Profile Job Results
Jobs
jp4lmx125
Results Ready
Name
squeezenet1_1_quantized
Target Device
- SA8650 (Proxy)
- Android 13
- Qualcomm® SA8650P
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
image_tensor: uint8[1, 224, 224, 3]Completion Time
11/26/2024, 12:49:41 PM
Versions
- TensorFlow Lite: 2.17.0
- QNN TfLite Delegate: v2.28.2.241116104011_103376
- Android: 13 (TP1A.220624.014)
- AI Hub: aihub-2024.11.22.0
Estimated Inference Time
204 μs
Estimated Peak Memory Usage
0 ‑ 77 MB
Compute Units
NPU
43
| Stage | Time | Memory |
|---|---|---|
First App Load | 385 ms | 21‑22 MB |
Subsequent App Load | 298 ms | 28‑96 MB |
Inference | 204 μs | 0‑77 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 |
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