#! /usr/bin/env bash

# grid-search for hyper-parameters in language model
CUDA_VISIBLE_DEVICES=0,1,2,3 \
python3 -u ${MAIN_ROOT}tools/tune.py \
--num_batches=-1 \
--batch_size=128 \
--beam_size=500 \
--num_proc_bsearch=12 \
--num_conv_layers=2 \
--num_rnn_layers=3 \
--rnn_layer_size=2048 \
--num_alphas=45 \
--num_betas=8 \
--alpha_from=1.0 \
--alpha_to=3.2 \
--beta_from=0.1 \
--beta_to=0.45 \
--cutoff_prob=1.0 \
--cutoff_top_n=40 \
--use_gru=False \
--use_gpu=True \
--share_rnn_weights=True \
--tune_manifest="data/manifest.dev-clean" \
--mean_std_path="data/mean_std.npz" \
--vocab_path="${MAIN_ROOT}/models/librispeech/vocab.txt" \
--model_path="${MAIN_ROOT}/models/librispeech" \
--lang_model_path="${MAIN_ROOT}/models/lm/common_crawl_00.prune01111.trie.klm" \
--error_rate_type="wer" \
--specgram_type="linear"

if [ $? -ne 0 ]; then
    echo "Failed in tuning!"
    exit 1
fi


exit 0