#!/bin/bash
# train.sh
#
# Usage:
# train.sh [model]
# Example:
# train.sh resnet50

#set -x

MODEL=${1}
HOSTML=`hostname`
LOGDIR="/home/jebba/devel/plantnet/RUNS/${MODEL}/${HOSTML}"
PLANTNETDIR="/home/jebba/devel/plantnet/PlantNet-300K"

mkdir -p ${LOGDIR}
echo "Training model: ${MODEL}" 1>>${LOGDIR}/${HOSTML}-${MODEL}.log
echo "`date`" 1>>${LOGDIR}/${HOSTML}-${MODEL}.log

cd ${PLANTNETDIR}

source env/bin/activate

echo "Run:"
echo "tail -fq ${LOGDIR}/${HOSTML}-${MODEL}.log ${LOGDIR}/${HOSTML}-${MODEL}.err"

time python main.py							\
	--lr=0.01							\
	--batch_size=32							\
	--mu=0.0001							\
	--n_epochs=30							\
	--epoch_decay 20 25						\
	--k 1 3 5 10							\
	--model=${MODEL}						\
	--pretrained							\
	--seed=4							\
	--image_size=256						\
	--crop_size=224							\
	--root=/srv/ml/plantnet/files/plantnet_300K/images		\
	--use_gpu=1							\
	--num_workers=`nproc`						\
	--save_name_xp=${MODEL}						\
	1>>${LOGDIR}/${HOSTML}-${MODEL}.log				\
	2>>${LOGDIR}/${HOSTML}-${MODEL}.err

mv results ${LOGDIR}
cp -p ~/bin/deepcrayon-plantnet-train ${LOGDIR}