From 213297546e5201820ab2ebcba40a3fcfa8cc1e9b Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Fri, 13 Jan 2023 17:26:09 +0900
Subject: [PATCH] from local

---
 .../.asr_datamodule.py.swp                    | Bin 32768 -> 32768 bytes
 .../.train.py.swp                             | Bin 69632 -> 69632 bytes
 .../train.py                                  |   4 ++--
 3 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.asr_datamodule.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.asr_datamodule.py.swp
index 91e2d8aa71d8cc49679bd42f0cd9420c85abc0ed..b12b6d0f3a154722d591ecc7360302a49747d779 100644
GIT binary patch
delta 32
mcmZo@U}|V!5=}A)^Ym4))H7fJ0s#hwFwuj_bsI%r*8>2869}9D

delta 32
mcmZo@U}|V!5=}A)^Ym4))H7fJ0s#hwK+%KAp&LbC*8>2783=9w

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.train.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/.train.py.swp
index 6bb6b21cf0b5720b27eba4c07c5b36cd898f6da8..909066f455ea9b1e49108260857a8c94fbbddac1 100644
GIT binary patch
delta 93
zcmZozz|ydQWdq9v)~}2V3`;k2UZ`hO+r`4bumFfNfjAzBHGo(hi2pD%FsujSr9eEJ
kdE><wjFS_bIM@|HKv`k(ip!fOM_);10dY6)yW(UG0DtQl+yDRo

delta 77
zcmZozz|ydQWdq9v)*p-v3@bKsUZ`hO+Q-7cump&6fjAk6wSia*i2pM)Fl++i70eqi
a{$re+;KVU`?d4UQr)?_c+<f+~u@L}NWf)cf

diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/train.py b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/train.py
index 58230147f..3059491fc 100755
--- a/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/train.py
+++ b/egs/librispeech/ASR/pruned_transducer_stateless_gtrans/train.py
@@ -1032,11 +1032,11 @@ def run(rank, world_size, args, wb=None):
         diagnostic = diagnostics.attach_diagnostics(model, opts)
 
     librispeech = LibriSpeechAsrDataModule(args)
-
+    
     if params.full_libri:
         train_cuts = librispeech.train_all_shuf_cuts()
     else:
-        train_cuts = librispeech.train_clean_100_cuts()
+        train_cuts = librispeech.train_clean_10_cuts()
 
     def remove_short_and_long_utt(c: Cut):
         # Keep only utterances with duration between 1 second and 20 seconds