inceptionv3.to(device) # 'cuda'
inceptionv3.eval()

inceptionv3.requires_grad_ = False

output = []

for batch in loader:
    torch.cuda.empty_cache()
    out = inceptionv3(batch[0].to(device))
    output.append(out.detach().cpu().numpy())
    del out

Somehow, this still winds up with a memory error. Adjusting batch size makes no difference.
Let me add that I’m using the facenet modification of inception v3, and there might be some error internal to the way the model was modified for the facenet data.