Model Explorer is a visualization tool for inspecting neural network structures and execution graphs. Arm provides a VGF adapter for Model Explorer, allowing you to visualize .vgf models created from your training and export pipeline.
This lets you inspect model architecture, tensor shapes, and graph connectivity before deployment. This can be a powerful way to debug and understand your exported neural graphics models.
The VGF adapter extends Model Explorer to support .vgf files exported from the Model Gym toolchain.
Run:
pip install vgf-adapter-model-explorer
The VGF adapter model explorer source code is available on GitHub .
The next step is to make sure the Model Explorer itself is installed. Use pip to set it up:
pip install torch ai-edge-model-explorer
Once installed, launch the explorer with the VGF adapter:
model-explorer --extensions=vgf_adapter_model_explorer
Use the file browser to open the .vgf model exported earlier in your training workflow.
Through this Learning Path, you’ve learned what neural graphics is and why it matters for game performance. You’ve stepped through the process of training and evaluating an NSS model using PyTorch and the Model Gym, and seen how to export that model into VGF (.vgf) for real-time deployment. You’ve also explored how to visualize and inspect the model’s structure using Model Explorer. You can now explore the Model Training Gym repository for deeper integration and to keep building your skills.