在这里加载模型的性能似乎正确吗？
Total time: 5.4545 s
Function: load_model at line 81
Line # Hits Time Per Hit % Time Line Contents
==============================================================
81 @profile
82 def load_model(dirname, device):
82 """ load model from disk """
83 1 90.0 90.0 0.0 device = torch.device(device)
84 1 26.0 26.0 0.0 modelfile = os.path.join(dirname, 'model.py')
85 1 7.0 7.0 0.0 weights = os.path.join(dirname, 'weights_%s.tar' % weights)
86 1 5379756.0 5379756.0 98.6 model = torch.load(modelfile, map_location=device)
87 1 72966.0 72966.0 1.3 model.load_state_dict(torch.load(weights, map_location=device))
88 1 1648.0 1648.0 0.0 model.eval()
89 1 1.0 1.0 0.0 return model
在第86行加载26MB模型的最初调用比在87加载26MB检查点的速度慢约100倍，而5.45秒要比我期望的要长得多吗？
我正在使用pytorch 1.2和device="cuda"，并确认了与1.3.1相同的性能。添加通话以进行同步可确认实际上所有时间都花在了torch.load中。
86 1 5395545.0 5395545.0 98.6 model = torch.load(modelfile, map_location=device)
87 1 76.0 76.0 0.0 torch.cuda.synchronize(device=device)
88 1 72403.0 72403.0 1.3 model.load_state_dict(torch.load(weights, map_location=device))
89 1 52.0 52.0 0.0 torch.cuda.synchronize(device=device)
90 1 1640.0 1640.0 0.0 model.eval()
91 1 21.0 21.0 0.0 torch.cuda.synchronize(device=device)
我在这里做错了吗？或者这是典型的吗？