1599 - qualcommrb3gen2 tflite

1599 - qualcommrb3gen2 tflite

Summary: Pipeline failed, error.log is filled, and a not valid report was generated.

Model Details

  • model name : movenet_singlepose_lightning_192_int8.tflite
  • model url : Download here

Logs Details

user.log
INFO: Created TensorFlow Lite delegate for GPU. 
W/Adreno-GSL (62920,62920): <os_lib_map:1488>:   os_lib_map error: libadreno_app_profiles.so: cannot open shared object file: No such file or directory, on 'libadreno_app_profiles.so' 
W/Adreno-CB (62920,62920): <cl_app_profiles_initialize:104>: Failed to load the app profiles library libadreno_app_profiles.so! 
INFO: Initialized OpenCL-based API. 
INFO: Created 1 GPU delegate kernels. 
INFO: Created TensorFlow Lite XNNPACK delegate for CPU. 
error.log
ERROR: Following operations are not supported by GPU delegate:
ARG_MAX: Operation is not supported.
CAST: Not supported Cast case. Input type: UINT8 and output type: FLOAT32
CONCATENATION: OP is supported, but tensor type/shape isn't compatible.
FLOOR_DIV: OP is supported, but tensor type/shape isn't compatible.
GATHER_ND: Operation is not supported.
MUL: OP is supported, but tensor type/shape isn't compatible.
PACK: OP is supported, but tensor type/shape isn't compatible.
RESHAPE: OP is supported, but tensor type/shape isn't compatible.
SUB: OP is supported, but tensor type/shape isn't compatible.
100 operations will run on the GPU, and the remaining 57 operations will run on the CPU.

Report Details

report.json
{
  "GFLOPs": null,
  "accuracy": null,
  "ambiant_temperature": null,
  "benchmark_type": "Type1",
  "date": "2025-03-10 07:14:29",
  "energy_efficiency": null,
  "flash_size": 116249661440,
  "flash_usage": 0.0024901921985330815,
  "inference_engine": "tflite",
  "inference_latency": {
    "latency_per_layers": [
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        "layer_name": " [Cast]:0",
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        "std": 0.0
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        "layer_name": " Delegate/quantize_and_dequantize 0 -> subtract 1 -> quantize_and_dequantize 142 -> mul 2 -> quantize_and_dequantize 143 -> subtract 3 -> quantize_and_dequantize 144:0",
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        "mean": 32.921600000000005,
        "min": 32.921600000000005,
        "std": 0.0
      },
      {
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        "std": 0.0
      },
      {
        "layer_name": " Delegate/depthwise_convolution 6 -> relu 7 -> quantize_and_dequantize 146:2",
        "max": 112.98,
        "mean": 112.98,
        "min": 112.98,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 8 -> quantize_and_dequantize 147:3",
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        "mean": 64.3137,
        "min": 64.3137,
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      {
        "layer_name": " Delegate/convolution_2d 9 -> relu 10 -> quantize_and_dequantize 148:4",
        "max": 185.76500000000001,
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      {
        "layer_name": " Delegate/depthwise_convolution 11 -> relu 12 -> quantize_and_dequantize 149:5",
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        "layer_name": " Delegate/depthwise_convolution 16 -> relu 17 -> quantize_and_dequantize 152:8",
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        "layer_name": " Delegate/convolution_2d 18 -> quantize_and_dequantize 153 -> add 19 -> quantize_and_dequantize 154:9",
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