The eval function changes behaviour of dropout (no nodes are dropped) and batchnorm (use global statistics rather than batch statistics), during testing. This is different from how they behave during training.
For all other operations/layers, the train and test outputs are the same. http://pytorch.org/docs/nn.html#torch.nn.Module.eval 11
The network in the example you linked does not have these layers which is why I suspect they did not call the eval function. Calling the train and eval functions won’t affect the model output. For models which have dropout/batchnorm layers, its quite imperative that you call the eval function before training.