From 8b59cb1ac062243e9e3baf364581a9326f211054 Mon Sep 17 00:00:00 2001
From: dohe0342 <kimdohe1070@gmail.com>
Date: Mon, 9 Jan 2023 20:19:54 +0900
Subject: [PATCH] from local

---
 .../ASR/incremental_transf/.conformer.py.swp  | Bin 114688 -> 114688 bytes
 .../incremental_transf/.identity_train.py.swp | Bin 65536 -> 65536 bytes
 .../ASR/incremental_transf/identity_train.py  |   2 --
 3 files changed, 2 deletions(-)

diff --git a/egs/librispeech/ASR/incremental_transf/.conformer.py.swp b/egs/librispeech/ASR/incremental_transf/.conformer.py.swp
index 0ab8cbcba5ab1fdecf778fa40a2b4af2b391f31d..0175375e557e2c742a981fe497b55cf459c11a3e 100644
GIT binary patch
delta 35
pcmZo@U~gz(7fmt<^Ym4))H7fJ0s#gF&2PJtzch+&6=i(A9{{Ge3Z(!5

delta 35
pcmZo@U~gz(7fmt<^Ym4))H7fJ0s#hw-mklp(;G#%iZZ_54*;h03VQ$m

diff --git a/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp b/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp
index 3fcaabe909a02c5e56a19ac386c8c586002c828e..33277a7f75df771d00cdfac403a95d19eab79628 100644
GIT binary patch
delta 296
zcmXZXJxD@P0LAg6Jb3EsLx+ZFd7BXgf)L>sNL!nmO9(9u2^Ba54qeBf?V@vgPY^Cn
zLPj(+Mzl0m($EmJi}n{h@Z+5I7~>h^4bC&Myt~NQ%GK1DCJ9MtDNijjUzbL3xJDCY
z{H;k}7@~tc%vPl*v~Y|ZwvolpiquDh77nqG0H1;M5$IHRj5ZEXMhRJ@@tcw!Fh&Ok
zMHJxUH7WJb#SJb|Lx@c*j=kd<QNqQ%d*4R&-5^}1d3Iu79ye_GmUQ3s9nWnY*|-}w
Gs<;0oG&Y|A

delta 292
zcmWm9JxfAi0LAem+)}%@7bh1<9m1rS?XE%u?ruWC9nwMU<r)sw()|V*w+|3$OE?G*
zI3%<cP7Y0t&5F3RM*cnU<BW$B1Xd7OeLoR#O(PK&?!KeaC?;u3a;athH>Dw7@r)Ku
zu#cY&=?h)>*uiXFGB`sCX(Zvm#@LY_&_)@DNMUZPu1{O~z&$+VkVOVIe%Ba87adel
zK^ohb#-#ynaRVQxaADz(bIXIhn2A{L(XdxO2<OKuW^(kh8a{e^j(=UdZ0=rMRjTKC
I^X3(w7B5RRasU7T

diff --git a/egs/librispeech/ASR/incremental_transf/identity_train.py b/egs/librispeech/ASR/incremental_transf/identity_train.py
index bc8f48dcf..8b722562f 100755
--- a/egs/librispeech/ASR/incremental_transf/identity_train.py
+++ b/egs/librispeech/ASR/incremental_transf/identity_train.py
@@ -982,7 +982,6 @@ def run(rank, world_size, args):
     transducer_model.load_state_dict(pre_trained_model, strict=True)
 
     model = get_interformer_model(transducer_model.encoder, params)
-    print(model)
     '''
     for n, p in model.named_parameters():
         if 'layer' not in n:
@@ -998,7 +997,6 @@ def run(rank, world_size, args):
             else:
                 print(f'skipping param load {n}')
     '''
-    exit()
 
     num_param = sum([p.numel() for p in model.parameters()])
     logging.info(f"Number of model parameters: {num_param}")