High memory usage in inference.

[toomanycats]

I've found that when running the Singularity container version of the DISCO pipeline, we needed 32 GB of memory for our
Sun Grid Engine to run the pipeline.

I made a sandboxed version of the sing container and added a cache clear on a hunch. This appears to have worked.
Still double checking.

def inference(T1_path, b0_d_path, model, device):
+    torch.cuda.empty_cache()
    # Eval mode
     model.eval()

[toomanycats]

UPDATE:

The cache clearing didn't help. Plus the call is probably wrong since this the device is not cuda.
Attempting another idea, to explicitly use float16 datatype rather than what we think is the default, float32.