From 208a473c5efa94b4914be457434e285f40ce1313 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Tue, 11 Apr 2023 16:59:20 +0900
Subject: [PATCH] from local

---
 .../.data2vec_audio.py.swp                    | Bin 40960 -> 40960 bytes
 .../.decode.py.swp                            | Bin 49152 -> 49152 bytes
 .../data2vec_audio.py                         |   2 +-
 3 files changed, 1 insertion(+), 1 deletion(-)

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 571e1fae240f6a0b07b9850bc2511d60224b1824..556bdbc2980f93922b14f9556b8af9b2755a8461 100644
GIT binary patch
delta 169
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z{=&w<@EM5D193MHy8!WDpvrBVRUId?Z02*TWb`V^%q!7QPb*DMPR=G8C}IFZb<N3!
MYLc5Lx#vXy00ELQLI3~&

delta 136
zcmZoTz|?SnX~TPF#?Z|lm>2LcI&YpRP^{1UjD>-LkBxzWL4bk5d9t9xXT?f(1_mD>
z_6A~gAbt##odd+7Knzm(ZnLW6M3%`sZhVvTUD+o8b(ICtj0zwYvvDk#28wV^Uf{|;
XS=&u?^G{bZ#>w_-+?yx4=S2Vjl}aV$

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.decode.py.swp
index 9ad05a615139567325e7ee09f54c45873fc7076a..b4c01865b3f5f60efe886ad56a489f258b3f5e96 100644
GIT binary patch
delta 34
ocmZo@U~Xt&7Edw=^Ym4))H7fJ0s#hwTSBHO+cr<#DE@Lk0GRIzRsaA1

delta 34
ocmZo@U~Xt&7Edw=^Ym4))H7fJ0s#hwPhpZNml9Goioe_s0GWUaE&u=k

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 491bb6b35..a1c382740 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
@@ -495,7 +495,7 @@ class Data2VecAudioModel(BaseFairseqModel):
             features = torch.cat([prompt, features], dim=1)
             prompt_padding_mask = torch.zeros(prompt.size()[0], prompt.size()[1]).type(torch.BoolTensor).to(features.device)
             padding_mask = torch.cat([prompt_padding_mask, padding_mask], dim=1)
-            print(padding_mask)
+            print('fuccckkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk!!!!!!!!!!!!!!!!!!1')
 
         features = self.layer_norm(features)