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A bug in Kaldi multi_cn run.sh
i use multi_cn/s5/run.sh train model, in the last step local/chain/run_cnn_tdnn.sh , find below bug:
run.pl: job failed, log is in exp/chain_cleaned/tdnn_cnn_1a_sp/log/train.1.3.log
2022-03-28 05:58:19,735 [/opt/kaldi/egs/multi_cn/s5/steps/libs/common.py:236 - background_command_waiter - ERROR ] Command exited with status 1: run.pl --mem 4G --gpu 1 exp/chain_cleaned/tdnn_cnn_1a_sp/log/train.1.3.log nnet3-chain-train --use-gpu=wait --apply-deriv-weights=False --l2-regularize=0.0 --leaky-hmm-coefficient=0.1 --read-cache=exp/chain_cleaned/tdnn_cnn_1a_sp/cache.1 --xent-regularize=0.1 --print-interval=10 --momentum=0.0 --max-param-change=2.0 --backstitch-training-scale=0.0 --backstitch-training-interval=1 --l2-regularize-factor=0.3333333333333333 --optimization.memory-compression-level=2 --srand=1 "nnet3-am-copy --raw=true --learning-rate=0.00044762974304870596 --scale=1.0 exp/chain_cleaned/tdnn_cnn_1a_sp/1.mdl - |nnet3-copy --edits='set-dropout-proportion name=* proportion=0.0' - - |" exp/chain_cleaned/tdnn_cnn_1a_sp/den.fst "ark,bg:nnet3-chain-copy-egs --frame-shift=0 ark:exp/chain_cleaned/tdnn_cnn_1a_sp/egs/cegs.6.ark ark:- | nnet3-chain-shuffle-egs --buffer-size=5000 --srand=1 ark:- ark:- | nnet3-chain-merge-egs --minibatch-size=128,64 ark:- ark:- |" exp/chain_cleaned/tdnn_cnn_1a_sp/2.3.raw
the exp/chain_cleaned/tdnn_cnn_1a_sp/log/train.1.3.log says:
ERROR (nnet3-chain-train[5.5]:ExecuteCommand():nnet-compute.cc:445) Error running command c247: tdnnf17.relu.Propagate(NULL, m126, &m126)
[ Stack-Trace: ]
/opt/kaldi/src/lib/libkaldi-base.so(kaldi::MessageLogger::LogMessage() const+0x82c) [0x7f9787f912aa]
nnet3-chain-train(kaldi::MessageLogger::LogAndThrow::operator=(kaldi::MessageLogger const&)+0x21) [0x4115d1]
/opt/kaldi/src/lib/libkaldi-nnet3.so(kaldi::nnet3::NnetComputer::ExecuteCommand()+0x13d1) [0x7f9789fef00f]
/opt/kaldi/src/lib/libkaldi-nnet3.so(kaldi::nnet3::NnetComputer::Run()+0x18a) [0x7f9789fef22e]
/opt/kaldi/src/lib/libkaldi-nnet3.so(kaldi::nnet3::NnetChainTrainer::TrainInternal(kaldi::nnet3::NnetChainExample const&, kaldi::nnet3::NnetComputation const&)+0x5b) [0x7f978a04116d]
/opt/kaldi/src/lib/libkaldi-nnet3.so(kaldi::nnet3::NnetChainTrainer::Train(kaldi::nnet3::NnetChainExample const&)+0x19d) [0x7f978a0415c5]
nnet3-chain-train(main+0x84d) [0x4103f3]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf0) [0x7f97870e4830]
nnet3-chain-train(_start+0x29) [0x40fad9]
Would someone be able to help debug this issue?
Just guessing from my own experience. Do you have enough GPU memory and have you set the GPU to exclusive mode?
yeah, I would also guess gpu memory or system memory or something like that. y.
On Tue, May 24, 2022 at 7:31 AM svenha @.***> wrote:
Just guessing from my own experience. Do you have enough GPU memory and have you set the GPU to exclusive mode?
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