Feature Request: Conditional Inclusion of CPU and GPU Versions in Plugin

[j05hau]

Issue Description

Currently, the plugin architecture does not dynamically include the necessary files for CPU and GPU support based on the environment it's running in. The codebase has the GPU include only. This setup requires manual intervention to switch between supported CPU and GPU versions, which is not ideal for a seamless development experience.

Proposed Solution

I propose that we enhance the plugin to use conditional statements that automatically determine the environment (CPU or GPU) and include the corresponding version dynamically. This way, the plugin can automatically detect the presence of directories such as dlls or lib within the respective CPU or GPU folders and act accordingly.

The expected structure would be:

• For CPU: ...\ThirdParty\LibTorch\Win64\CPU\include
• For GPU: ...\ThirdParty\LibTorch\Win64\GPU\include

The plugin should check for the existence of these directories and utilize the corresponding version based on what's available or specified as the target environment.

Benefits

• Automation: Eliminates the need for manual switching between CPU and GPU versions, enhancing developer productivity.
• Flexibility: Supports both CPU and GPU environments out of the box without additional setup other than adding the supported lib files found in Releases.
• Simplicity: Simplifies the project structure by having a single, unified branch that supports both environments.

Implementation Considerations

• We need to define the logic for detecting the environment and choosing the right directory.
• Ensure that the inclusion of these directories does not lead to conflicts or ambiguous references in the project.
• Testing should be comprehensive to cover both CPU and GPU environments.

Request for Comments

I invite contributors to provide feedback on this proposal, especially regarding:

• Potential challenges in implementing the proposed solution.
• Suggestions for an effective implementation approach.

[j05hau]

Automatically detecting supported architecture might not be the best method for all implementations and it could be better to implement a persistent flag in Build.cs or some other method that enables the end-user to decide what environment to use, such as a DefaultGame.ini config setting, so that computational resources can be effectively and individually managed by the user.

[j05hau]

It might also be worth considering to lean on CPU as the default environment rather than GPU, as the official PyTorch CPU lib files are easier to acquire and not everyone has an NVIDIA GPU but everyone of course has a CPU, but didn't include this in the issue directly as its more of a personal QoL feature.