From 6b4f2d138c9ebf7d4f12442de8400b0332177607 Mon Sep 17 00:00:00 2001 From: dohe0342 Date: Sat, 10 Dec 2022 13:51:56 +0900 Subject: [PATCH] from local --- .../.train.py.swp | Bin 90112 -> 90112 bytes .../train.py | 32 +++++++----------- 2 files changed, 12 insertions(+), 20 deletions(-) diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/.train.py.swp index 94abd585e7835b904758585901a3d5ed5b6863ef..1405a00bc23da8e8d54b4a46bf76d94fc5f4ed07 100644 GIT binary patch delta 398 zcmZoTz}j$tRW!*U%+puFQqO<^2m}}yf(51|Z{H~TTaeLrv!KxDTwY;T28Ludh@|gi z!G`zsH#ry>4gv83Ag%}Ea3J;tVoe|x0^$$s3=HRicsUTy1>!kCYyreqfTk=2;yfVE z1!9n?GC<4^#P@-=tOw#kkZnMm1jMpHECs{@KzxFQfuRA2Ggufl*Eh~%=1>5F)STkf z>4|ZS;*(ig)x}^URtyXvCJ-RYE3+W;1Tpjrs=#!>^@B9PISLBJ$r-7W6ZK6H25n|( zRc4&*70ox&_-~X?F?o`N~3Qom0HaNt4MIS@i7z^0e z!>fnR7rQA~v^$=n*0~DCZp|OVAlY-J?45sM4%N~;8?&t=zvFTD?xc{6V5g`N1uZ!Gb?77w=0TUD>Wtx?O1!Hh#KYr-aoH) zp_AfrLXLX*Y$A|W#BfZX&?d#WD$kU!NwbM=8rgCABvt>+p!+{l9wNi&CeuJ83xfOa zH~*dg&Ubo}DLIkiX<3gbJegM2IFH3sT2xzSxqea26efhs!q*CZ<3D diff --git a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py index de55f139c..b0e8a02b5 100755 --- a/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py +++ b/egs/librispeech/ASR/pruned_transducer_stateless_d2v_v2/train.py @@ -1146,26 +1146,18 @@ def run(rank, world_size, args, wb=None): dec_names.append(n) dec_param.append(p) - if wb is None: - optimizer_enc = ScaledAdam( - enc_param, - lr=param.peak_enc_lr, - clipping_scale=None, - parameters_names=enc_names, - ) - optimizer_dec = ScaledAdam( - dec_param, - lr=param.peak_dec_lr, - clipping_scale=None, - parameters_names=dec_names, - ) - - else: - logging.info('start wandb sweep optimization...') - logging.info(wb.config.peak_enc_lr) - logging.info(wb.config.peak_dec_lr) - optimizer_enc = Eve(enc_param, lr=wb.config.peak_enc_lr) - optimizer_dec = Eve(dec_param, lr=wb.config.peak_dec_lr) + optimizer_enc = ScaledAdam( + enc_param, + lr=param.peak_enc_lr, + clipping_scale=None, + parameters_names=enc_names, + ) + optimizer_dec = ScaledAdam( + dec_param, + lr=param.peak_dec_lr, + clipping_scale=None, + parameters_names=dec_names, + ) scheduler_enc = Eden(optimizer_enc, params.lr_batches*params.accum_grads, params.lr_epochs) scheduler_dec = Eden(optimizer_dec, params.lr_batches*params.acuum_grads, params.lr_epochs)