Hi,
(10, 2048, 1, 1) means that you have a batch of 10 images. with a 2048 channels and height and width of size 1.
It is a very weird image , but this is the output you get from the last convolutions/spatial pooling layers.
To now go to Linear layers, you want a 2D Tensor of shape (batch_size x nb_features). In this case, You want: out.view(-1, 2048) in your case.
If you want 1000 outputs in the end, you need to add other Linear layers that will do this transformation (nn.Linear(2048, 1000) for example).