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Jobs
jz5we97m5
Results Ready
Name
controlnet_quantized_UNet_Quantized
Target Device
  • Samsung Galaxy S24
  • Android 14
  • Snapdragon® 8 Gen 3 | SM8650
Creator
ai-hub-support@qti.qualcomm.com
Target Model
Input Specs
input_1: float32[1, 64, 64, 4]
input_2: float32[1, 1280]
input_3: float32[1, 77, 768]
controlnet_downblock1: float32[1, 64, 64, 320]
controlnet_downblock2: float32[1, 64, 64, 320]
controlnet_downblock3: float32[1, 64, 64, 320]
controlnet_downblock4: float32[1, 32, 32, 320]
controlnet_downblock5: float32[1, 32, 32, 640]
controlnet_downblock6: float32[1, 32, 32, 640]
controlnet_downblock7: float32[1, 16, 16, 640]
controlnet_downblock8: float32[1, 16, 16, 1280]
controlnet_downblock9: float32[1, 16, 16, 1280]
controlnet_downblock10: float32[1, 8, 8, 1280]
controlnet_downblock11: float32[1, 8, 8, 1280]
controlnet_downblock12: float32[1, 8, 8, 1280]
controlnet_midblock: float32[1, 8, 8, 1280]
Completion Time
3/19/2024, 12:44:52 AM
Versions
  • QNN: v2.19.0.240124133650_81096
  • QNN Backend API: 5.19.0
  • QNN Core API: 2.13.0
  • Android: 14 (UP1A.231005.007)
  • AI Hub: aihub-2024.03.07.0
Estimated Inference Time
193 ms
Estimated Peak Memory Usage
0 - 1 GB
Compute Units
NPU
5434
StageTimeMemory
First App Load
479 ms2-10 MB
Subsequent App Load
504 ms1-10 MB
Inference
193 ms0-1 GB
QNNValue
context_options.htp_options.performance_modeBURST
default_graph_options.htp_options.precisionFLOAT16

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