advanced-ss_att-eval-1ckpt_finetune-with-decay-da.sh

#!/bin/bash

DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"

model_name="show_and_tell_advanced_model_attention_finetune_with_decay_da"
num_processes=1
gpu_fraction=1
device=0
model=ShowAndTellAdvancedModel

MODEL_DIR="${DIR}/model/${model_name}"
ckpt="avg-0"

# the script directory
VALIDATE_TFRECORD_FILE="${DIR}/data/Newloc_TFRecord_data/validate*.tfrecord"
VALIDATE_REFERENCE_FILE="${DIR}/data/ai_challenger_caption_validation_20170910/reference.json"


CHECKPOINT_PATH="${MODEL_DIR}/model.ckpt-$ckpt"
OUTPUT_DIR="${MODEL_DIR}/model.ckpt-${ckpt}.eval"

mkdir $OUTPUT_DIR

cd ${DIR}/im2txt

if [ ! -f ${OUTPUT_DIR}/out.json ]; then
  CUDA_VISIBLE_DEVICES=$device python batch_inference.py \
    --input_file_pattern="$VALIDATE_TFRECORD_FILE" \
    --checkpoint_path=${CHECKPOINT_PATH} \
    --vocab_file=${DIR}/data/word_counts.txt \
    --output=${OUTPUT_DIR}/out.json \
    --reader=ImageCaptionTestReader \
    --batch_size=10 \
    --model=${model} \
    --inception_return_tuple=True \
    --use_attention_wrapper=True \
    --attention_mechanism=BahdanauAttention \
    --num_lstm_layers=1 \
    --support_ingraph=True \
    --gpu_memory_fraction=$gpu_fraction
  echo output saved to ${OUTPUT_DIR}/out.json
fi

if [ ! -f ${OUTPUT_DIR}/out.eval ]; then
  python ${DIR}/tools/eval/run_evaluations.py --submit ${OUTPUT_DIR}/out.json --ref $VALIDATE_REFERENCE_FILE | tee ${OUTPUT_DIR}/out.eval | grep ^Eval
  echo eval result saved to ${OUTPUT_DIR}/out.eval
fi