run_4d3.sh
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#!/bin/bash
# run_4d3.sh is as run_4d.sh, but using a newer version of the scripts that
# dump the egs with several frames of labels.
train_stage=-10
use_gpu=true
dir=exp/nnet4d3
. ./cmd.sh
. ./path.sh
. utils/parse_options.sh
if $use_gpu; then
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
parallel_opts="--gpu 1"
num_threads=1
minibatch_size=512
else
num_threads=16
minibatch_size=128
parallel_opts="--num-threads $num_threads"
fi
if true || [ ! -f $dir/final.mdl ]; then
steps/nnet2/train_pnorm_simple2.sh --stage $train_stage \
--samples-per-iter 200000 \
--num-threads "$num_threads" \
--minibatch-size "$minibatch_size" \
--parallel-opts "$parallel_opts" \
--num-jobs-nnet 4 \
--num-epochs 13 --add-layers-period 1 \
--num-hidden-layers 2 \
--mix-up 4000 \
--initial-learning-rate 0.02 --final-learning-rate 0.004 \
--cmd "$decode_cmd" \
--pnorm-input-dim 1000 \
--pnorm-output-dim 200 \
data/train data/lang exp/tri3b_ali $dir || exit 1;
fi
steps/nnet2/decode.sh --config conf/decode.config --cmd "$decode_cmd" --nj 20 \
--transform-dir exp/tri3b/decode \
exp/tri3b/graph data/test $dir/decode &
steps/nnet2/decode.sh --config conf/decode.config --cmd "$decode_cmd" --nj 20 \
--transform-dir exp/tri3b/decode_ug \
exp/tri3b/graph_ug data/test $dir/decode_ug
wait