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test.py
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test.py
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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_round import Evaler
from scorer.scorer import Scorer
from lib.config import cfg, cfg_from_file
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):
##### for fc conv module
model = models.create('XLAN_fc_group')
self.model=model.cuda()
def eval(self, epoch):
epoch0=20
for i in range(30):
print('Now is in the round: [%d]' %(i+epoch0))
epoch=epoch0 + i*1
## for multiple gpus
# pretrained_dict=torch.load(self.snapshot_path("caption_model", epoch))
# net_dict=self.model.state_dict()
# for key, value in pretrained_dict.items():
# net_dict[key[7:]]=value
# net_dict.update(net_dict)
# self.model.load_state_dict(net_dict)
## for single gpu
self.model.load_state_dict(torch.load(self.snapshot_path("caption_model", epoch),map_location=lambda storage, loc: storage))
res = self.evaler(self.model, 'test_' + str(epoch))
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='./experiments/xlan', type=str)
parser.add_argument("--resume", type=int, default=-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)