kaldi/egs/babel/s5b/run-2a-nnet-gpu.sh

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#!/bin/bash
dir=exp/tri6_nnet
train_stage=-10
. conf/common_vars.sh
. ./lang.conf
# This parameter will be used when the training dies at a certain point.
train_stage=-100
. ./utils/parse_options.sh
set -e
set -o pipefail
set -u
# Wait till the main run.sh gets to the stage where's it's
# finished aligning the tri5 model.
echo "Waiting till exp/tri5_ali/.done exists...."
while [ ! -f exp/tri5_ali/.done ]; do sleep 30; done
echo "...done waiting for exp/tri5_ali/.done"
if [ ! -f $dir/.done ]; then
steps/nnet2/train_pnorm_fast.sh \
--stage $train_stage --mix-up $dnn_mixup \
--initial-learning-rate $dnn_init_learning_rate \
--final-learning-rate $dnn_final_learning_rate \
--num-hidden-layers $dnn_num_hidden_layers \
--pnorm-input-dim $dnn_input_dim \
--pnorm-output-dim $dnn_output_dim \
--cmd "$train_cmd" \
"${dnn_gpu_parallel_opts[@]}" \
data/train data/lang exp/tri5_ali $dir || exit 1
touch $dir/.done
fi