNp6Y7GQMSJW-%npI3{Ofgz3!BI!0+
z(BZ!27Y+u7vp~EGh%<rM6o?st_zgP)!xSK{0b*ky<_6-MK%MJ>xDJR5H)}d3vQCzF
zXA3MyOi9ViOOMY@EY8-;%g?JyEy~x>)GN-cO4ZQRWKci?1x1;8B^uZ@AXHA4jFaY#
z&WuGEHo4SYbMnI$(aEA7Mw_3xTQVkt48=4p+8`ET40a`W+?AG^SW;S)S`1aPS=94&
F7yvmsT>$_9

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
index 4f47dc1cf..ba225b775 100644
--- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/data2vec_audio.py
@@ -490,9 +490,6 @@ class Data2VecAudioModel(BaseFairseqModel):
         
         ## for prompt tuning
         if prompt is not None:
-            print(features.size())
-            print(padding_mask.size())
-            print(padding_mask[0])
             conv_feat_all = torch.tensor([]).to(features.device)
             for i in range(padding_mask.size()[0]):
                 nonzero = padding_mask[i].nonzero()
@@ -500,11 +497,7 @@ class Data2VecAudioModel(BaseFairseqModel):
                     conv_feat_all = torch.cat([conv_feat_all, features[i][nonzero[0]]])
                 except:
                     conv_feat_all = torch.cat([conv_feat_all, features])
-            print(conv_feat_all.size())
-                #print(padding_mask[i].nonzero())
-            print(padding_mask.nonzero())
-            print(padding_mask.nonzero().size())
-            
+            print(conv_feat_all.size()) 
             exit()
             prompt = prompt.expand((features.size()[0], prompt.size()[0], prompt.size()[1]))
             features = torch.cat([prompt, features], dim=1)