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egs/gale_arabic/s5b/local/nnet3/tuning/run_tdnn_1a.sh
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#!/bin/bash # started from tedlium recipe with few edits set -e -o pipefail -u # First the options that are passed through to run_ivector_common.sh # (some of which are also used in this script directly). stage=0 nj=30 decode_nj=30 min_seg_len=1.55 train_set=train gmm=tri2b # this is the source gmm-dir for the data-type of interest; it # should have alignments for the specified training data. num_threads_ubm=32 nnet3_affix=_cleaned # cleanup affix for exp dirs, e.g. _cleaned tdnn_affix= #affix for TDNN directory e.g. "a" or "b", in case we change the configuration. # Options which are not passed through to run_ivector_common.sh train_stage=-10 splice_indexes="-2,-1,0,1,2 -1,2 -3,3 -7,2 -3,3 0 0" remove_egs=true relu_dim=850 num_epochs=3 . ./cmd.sh . ./path.sh . ./utils/parse_options.sh if ! cuda-compiled; then cat <<EOF && exit 1 This script is intended to be used with GPUs but you have not compiled Kaldi with CUDA If you want to use GPUs (and have them), go to src/, and configure and make on a machine where "nvcc" is installed. EOF fi local/nnet3/run_ivector_common.sh --stage $stage \ --nj $nj \ --min-seg-len $min_seg_len \ --train-set $train_set \ --gmm $gmm \ --num-threads-ubm $num_threads_ubm \ --nnet3-affix "$nnet3_affix" gmm_dir=exp/${gmm} graph_dir=$gmm_dir/graph ali_dir=exp/${gmm}_ali_${train_set}_sp_comb dir=exp/nnet3${nnet3_affix}/tdnn${tdnn_affix}_sp train_data_dir=data/${train_set}_sp_hires_comb train_ivector_dir=exp/nnet3${nnet3_affix}/ivectors_${train_set}_sp_hires_comb for f in $train_data_dir/feats.scp $train_ivector_dir/ivector_online.scp \ $graph_dir/HCLG.fst $ali_dir/ali.1.gz $gmm_dir/final.mdl; do [ ! -f $f ] && echo "$0: expected file $f to exist" && exit 1 done if [ $stage -le 12 ]; then if [[ $(hostname -f) == *.clsp.jhu.edu ]] && [ ! -d $dir/egs/storage ]; then utils/create_split_dir.pl \ /export/b0{3,4,5,6}/$USER/kaldi-data/egs/tedlium-$(date +'%m_%d_%H_%M')/s5_r2/$dir/egs/storage $dir/egs/storage fi steps/nnet3/tdnn/train.sh --stage $train_stage \ --num-epochs $num_epochs --num-jobs-initial 2 --num-jobs-final 2 \ --splice-indexes "$splice_indexes" \ --feat-type raw \ --online-ivector-dir ${train_ivector_dir} \ --cmvn-opts "--norm-means=false --norm-vars=false" \ --initial-effective-lrate 0.0015 --final-effective-lrate 0.00015 \ --cmd "$decode_cmd" \ --relu-dim "$relu_dim" \ --remove-egs "$remove_egs" \ $train_data_dir data/lang $ali_dir $dir fi if [ $stage -le 13 ]; then steps/nnet3/decode.sh --nj $decode_nj --cmd "$decode_cmd" --num-threads 4 \ --online-ivector-dir exp/nnet3${nnet3_affix}/ivectors_test_hires \ ${graph_dir} data/test_hires ${dir}/decode || exit 1 fi exit 0; |