Balamurali_M:

We use eval because we won’t be interested in updating the weight of the network.


My understanding is that .eval() is to tell the network to disable dropout and batchnorm layers, where as the torch.no_grad() context is to disable gradient calculations. They are different concepts which happen to be used together during inference.
One possibility why .eval() is missing is because there are no dropout or batchnorm layers?