Load model by from_pretrained() then model.train()?
I got one question about torch.
I load pre-training model like:
model_name = &quot;bert-base-uncased&quot;
model = BertTokenizer.from_pretrained(model_name)
and I read  To train the model, you should first set it back in training mode with model.train().
but I don't understand how it does work. when I read document of from_pretrained(), there isn't any explanation about train().
How it works?

.train() is a method of torch.nn.Module. It notifies the module to switch to the training mode, see documentation. What exactly happens under the hood is up to the actual Module, in many modules it doesn't change anything, so without knowing your network we cannot say what examctly happens. But for instance in torch.nn.BatchNormNd it has an effect.
