Profile Job Results
Jobs
jygzz0vog
Results Ready
Name
detr_resnet50
Target Device
- SA8650 (Proxy)
- Android 13
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image: float32[1, 480, 480, 3]Completion Time
8/11/2024, 8:36:56 AM
Versions
- TensorFlow Lite: 2.16.1
- QNN TfLite Delegate: v2.24.0.240626131148_96320
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2024.08.01.0
Estimated Inference Time
21.0 ms
Estimated Peak Memory Usage
2 - 10 MB
Compute Units
NPU
787
GPU
1
| Stage | Time | Memory |
|---|---|---|
First App Load | 9.53 s | 688-689 MB |
Subsequent App Load | 374 ms | 85-317 MB |
Inference | 21.0 ms | 2-10 MB |
| TensorFlow Lite | Value |
|---|---|
| number_of_threads | 4 |
| QNN Delegate | Value |
|---|---|
| backend_type | kHtpBackend |
| log_level | kLogLevelWarn |
| htp_options.performance_mode | kHtpBurst |
| htp_options.precision | kHtpFp16 |
| htp_options.useConvHmx | true |
| GPUv2 Delegate | Value |
|---|---|
| inference_preference | TFLITE_GPU_INFERENCE_PREFERENCE_SUSTAINED_SPEED |
| inference_priority1 | TFLITE_GPU_INFERENCE_PRIORITY_MIN_LATENCY |
| inference_priority2 | TFLITE_GPU_INFERENCE_PRIORITY_MIN_MEMORY_USAGE |
| inference_priority3 | TFLITE_GPU_INFERENCE_PRIORITY_MAX_PRECISION |
Sign up to run this model on a hosted Qualcomm® device!
Run on device