Pytorchのエラーについて

前提・実現したいこと

python3.6.7でコードを動かした際に，pytorchでのエラーが抜け出せません．
何度かバージョンを変えて実行しましたが，pipにはtorchがあるのにモジュールがないとエラーが出ています．

発生している問題・エラーメッセージ

ImportError: No module named 'torch'

該当のソースコード

python3.6.7
1from __future__ import absolute_import
2from __future__ import division
3from __future__ import print_function
4
5import argparse
6import os
7import pprint
8
9import torch
10import torch.nn.parallel
11import torch.backends.cudnn as cudnn
12import torch.optim
13import torch.utils.data
14import torch.utils.data.distributed
15import torchvision.transforms as transforms
16
17import _init_paths
18from config import cfg
19from config import update_config
20from core.loss import JointsMSELoss
21from core.function import validate
22from utils.utils import create_logger
23
24import dataset
25import models
26
27def parse_args():
28    parser = argparse.ArgumentParser(description='Train keypoints network')
29    # general
30    parser.add_argument('--cfg',
31                        help='experiment configure file name',
32                        required=True,
33                        type=str)
34
35    parser.add_argument('opts',
36                        help="Modify config options using the command-line",
37                        default=None,
38                        nargs=argparse.REMAINDER)
39
40    parser.add_argument('--modelDir',
41                        help='model directory',
42                        type=str,
43                        default='')
44    parser.add_argument('--logDir',
45                        help='log directory',
46                        type=str,
47                        default='')
48    parser.add_argument('--dataDir',
49                        help='data directory',
50                        type=str,
51                        default='')
52    parser.add_argument('--prevModelDir',
53                        help='prev Model directory',
54                        type=str,
55                        default='')
56
57    args = parser.parse_args()
58    return args
59
60def main():
61    args = parse_args()
62    update_config(cfg, args)
63
64    logger, final_output_dir, tb_log_dir = create_logger(
65        cfg, args.cfg, 'valid')
66
67    logger.info(pprint.pformat(args))
68    logger.info(cfg)
69
70    # cudnn related setting
71    cudnn.benchmark = cfg.CUDNN.BENCHMARK
72    torch.backends.cudnn.deterministic = cfg.CUDNN.DETERMINISTIC
73    torch.backends.cudnn.enabled = cfg.CUDNN.ENABLED
74
75    model = eval('models.'+cfg.MODEL.NAME+'.get_pose_net')(
76        cfg, is_train=False
77    )
78
79    if cfg.TEST.MODEL_FILE:
80        logger.info('=> loading model from {}'.format(cfg.TEST.MODEL_FILE))
81        model.load_state_dict(torch.load(cfg.TEST.MODEL_FILE), strict=False)
82    else:
83        model_state_file = os.path.join(
84            final_output_dir, 'final_state.pth'
85        )
86        logger.info('=> loading model from {}'.format(model_state_file))
87        model.load_state_dict(torch.load(model_state_file))
88
89    model = torch.nn.DataParallel(model, device_ids=cfg.GPUS).cuda()
90
91    # define loss function (criterion) and optimizer
92    criterion = JointsMSELoss(
93        use_target_weight=cfg.LOSS.USE_TARGET_WEIGHT
94    ).cuda()
95
96    # Data loading code
97    normalize = transforms.Normalize(
98        mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
99    )
100    valid_dataset = eval('dataset.'+cfg.DATASET.DATASET)(
101        cfg, cfg.DATASET.ROOT, cfg.DATASET.TEST_SET, False,
102        transforms.Compose([
103            transforms.ToTensor(),
104            normalize,
105        ])
106    )
107    valid_loader = torch.utils.data.DataLoader(
108        valid_dataset,
109        batch_size=cfg.TEST.BATCH_SIZE_PER_GPU*len(cfg.GPUS),
110        shuffle=False,
111        num_workers=cfg.WORKERS,
112        pin_memory=True
113    )
114
115    # evaluate on validation set
116    validate(cfg, valid_loader, valid_dataset, model, criterion,
117             final_output_dir, tb_log_dir)
118
119
120if __name__ == '__main__':
121    main()