From 44d0f6e0fbd61d70164bd148774aaecf35d77591 Mon Sep 17 00:00:00 2001 From: dohe0342 Date: Mon, 9 Jan 2023 22:48:06 +0900 Subject: [PATCH] from local --- .../incremental_transf/.identity_train.py.swp | Bin 77824 -> 77824 bytes .../ASR/incremental_transf/identity_train.py | 8 +++++--- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp b/egs/librispeech/ASR/incremental_transf/.identity_train.py.swp index 882671d85631b764f04b2ca9bde79aa92857a5c7..15f5829fe5b88c8d38f5a86bf21ecedae73d6422 100644 GIT binary patch delta 472 zcmX}o-77Jxcc2p za-r0?FzL7>#Xn%;VkI?c?FJXFyxjO6o8v2@a@)Yyr_39Ks5W!6;O~vz6!+l5hlZShvz3iAb8D z0bcQKFK_?}P@xC%ArC&VdKNBV3pPMMryttPn!(s&VqZ@d*5xl{*H?BX+*!1s|B};O HVk-3wFV$(2 delta 437 zcmZY5y-Nad7zgm@K+gB{iW4L%B?v7LBZ({oTl9_y3@U}*FqIM_OO8++l&GP>mLIfa z4LP+XM_YeDV@54bnuAj{7PRy|8hhZw?}6tB&r7APtF(3EwtrP#bOn8WLfDD!oewFo zAzlhxh&6-}E~qwzDWA2;6Ls`|UqVa>_l7wmQPDsY0S>h43Emx;F{qCD6`t8PE$n?` zpPkBfR*p`xAt|oU6jGT3WtN2{(X8b1sa@Y*E}8bQvb1LMk_(~ai~q|md5QC?CHaiE zM$k#?s*M|DLTt3`wh=kuvybQ*>JSGR2BBvqszDmYp=BX@gbO%_D#Ty_`k`eex`S&t z1PP)bK*vOM3w5}Gs)-ip2+1;xfg8Fw&Kq1o4YCk`Z;br~AJ767j-dqFO4A0F(*^YG Zr)y+$35U9#c;Wd>A**=2>crOT(=Q4ZT%Z5| diff --git a/egs/librispeech/ASR/incremental_transf/identity_train.py b/egs/librispeech/ASR/incremental_transf/identity_train.py index 831bf3f62..874dbdbbd 100755 --- a/egs/librispeech/ASR/incremental_transf/identity_train.py +++ b/egs/librispeech/ASR/incremental_transf/identity_train.py @@ -975,8 +975,11 @@ def run(rank, world_size, args): logging.info("About to create model") transducer_model = get_transducer_model(params) - try: pre_trained_model = torch.load('/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_12layers.pt') - except: pre_trained_model = torch.load('/home/work/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_12layers.pt') + try: + path = '/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_12layers.pt' + load_checkpoint(transducer_model) + except: + path = '/home/work/workspace/icefall/egs/librispeech/ASR/incremental_transf/conformer_12layers.pt' pre_trained_model = pre_trained_model['model'] transducer_model.load_state_dict(pre_trained_model, strict=True) transducer_model.to(device) @@ -987,7 +990,6 @@ def run(rank, world_size, args): p.requires_grad = False else: print(n) - exit() ''' for n, p in model.named_parameters(): if 'layer' not in n: