{"action":"created","comment":{"url":"https://api.github.com/repos/kaldi-asr/kaldi/pulls/comments/58648854","id":58648854,"diff_hunk":"@@ -0,0 +1,113 @@\n+#!/bin/bash\n+\n+# this is the standard \"tdnn\" system, built in nnet3; it's what we use to\n+# call multi-splice.\n+\n+# Results: \n+# %WER 15.3 | 507 17792 | 87.4 9.0 3.6 2.7 15.3 90.1 | -0.081 | exp/nnet3/tdnn_sp/decode_dev/score_10_0.5/ctm.filt.filt.sys\n+# %WER 13.9 | 507 17792 | 88.4 8.0 3.6 2.3 13.9 85.8 | -0.164 | exp/nnet3/tdnn_sp/decode_dev_rescore/score_10_0.5/ctm.filt.filt.sys\n+# %WER 13.8 | 1155 27512 | 88.5 8.7 2.7 2.3 13.8 84.2 | -0.076 | exp/nnet3/tdnn_sp/decode_test/score_10_0.0/ctm.filt.filt.sys\n+# %WER 12.5 | 1155 27512 | 89.6 7.7 2.6 2.1 12.5 81.5 | -0.133 | exp/nnet3/tdnn_sp/decode_test_rescore/score_10_0.0/ctm.filt.filt.sys\n+\n+# At this script level we don't support not running on GPU, as it would be painfully slow.\n+# If you want to run without GPU you'd have to call train_tdnn.sh with --gpu false,\n+# --num-threads 16 and --minibatch-size 128.\n+\n+stage=9\n+affix=\n+train_stage=-10\n+speed_perturb=true\n+common_egs_dir=\n+reporting_email=\n+remove_egs=false\n+decode_iter=\n+\n+. ./cmd.sh\n+. ./path.sh\n+. ./utils/parse_options.sh\n+\n+\n+if ! cuda-compiled; then\n+  cat <<EOF && exit 1\n+This script is intended to be used with GPUs but you have not compiled Kaldi with CUDA\n+If you want to use GPUs (and have them), go to src/, and configure and make on a machine\n+where \"nvcc\" is installed.\n+EOF\n+fi\n+\n+suffix=\n+if [ \"$speed_perturb\" == \"true\" ]; then\n+  suffix=_sp\n+fi\n+dir=exp/nnet3/tdnn\n+dir=$dir${affix:+_$affix}\n+dir=${dir}$suffix\n+train_set=train$suffix\n+ali_dir=exp/tri3_ali$suffix\n+\n+local/nnet3/run_ivector_common.sh --stage $stage \\\n+  --speed-perturb $speed_perturb || exit 1;\n+\n+if [ $stage -le 9 ]; then\n+  echo \"$0: creating neural net configs\";\n+\n+  # create the config files for nnet initialization\n+  python steps/nnet3/tdnn/make_configs.py  \\\n+    --feat-dir data/${train_set}_hires \\\n+    --ivector-dir exp/nnet3/ivectors_${train_set} \\\n+    --ali-dir $ali_dir \\\n+    --relu-dim 500 \\\n+    --splice-indexes \"-1,0,1 -1,0,1,2 -3,0,3 -3,0,3 -3,0,3 -6,-3,0\" \\\n+    --use-presoftmax-prior-scale true \\\n+   $dir/configs || exit 1;\n+fi\n+\n+if [ $stage -le 10 ]; then\n+  if [[ $(hostname -f) == *.clsp.jhu.edu ]] && [ ! -d $dir/egs/storage ]; then\n+    utils/create_split_dir.pl \\\n+     /export/b{09,10,11,12}/$USER/kaldi-data/egs/tedlium-$(date +'%m_%d_%H_%M')/s5/$dir/egs/storage $dir/egs/storage\n+  fi\n+\n+  steps/nnet3/train_dnn.py --stage=$train_stage \\\n+    --cmd=\"$decode_cmd\" \\\n+    --feat.online-ivector-dir exp/nnet3/ivectors_${train_set} \\\n+    --feat.cmvn-opts=\"--norm-means=false --norm-vars=false\" \\\n+    --trainer.num-epochs 2 \\","path":"egs/tedlium/s5/local/nnet3/run_tdnn.sh","position":75,"original_position":75,"commit_id":"036396efc35ad2cdb5b2039fdfce6b8e9f3d5786","original_commit_id":"036396efc35ad2cdb5b2039fdfce6b8e9f3d5786","user":{"login":"vijayaditya","id":3895456,"avatar_url":"https://avatars.githubusercontent.com/u/3895456?v=3","gravatar_id":"","url":"https://api.github.com/users/vijayaditya","html_url":"https://github.com/vijayaditya","followers_url":"https://api.github.com/users/vijayaditya/followers","following_url":"https://api.github.com/users/vijayaditya/following{/other_user}","gists_url":"https://api.github.com/users/vijayaditya/gists{/gist_id}","starred_url":"https://api.github.com/users/vijayaditya/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vijayaditya/subscriptions","organizations_url":"https://api.github.com/users/vijayaditya/orgs","repos_url":"https://api.github.com/users/vijayaditya/repos","events_url":"https://api.github.com/users/vijayaditya/events{/privacy}","received_events_url":"https://api.github.com/users/vijayaditya/received_events","type":"User","site_admin":false},"body":"did you run an experiment with larger number of epochs ? Did it help the baseline system ?","created_at":"2016-04-06T04:10:02Z","updated_at":"2016-04-06T04:10:02Z","html_url":"https://github.com/kaldi-asr/kaldi/pull/644#discussion_r58648854","pull_request_url":"https://api.github.com/repos/kaldi-asr/kaldi/pulls/644","_links":{"self":{"href":"https://api.github.com/repos/kaldi-asr/kaldi/pulls/comments/58648854"},"html":{"href":"https://github.com/kaldi-asr/kaldi/pull/644#discussion_r58648854"},"pull_request":{"href":"https://api.github.com/repos/kaldi-asr/kaldi/pulls/644"}}},"pull_request":{"url":"https://api.github.com/repos/kaldi-asr/kaldi/pulls/644","id":65049825,"html_url":"https://github.com/kaldi-asr/kaldi/pull/644","diff_url":"https://github.com/kaldi-asr/kaldi/pull/644.diff","patch_url":"https://github.com/kaldi-asr/kaldi/pull/644.patch","issue_url":"https://api.github.com/repos/kaldi-asr/kaldi/issues/644","number":644,"state":"open","locked":false,"title":"Tedlium chain and nnet3 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