Failing to load the GPU-trained model onto CPU-machine
What is your question?
Hi, I cannot load neither model nor checkpoint from GPU onto CPU machine.
I followed the docs but the problem still remains. How can I resolve this issue?
Please follow the code sections below and its corresponding error messages.
Code
m_ae_model = LitAE.load_from_checkpoint(r'Path\version_1_load.ckpt', in_out_size, z_size)
TypeError: 'tuple' object is not callable
(in_out_size is a tuple, image dimensions for convolutional operations, whereas z_size is the latent variable dimension)
I also tried loading ".pt" model by placing it onto the CPU using map_location.
Code
location = torch.device('cpu')
m_ae_model = torch.load("m_ae_model.pt", map_location=location)
AttributeError: 'Trainer' object has no attribute '_enable_pl_optimizer'

What have you tried?
Saving GPU-trained model onto CPU (by model.to('CPU')), loading checkpoints.
What's your environment?

OS: Win (both machines)
Packaging pip
Version 1.1.3