text: base=./mount
  dir=$base/temp/ai2018/sentiment/tfrecords/$SRC
  
  fold=0
  if [ $# == 1 ];
    then fold=$1
  fi 
  if [ $FOLD ];
    then fold=$FOLD
  fi 
  
  model_dir=$base/temp/ai2018/sentiment/model/v1.1/$fold/$SRC/torch.fastai/
  num_epochs=30
  
  mkdir -p $model_dir/epoch 
  cp $dir/vocab* $model_dir
  cp $dir/vocab* $model_dir/epoch
  
  exe=./torch-train.py 
  if [ "$INFER" = "1"  ]; 
    then echo "INFER MODE" 
    exe=./infer.py 
    model_dir=$1
    fold=0
  fi
  
  if [ "$INFER" = "2"  ]; 
    then echo "VALID MODE" 
    exe=./infer.py 
    model_dir=$1
    fold=0
  fi
  
  python $exe \
          --use_label_rnn=0 \
          --hop=1 \
          --att_combiner='sfu' \
          --rnn_no_padding=1 \
          --model=Fastai \
          --use_self_match=1 \
          --label_emb_height=20 \
          --fold=$fold \
          --use_label_att=0 \
          --use_self_match=0 \
          --vocab $dir/vocab.txt \
          --model_dir=$model_dir \
          --train_input=$dir/train/'*,' \
          --test_input=$dir/test/'*,' \
          --info_path=$dir/info.pkl \
          --emb_dim 300 \
          --word_embedding_file=$dir/emb.npy \
          --finetune_word_embedding=1 \
          --batch_size 32 \
          --encoder_type=rnn \
          --keep_prob=0.7 \
          --num_layers=2 \
          --rnn_hidden_size=200 \
          --encoder_output_method=topk,att \
          --eval_interval_steps 1000 \
          --metric_eval_interval_steps 1000 \
          --save_interval_steps 1000 \
          --save_interval_epochs=1 \
          --valid_interval_epochs=1 \
          --inference_interval_epochs=1 \
          --freeze_graph=1 \
          --optimizer=adam \
          --learning_rate=0.002 \
          --decay_target=loss \
          --decay_patience=1 \
          --decay_factor=0.8 \
          --num_epochs=$num_epochs \
  
  