Python OcclusionAwareGenerator.load_state_dict示例

示例#1

def load_checkpoints(config_path, checkpoint_path, cpu=False):

    with open(config_path) as f:
        config = yaml.load(f)

    generator = OcclusionAwareGenerator(**config['model_params']['generator_params'],
                                        **config['model_params']['common_params'])
    if not cpu:
        generator.cuda()

    kp_detector = KPDetector(**config['model_params']['kp_detector_params'],
                             **config['model_params']['common_params'])
    if not cpu:
        kp_detector.cuda()
    
    if cpu:
        checkpoint = torch.load(checkpoint_path, map_location=torch.device('cpu'))
    else:
        checkpoint = torch.load(checkpoint_path)
 
    generator.load_state_dict(checkpoint['generator'])
    kp_detector.load_state_dict(checkpoint['kp_detector'])
    
    if not cpu:
        generator = DataParallelWithCallback(generator)
        kp_detector = DataParallelWithCallback(kp_detector)

    generator.eval()
    kp_detector.eval()
    
    return generator, kp_detector

示例#2

文件： process_task.py 项目： kibernetika-ai/first-order-model

def load_checkpoints(config_path, checkpoint_path, cpu=False):
    with open(config_path) as f:
        config = yaml.load(f)

    generator = OcclusionAwareGenerator(
        **config["model_params"]["generator_params"],
        **config["model_params"]["common_params"],
    )
    if cpu:
        generator.cpu()
    else:
        generator.cuda()

    kp_detector = KPDetector(
        **config["model_params"]["kp_detector_params"],
        **config["model_params"]["common_params"],
    )
    if cpu:
        kp_detector.cpu()
    else:
        kp_detector.cuda()

    checkpoint = torch.load(checkpoint_path, map_location="cpu" if cpu else None)
    generator.load_state_dict(checkpoint["generator"])
    kp_detector.load_state_dict(checkpoint["kp_detector"])

    generator = DataParallelWithCallback(generator)
    kp_detector = DataParallelWithCallback(kp_detector)

    generator.eval()
    kp_detector.eval()

    return generator, kp_detector

示例#3

def load_checkpoints(config_path, checkpoint_path, device='cuda'):

    with open(config_path) as f:
        config = yaml.load(f)

    generator = OcclusionAwareGenerator(
        **config['model_params']['generator_params'],
        **config['model_params']['common_params'])
    generator.to(device)

    kp_detector = KPDetector(**config['model_params']['kp_detector_params'],
                             **config['model_params']['common_params'])
    kp_detector.to(device)

    checkpoint = torch.load(checkpoint_path, map_location=device)
    generator.load_state_dict(checkpoint['generator'])
    kp_detector.load_state_dict(checkpoint['kp_detector'])

    generator = DataParallelWithCallback(generator)
    kp_detector = DataParallelWithCallback(kp_detector)

    generator.eval()
    kp_detector.eval()

    return generator, kp_detector

示例#4

文件： cam_fomm.py 项目： dbandrews/avatarify

def load_checkpoints(config_path, checkpoint_path, device="cuda"):

    with open(config_path) as f:
        config = yaml.load(f, Loader=yaml.FullLoader)

    generator = OcclusionAwareGenerator(
        **config["model_params"]["generator_params"],
        **config["model_params"]["common_params"],
    )
    generator.to(device)

    kp_detector = KPDetector(
        **config["model_params"]["kp_detector_params"],
        **config["model_params"]["common_params"],
    )
    kp_detector.to(device)

    checkpoint = torch.load(checkpoint_path, map_location=device)
    generator.load_state_dict(checkpoint["generator"])
    kp_detector.load_state_dict(checkpoint["kp_detector"])

    generator = DataParallelWithCallback(generator)
    kp_detector = DataParallelWithCallback(kp_detector)

    generator.eval()
    kp_detector.eval()

    return generator, kp_detector