#! /usr/bin/env bash

# train model
# if you wish to resume from an exists model, uncomment --init_from_pretrained_model
export FLAGS_sync_nccl_allreduce=0
CUDA_VISIBLE_DEVICES=0,1,2,3 \
python3 -u ${MAIN_ROOT}/train.py \
--batch_size=4 \
--num_epoch=20 \
--num_conv_layers=2 \
--num_rnn_layers=3 \
--rnn_layer_size=2048 \
--num_iter_print=1 \
--save_epoch=1 \
--num_samples=64 \
--learning_rate=1e-5 \
--max_duration=27.0 \
--min_duration=0.0 \
--test_off=False \
--use_sortagrad=True \
--use_gru=False \
--use_gpu=True \
--is_local=True \
--share_rnn_weights=True \
--train_manifest="data/manifest.tiny" \
--dev_manifest="data/manifest.tiny" \
--mean_std_path="data/mean_std.npz" \
--vocab_path="data/vocab.txt" \
--output_model_dir="./checkpoints/" \
--augment_conf_path="${MAIN_ROOT}/conf/augmentation.config" \
--specgram_type="linear" \
--shuffle_method="batch_shuffle_clipped" \

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


exit 0