import datasets.preprocess as preprocess
from utils import opts
if __name__ == '__main__':
config = opts.parse_opt()
preprocess.run_prepro(csv_folder=config.dataset_path,
output_folder=config.output_path,
sentence_limit=config.sentence_limit,
word_limit=config.word_limit,
min_word_count=config.min_word_count)
import numpy as np
import time
import os
from six.moves import cPickle
import utils.opts as opts
import models
from utils.dataloader import *
import torch.utils.tensorboard as td
import utils.eval_utils as eval_utils
import utils.utils as utils
from utils.rewards import init_cider_scorer, get_self_critical_reward, get_self_critical_cider_bleu_reward, init_bleu_scorer
opt = opts.parse_opt()
os.environ["CUDA_VISIBLE_DEVICES"] = opt.gpu_id
def train(opt):
opt.use_att = utils.if_use_att(opt.caption_model)
loader = DataLoader(opt)
opt.vocab_size = loader.vocab_size
opt.seq_length = loader.seq_length
td_summary_writer = td.writer.SummaryWriter(opt.ckpt_path)
infos = {
'iter': 0,
'epoch': 0,
'loader_state_dict': None,