StateTransformer / README.md
qaihm-bot's picture
v0.62.2
b2be913 verified
|
Raw
History Blame Contribute Delete
4.95 kB
---
library_name: pytorch
license: mit
tags:
- bu_auto
- android
pipeline_tag: other
---
![](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/statetransformer/web-assets/model_demo.png)
# StateTransformer: Optimized for Qualcomm Devices
StateTransformer is a transformer-based model designed for trajectory prediction in self-driving scenarios. It integrates rasterized map data, agent context, and temporal dynamics to generate accurate future trajectories.
This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/statetransformer) library to export with custom configurations. More details on model performance across various devices, can be found [here](#performance-summary).
Qualcomm AI Hub Models uses [Qualcomm AI Hub Workbench](https://workbench.aihub.qualcomm.com) to compile, profile, and evaluate this model. [Sign up](https://myaccount.qualcomm.com/signup) to run these models on a hosted Qualcomm® device.
## Getting Started
There are two ways to deploy this model on your device:
### Option 1: Download Pre-Exported Models
Below are pre-exported model assets ready for deployment.
| Runtime | Precision | Chipset | SDK Versions | Download |
|---|---|---|---|---|
| ONNX | float | Universal | QAIRT 2.45, ONNX Runtime 1.27.1 | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/statetransformer/releases/v0.62.2/statetransformer-onnx-float.zip)
| TFLITE | float | Universal | | [Download](https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/statetransformer/releases/v0.62.2/statetransformer-tflite-float.zip)
For more device-specific assets and performance metrics, visit **[StateTransformer on Qualcomm® AI Hub](https://aihub.qualcomm.com/models/statetransformer)**.
### Option 2: Export with Custom Configurations
Use the [Qualcomm® AI Hub Models](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/statetransformer) Python library to compile and export the model with your own:
- Custom weights (e.g., fine-tuned checkpoints)
- Custom input shapes
- Target device and runtime configurations
This option is ideal if you need to customize the model beyond the default configuration provided here.
See our repository for [StateTransformer on GitHub](https://github.com/qualcomm/ai-hub-models/blob/v0.62.2/src/qai_hub_models/models/statetransformer) for usage instructions.
## Model Details
**Model Type:** Model_use_case.driver_assistance
**Model Stats:**
- Input resolution: 1x224x224x58, 1x224x224x58, 1x4x7
- Model checkpoint: pretrained-mixtral-small
- Model size (float): 348 MB
- Number of parameters: 90.7M
## Performance Summary
| Model | Runtime | Precision | Chipset | Inference Time (ms) | Peak Memory Range (MB) | Primary Compute Unit
|---|---|---|---|---|---|---
| StateTransformer | ONNX | float | Snapdragon® 8 Gen 3 Mobile | 291.136 ms | 200 - 5703 MB | NPU
| StateTransformer | ONNX | float | Qualcomm® Dragonwing™ IQ-8275 | 349.435 ms | 100 - 142 MB | NPU
| StateTransformer | ONNX | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 373.184 ms | 196 - 200 MB | NPU
| StateTransformer | ONNX | float | Qualcomm® Dragonwing™ IQ-9075 | 315.741 ms | 106 - 147 MB | NPU
| StateTransformer | ONNX | float | Qualcomm® Dragonwing™ Q-8750 | 236.364 ms | 168 - 5681 MB | NPU
| StateTransformer | ONNX | float | Snapdragon® 8 Elite Mobile | 236.364 ms | 168 - 5681 MB | NPU
| StateTransformer | ONNX | float | Snapdragon® 8 Elite Gen 5 Mobile | 212.445 ms | 183 - 5749 MB | NPU
| StateTransformer | TFLITE | float | Qualcomm® Dragonwing™ IQ-8275 | 1528.046 ms | 294 - 816 MB | CPU
| StateTransformer | TFLITE | float | Qualcomm® Dragonwing™ QCS8550 (Proxy) | 1115.87 ms | 241 - 394 MB | CPU
| StateTransformer | TFLITE | float | Qualcomm® SA8650P | 792.928 ms | 452 - 465 MB | CPU
| StateTransformer | TFLITE | float | Qualcomm® SA8255P | 792.928 ms | 452 - 465 MB | CPU
| StateTransformer | TFLITE | float | Qualcomm® QCS8450 | 808.833 ms | 450 - 470 MB | CPU
| StateTransformer | TFLITE | float | Qualcomm® Dragonwing™ IQ-9075 | 1309.723 ms | 293 - 815 MB | CPU
| StateTransformer | TFLITE | float | Qualcomm® Dragonwing™ Q-8750 | 645.781 ms | 267 - 4157 MB | CPU
| StateTransformer | TFLITE | float | Snapdragon® 8 Elite Mobile | 645.781 ms | 267 - 4157 MB | CPU
## License
* The license for the original implementation of StateTransformer can be found
[here](https://github.com/Tsinghua-MARS-Lab/StateTransformer/blob/main/setup.py).
## Community
* Join [our AI Hub Slack community](https://aihub.qualcomm.com/community/slack) to collaborate, post questions and learn more about on-device AI.
* For questions or feedback please [reach out to us](mailto:ai-hub-support@qti.qualcomm.com).