From 2cf703ffefc4a940cb8df43372b187b0faf92227 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Tue, 3 Jan 2023 17:02:23 +0900
Subject: [PATCH] from local

---
 .../.data2vec_audio.py.swp                    | Bin 45056 -> 45056 bytes
 .../data2vec_audio.py                         |   2 +-
 2 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 ee6b6ce9ec8af40fe896506ec08f7636e2cb937a..5d89413530468bc8508704e41fc8109dda691d84 100644
GIT binary patch
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delta 378
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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 659f9f22b..dd0507e05 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
@@ -43,7 +43,7 @@ class TransformerEncoderAdapter(TransformerEncoder):
 
         for p in self.adapters.parameters():
         #    p.data = nn.Parameter(torch.zeros(p.size()).to('cuda'))
-            p.data = nn.Parameter(torch.randn(p.size()).to('cuda')/50.)
+            p.data = nn.Parameter(torch.randn(p.size()).to('cuda')/100.)
 
     def forward(self, x, padding_mask=None, layer=None, tgt_layer=None):
         x, layer_results = self.extract_features_with_adapter(