Python pretrainedmodels.resnet152() Examples

The following are 3 code examples of pretrainedmodels.resnet152(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module pretrainedmodels , or try the search function .
Example #1
Source File: finetune_cnn.py    From video-caption.pytorch with MIT License 5 votes vote down vote up 
def main(args):
    global C, H, W
    coco_labels = json.load(open(args.coco_labels))
    num_classes = coco_labels['num_classes']
    if args.model == 'inception_v3':
        C, H, W = 3, 299, 299
        model = pretrainedmodels.inceptionv3(pretrained='imagenet')

    elif args.model == 'resnet152':
        C, H, W = 3, 224, 224
        model = pretrainedmodels.resnet152(pretrained='imagenet')

    elif args.model == 'inception_v4':
        C, H, W = 3, 299, 299
        model = pretrainedmodels.inceptionv4(
            num_classes=1000, pretrained='imagenet')

    else:
        print("doesn't support %s" % (args['model']))

    load_image_fn = utils.LoadTransformImage(model)
    dim_feats = model.last_linear.in_features
    model = MILModel(model, dim_feats, num_classes)
    model = model.cuda()
    dataset = CocoDataset(coco_labels)
    dataloader = DataLoader(
        dataset, batch_size=args.batch_size, shuffle=True)
    optimizer = optim.Adam(
        model.parameters(), lr=args.learning_rate, weight_decay=args.weight_decay)
    exp_lr_scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=args.learning_rate_decay_every,
                                                 gamma=args.learning_rate_decay_rate)

    crit = nn.MultiLabelSoftMarginLoss()
    if not os.path.isdir(args.checkpoint_path):
        os.mkdir(args.checkpoint_path)
    train(dataloader, model, crit, optimizer,
          exp_lr_scheduler, load_image_fn, args)
Example #2
Source File: vid_feature_extractor.py    From OpenNMT-py with MIT License 5 votes vote down vote up 
def __init__(self):
        super(FeatureExtractor, self).__init__()
        self.model = pretrainedmodels.resnet152()
        self.FEAT_SIZE = 2048
Example #3
Source File: vid_feature_extractor.py    From OpenNMT-kpg-release with MIT License 5 votes vote down vote up 
def __init__(self):
        super(FeatureExtractor, self).__init__()
        self.model = pretrainedmodels.resnet152()
        self.FEAT_SIZE = 2048