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egs/ptb/s5/local/rnnlm/tuning/run_tdnn_a.sh
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#!/bin/bash
# To be run from the directory egs/ptb/s5.
# This is to be done after local/prepare_rnnlm_data.sh.
# some of the output follows.
# rnnlm/train_rnnlm.sh: best iteration (out of 8) was 3, linking it to final iteration.
# Train objf: -92.38 -5.01 -4.70 -4.48 -4.30 -4.14 -4.01 -3.81
# Dev objf: -9.21 -5.29 -5.05 -4.96 -4.97 -5.02 -5.09 -5.16
set -e
embedding_dim=400
dir=exp/rnnlm_tdnn_a
stage=0
train_stage=0
. utils/parse_options.sh # parse options-- mainly for the --stage parameter.
for f in data/vocab/words.txt data/text/ptb.txt; do
[ ! -f ] && echo "$0: expected file $f to exist" && exit 1
done
if [ $stage -le 0 ]; then
mkdir -p $dir/config
cp data/vocab/words.txt $dir/config/
cat > $dir/config/data_weights.txt <<EOF
ptb 1 1.0
EOF
echo "<unk>" >$dir/config/oov.txt # not really necessary as OOVs were previously
# converted to <unk>, but doesn't hurt.
# we need the unigram probs to get the unigram features.
rnnlm/get_unigram_probs.py --vocab-file=data/vocab/words.txt \
--data-weights-file=$dir/config/data_weights.txt \
data/text >$dir/config/unigram_probs.txt
# choose features
rnnlm/choose_features.py --unigram-probs=$dir/config/unigram_probs.txt \
--use-constant-feature=true \
--special-words='<s>,</s>,<brk>,<unk>' \
data/vocab/words.txt > $dir/config/features.txt
cat >$dir/config/xconfig <<EOF
input dim=$embedding_dim name=input
relu-renorm-layer name=tdnn1 dim=400 input=Append(0, IfDefined(-1))
relu-renorm-layer name=tdnn2 dim=400 input=Append(0, IfDefined(-1))
relu-renorm-layer name=tdnn3 dim=400 input=Append(0, IfDefined(-2))
output-layer name=output include-log-softmax=false dim=$embedding_dim
EOF
rnnlm/validate_config_dir.sh data/text $dir/config
fi
if [ $stage -le 1 ]; then
rnnlm/prepare_rnnlm_dir.sh data/text $dir/config $dir
fi
if [ $stage -le 2 ]; then
rnnlm/train_rnnlm.sh --num-epochs 40 --cmd "queue.pl" $dir
fi
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