本文整理汇总了Python中model.generate_model方法的典型用法代码示例。如果您正苦于以下问题：Python model.generate_model方法的具体用法？Python model.generate_model怎么用？Python model.generate_model使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类model的用法示例。
在下文中一共展示了model.generate_model方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: load_models
# 需要导入模块: import model [as 别名]
# 或者: from model import generate_model [as 别名]
def load_models(opt):
opt.resume_path = opt.resume_path_clf
opt.pretrain_path = opt.pretrain_path_clf
opt.sample_duration = opt.sample_duration_clf
opt.model = opt.model_clf
opt.model_depth = opt.model_depth_clf
opt.width_mult = opt.width_mult_clf
opt.modality = opt.modality_clf
opt.resnet_shortcut = opt.resnet_shortcut_clf
opt.n_classes = opt.n_classes_clf
opt.n_finetune_classes = opt.n_finetune_classes_clf
if opt.root_path != '':
opt.video_path = os.path.join(opt.root_path, opt.video_path)
opt.annotation_path = os.path.join(opt.root_path, opt.annotation_path)
opt.result_path = os.path.join(opt.root_path, opt.result_path)
if opt.resume_path:
opt.resume_path = os.path.join(opt.root_path, opt.resume_path)
if opt.pretrain_path:
opt.pretrain_path = os.path.join(opt.root_path, opt.pretrain_path)
opt.scales = [opt.initial_scale]
for i in range(1, opt.n_scales):
opt.scales.append(opt.scales[-1] * opt.scale_step)
opt.arch = '{}'.format(opt.model)
opt.mean = get_mean(opt.norm_value)
opt.std = get_std(opt.norm_value)
print(opt)
with open(os.path.join(opt.result_path, 'opts_clf.json'), 'w') as opt_file:
json.dump(vars(opt), opt_file)
torch.manual_seed(opt.manual_seed)
classifier, parameters = generate_model(opt)
if opt.resume_path:
print('loading checkpoint {}'.format(opt.resume_path))
checkpoint = torch.load(opt.resume_path)
# assert opt.arch == checkpoint['arch']
classifier.load_state_dict(checkpoint['state_dict'])
print('Model 2 \n', classifier)
pytorch_total_params = sum(p.numel() for p in classifier.parameters() if
p.requires_grad)
print("Total number of trainable parameters: ", pytorch_total_params)
return classifier