PyTorch中，关于model.eval()和torch.no_grad()

• 一直对于model.eval()和torch.no_grad()有些疑惑
• 之前看博客说，只用torch.no_grad()即可
• 但是今天查资料，发现不是这样，而是两者都用，因为两者有着不同的作用
• 引用stackoverflow:

Use both. They do different things, and have different scopes.
with torch.no_grad： disables tracking of gradients in autograd.
model.eval()： changes the forward() behaviour of the module it is called upon. eg, it disables dropout and has batch norm use the entire population statistics