main_test.py

import os
import sys
import pprint
import random
import time
import tqdm
import logging
import argparse
import numpy as np

import torch
import torch.nn as nn
import torch.multiprocessing as mp
import torch.distributed as dist

import losses
import models
import datasets
import lib.utils as utils
from lib.utils import AverageMeter
from optimizer.optimizer import Optimizer
from evaluation.evaler import Evaler
from scorer.scorer import Scorer
from lib.config import cfg, cfg_from_file
from fvcore.common.checkpoint import Checkpointer


class CaptionCheckpointer(Checkpointer):
    def _load_file(self, filename):
        loaded = super()._load_file(filename)  # load native pth checkpoint
        if "model" not in loaded:
            loaded = {"model": loaded}
        return loaded


class Tester(object):
    def __init__(self, args):
        super(Tester, self).__init__()
        self.args = args
        self.device = torch.device("cuda")

        self.setup_logging()
        self.setup_network()
        self.evaler = Evaler(eval_ids=cfg.DATA_LOADER.TEST_ID,
                             gv_feat=cfg.DATA_LOADER.TEST_GV_FEAT,
                             att_feats=cfg.DATA_LOADER.TEST_ATT_FEATS,
                             eval_annfile=cfg.INFERENCE.TEST_ANNFILE)

    def setup_logging(self):
        self.logger = logging.getLogger(cfg.LOGGER_NAME)
        self.logger.setLevel(logging.INFO)

        ch = logging.StreamHandler(stream=sys.stdout)
        ch.setLevel(logging.INFO)
        formatter = logging.Formatter(
            "[%(levelname)s: %(asctime)s] %(message)s")
        ch.setFormatter(formatter)
        self.logger.addHandler(ch)

        if not os.path.exists(cfg.ROOT_DIR):
            os.makedirs(cfg.ROOT_DIR)

        fh = logging.FileHandler(
            os.path.join(cfg.ROOT_DIR, cfg.LOGGER_NAME + '.txt'))
        fh.setLevel(logging.INFO)
        fh.setFormatter(formatter)
        self.logger.addHandler(fh)

    def setup_network(self):
        model = models.create(cfg.MODEL.TYPE)
        self.model = model.cuda()
        self.checkpointer = CaptionCheckpointer(
            self.model, os.path.join(cfg.ROOT_DIR, "snapshot"))

        if self.args.resume > 0:
            self.checkpointer.load(
                self.snapshot_path("caption_model", self.args.resume))

    def eval(self, epoch):
        res = self.evaler(self.model, 'test_' + str(epoch), 2)
        self.logger.info('######## Epoch ' + str(epoch) + ' ########')
        self.logger.info(str(res))

    def snapshot_path(self, name, epoch):
        snapshot_folder = os.path.join(cfg.ROOT_DIR, 'snapshot')
        return os.path.join(snapshot_folder, name + "_" + str(epoch) + ".pth")


def parse_args():
    """
    Parse input arguments
    """
    parser = argparse.ArgumentParser(description='Image Captioning')
    parser.add_argument('--folder', dest='folder', default=None, type=str)
    parser.add_argument("--resume", type=int, default=-1)

    if len(sys.argv) == 1:
        parser.print_help()
        sys.exit(1)

    args = parser.parse_args()
    return args


if __name__ == '__main__':
    args = parse_args()
    print('Called with args:')
    print(args)

    if args.folder is not None:
        cfg_from_file(os.path.join(args.folder, 'config.yml'))
    cfg.ROOT_DIR = args.folder

    tester = Tester(args)
    tester.eval(args.resume)