run_pnorm_bnf.sh
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#!/bin/bash
# Note: In order to run BNF, run run_bnf.sh
use_gpu=true
bnf_train_stage=-100
. ./path.sh
. ./cmd.sh
. utils/parse_options.sh
set -e
set -o pipefail
set -u
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
dir=exp_bnf/tri6_bnf_gpu
else
# Use 4 nnet jobs just like run_4d_gpu.sh so the results should be
# almost the same, but this may be a little bit slow.
num_threads=16
parallel_opts="--num-threads $num_threads"
minibatch_size=128
dir=exp_bnf/tri6_bnf
fi
align_dir=exp/tri4b_ali_si284
mkdir -p exp_bnf
mkdir -p $dir
if [ ! -f $dir/.done ]; then
echo ---------------------------------------------------------------------
echo "Starting training the bottleneck network"
echo ---------------------------------------------------------------------
steps/nnet2/train_pnorm_bottleneck_fast.sh \
--samples-per-iter 400000 \
--stage $bnf_train_stage --num-jobs-nnet 4 \
--parallel-opts "$parallel_opts" \
--num-threads "$num_threads" \
--minibatch-size "$minibatch_size" \
--initial-learning-rate 0.02 --final-learning-rate 0.004 \
--pnorm-input-dim 2000 --pnorm-output-dim 400 \
--num-jobs-nnet 8 --mix-up 8000 \
--num-hidden-layers 4 \
--bottleneck-dim 42 --cmd "$train_cmd" \
data/train_si284 data/lang $align_dir $dir || exit 1
touch $dir/.done
fi
[ ! -d param_bnf ] && mkdir -p param_bnf
if [ ! -f data_bnf/train_bnf/.done ]; then
mkdir -p data_bnf
# put the archives in param_bnf/.
steps/nnet2/dump_bottleneck_features.sh --cmd "$train_cmd" \
--transform-dir exp/tri4a data/train_si284 data_bnf/train_bnf $dir param_bnf exp_bnf/dump_bnf
touch data_bnf/train_bnf/.done
fi
[ ! -d data/test_eval92 ] && echo "No such directory data/test_eval92" && exit 1;
[ ! -d data/test_dev93 ] && echo "No such directory data/test_dev93" && exit 1;
[ ! -d exp/tri4b/decode_bd_tgpr_eval92 ] && echo "No such directory exp/tri4b/decode_bd_tgpr_eval92" && exit 1;
[ ! -d exp/tri4b/decode_bd_tgpr_dev93 ] && echo "No such directory exp/tri4b/decode_bd_tgpr_dev93" && exit 1;
# put the archives in param_bnf/.
steps/nnet2/dump_bottleneck_features.sh --nj 8 \
--transform-dir exp/tri4b/decode_bd_tgpr_eval92 data/test_eval92 data_bnf/eval92_bnf $dir param_bnf exp_bnf/dump_bnf
steps/nnet2/dump_bottleneck_features.sh --nj 10 \
--transform-dir exp/tri4b/decode_bd_tgpr_dev93 data/test_dev93 data_bnf/dev93_bnf $dir param_bnf exp_bnf/dump_bnf
if [ ! data_bnf/train/.done -nt data_bnf/train_bnf/.done ]; then
steps/nnet/make_fmllr_feats.sh --cmd "$train_cmd --max-jobs-run 10" \
--transform-dir $align_dir data_bnf/train_sat data/train_si284 \
exp/tri4b exp_bnf/make_fmllr_feats/log param_bnf/
steps/append_feats.sh --cmd "$train_cmd" --nj 4 \
data_bnf/train_bnf data_bnf/train_sat data_bnf/train \
exp_bnf/append_feats/log param_bnf/
steps/compute_cmvn_stats.sh --fake data_bnf/train exp_bnf/make_fmllr_feats param_bnf
rm -r data_bnf/train_sat
touch data_bnf/train/.done
fi
## preparing Bottleneck features for eval92 and dev93
steps/nnet/make_fmllr_feats.sh \
--nj 8 --transform-dir exp/tri4b/decode_bd_tgpr_eval92 data_bnf/eval92_sat data/test_eval92 \
$align_dir exp_bnf/make_fmllr_feats/log param_bnf/
steps/nnet/make_fmllr_feats.sh \
--nj 10 --transform-dir exp/tri4b/decode_bd_tgpr_dev93 data_bnf/dev93_sat data/test_dev93 \
$align_dir exp_bnf/make_fmllr_feats/log param_bnf/
steps/append_feats.sh --nj 4 \
data_bnf/eval92_bnf data_bnf/eval92_sat data_bnf/eval92 \
exp_bnf/append_feats/log param_bnf/
steps/append_feats.sh --nj 4 \
data_bnf/dev93_bnf data_bnf/dev93_sat data_bnf/dev93 \
exp_bnf/append_feats/log param_bnf/
steps/compute_cmvn_stats.sh --fake data_bnf/eval92 exp_bnf/make_fmllr_feats param_bnf
steps/compute_cmvn_stats.sh --fake data_bnf/dev93 exp_bnf/make_fmllr_feats param_bnf
rm -r data_bnf/eval92_sat
rm -r data_bnf/dev93_sat
exit 0;