ACOM crystal.orientation_plan GPU Memory Management

Describe the bug
When creating an orientation plan within a crystal class with CUDA set to True, GPU memory is continuously filled. I have not been able to figure out a way to dump the GPU memory short of shutting down the kernel and restarting it. Thus when working with multiple crystal classes and detailed orientation plans, GPU resource management is a cumbersome.

To Reproduce
-Build crystal classes (I am doing so from cif files)
-Calculate structure factors
-Generate detailed orientation plans (with small angle_step_zone_axis values)
-If that does not fill up the GPU memory, I also ran into the out of memory error when matching experimental patterns to the generated plans

Expected behavior
-Maybe implement some kind of batching system where GPU can dump to system memory
-Implement way to forcibly clear GPU memory so parameters in generating orientation plan can be tweaked so as to not fill up GPU memory
-Dump GPU memory to system memory after orientation plan has been generated

py4DSTEM version
0.14.9
Python version
python3.11
Operating system
Linux on an HPC cluster
Interfacing with JupyterLab

GPU
If GPU related please provide:

• CUDA driver - 535.154.05
• Cuda Version 12.2
• Cupy Version - 13.0.0

Screenshots

Additional context
Screenshots show extreme example of an orientation plan for illustration of issue

No files or tests are named. Reproduce the CUDA-enabled orientation-plan and experimental-pattern matching workflows described in the issue, using the reported Python, py4DSTEM, CUDA, and CuPy versions, then trace where GPU memory remains allocated. Done means repeated plans and matching runs no longer exhaust GPU memory and a documented cleanup or batching behavior is covered by tests.