Skip to content

124209 - qualcommrb3gen2 tflite

Summary: Pipeline succeeded and valid report was generated.

Model Details

  • model name : squeezenetv1.1_224_tfs_int8.tflite
  • model url : Download here

Logs Details

user.log
INFO: Created TensorFlow Lite delegate for GPU. 
W/Adreno-GSL (36730,36730): <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 (36730,36730): <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. 
error.log

Report Details

report.json
{
  "GFLOPs": null,
  "accuracy": null,
  "ambiant_temperature": null,
  "benchmark_type": "TYPE1",
  "date": "2026-04-14T22:15:25.",
  "energy_efficiency": null,
  "flash_size": 116249661440,
  "flash_usage": 0.000708798623405264,
  "inference_engine": "tflite",
  "inference_latency": {
    "latency_per_layers": [
      {
        "layer_name": " Delegate/quantize_and_dequantize 0:0",
        "max": 50.1605,
        "mean": 50.1605,
        "min": 50.1605,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 1 -> relu 2 -> quantize_and_dequantize 67:1",
        "max": 236.06199999999998,
        "mean": 236.06199999999998,
        "min": 236.06199999999998,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/pooling_2d 3 -> quantize_and_dequantize 68:2",
        "max": 214.63,
        "mean": 214.63,
        "min": 214.63,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 4 -> relu 5 -> quantize_and_dequantize 69:3",
        "max": 31.5185,
        "mean": 31.5185,
        "min": 31.5185,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 6 -> relu 7 -> quantize_and_dequantize 70:4",
        "max": 30.5432,
        "mean": 30.5432,
        "min": 30.5432,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 8 -> relu 9 -> quantize_and_dequantize 71:5",
        "max": 171.72799999999998,
        "mean": 171.72799999999998,
        "min": 171.72799999999998,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 10 -> quantize_and_dequantize 72:6",
        "max": 165.691,
        "mean": 165.691,
        "min": 165.691,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 11 -> relu 12 -> quantize_and_dequantize 73:7",
        "max": 82.6173,
        "mean": 82.6173,
        "min": 82.6173,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 13 -> relu 14 -> quantize_and_dequantize 74:8",
        "max": 29.296300000000002,
        "mean": 29.296300000000002,
        "min": 29.296300000000002,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 15 -> relu 16 -> quantize_and_dequantize 75:9",
        "max": 171.494,
        "mean": 171.494,
        "min": 171.494,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 17 -> quantize_and_dequantize 76:10",
        "max": 168.93800000000002,
        "mean": 168.93800000000002,
        "min": 168.93800000000002,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/pooling_2d 18 -> quantize_and_dequantize 77:11",
        "max": 122.02499999999999,
        "mean": 122.02499999999999,
        "min": 122.02499999999999,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 19 -> relu 20 -> quantize_and_dequantize 78:12",
        "max": 35.7654,
        "mean": 35.7654,
        "min": 35.7654,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 21 -> relu 22 -> quantize_and_dequantize 79:13",
        "max": 27.0864,
        "mean": 27.0864,
        "min": 27.0864,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 23 -> relu 24 -> quantize_and_dequantize 80:14",
        "max": 198.42000000000002,
        "mean": 198.42000000000002,
        "min": 198.42000000000002,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 25 -> quantize_and_dequantize 81:15",
        "max": 66.81479999999999,
        "mean": 66.81479999999999,
        "min": 66.81479999999999,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 26 -> relu 27 -> quantize_and_dequantize 82:16",
        "max": 69.19749999999999,
        "mean": 69.19749999999999,
        "min": 69.19749999999999,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 28 -> relu 29 -> quantize_and_dequantize 83:17",
        "max": 30.2716,
        "mean": 30.2716,
        "min": 30.2716,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 30 -> relu 31 -> quantize_and_dequantize 84:18",
        "max": 202.27200000000002,
        "mean": 202.27200000000002,
        "min": 202.27200000000002,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 32 -> quantize_and_dequantize 85:19",
        "max": 69.2716,
        "mean": 69.2716,
        "min": 69.2716,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/pooling_2d 33 -> quantize_and_dequantize 86:20",
        "max": 51.629599999999996,
        "mean": 51.629599999999996,
        "min": 51.629599999999996,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 34 -> relu 35 -> quantize_and_dequantize 87:21",
        "max": 61.0864,
        "mean": 61.0864,
        "min": 61.0864,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 36 -> relu 37 -> quantize_and_dequantize 88:22",
        "max": 17.2469,
        "mean": 17.2469,
        "min": 17.2469,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 38 -> relu 39 -> quantize_and_dequantize 89:23",
        "max": 117.062,
        "mean": 117.062,
        "min": 117.062,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 40 -> quantize_and_dequantize 90:24",
        "max": 38.481500000000004,
        "mean": 38.481500000000004,
        "min": 38.481500000000004,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 41 -> relu 42 -> quantize_and_dequantize 91:25",
        "max": 88.2593,
        "mean": 88.2593,
        "min": 88.2593,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 43 -> relu 44 -> quantize_and_dequantize 92:26",
        "max": 17.5062,
        "mean": 17.5062,
        "min": 17.5062,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 45 -> relu 46 -> quantize_and_dequantize 93:27",
        "max": 115.827,
        "mean": 115.827,
        "min": 115.827,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 47 -> quantize_and_dequantize 94:28",
        "max": 37.4074,
        "mean": 37.4074,
        "min": 37.4074,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 48 -> relu 49 -> quantize_and_dequantize 95:29",
        "max": 87.56790000000001,
        "mean": 87.56790000000001,
        "min": 87.56790000000001,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 50 -> relu 51 -> quantize_and_dequantize 96:30",
        "max": 23.8889,
        "mean": 23.8889,
        "min": 23.8889,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 52 -> relu 53 -> quantize_and_dequantize 97:31",
        "max": 255.877,
        "mean": 255.877,
        "min": 255.877,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 54 -> quantize_and_dequantize 98:32",
        "max": 57.7037,
        "mean": 57.7037,
        "min": 57.7037,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 55 -> relu 56 -> quantize_and_dequantize 99:33",
        "max": 114.61699999999999,
        "mean": 114.61699999999999,
        "min": 114.61699999999999,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 57 -> relu 58 -> quantize_and_dequantize 100:34",
        "max": 24.8395,
        "mean": 24.8395,
        "min": 24.8395,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 59 -> relu 60 -> quantize_and_dequantize 101:35",
        "max": 266.864,
        "mean": 266.864,
        "min": 266.864,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/concat 61 -> quantize_and_dequantize 102:36",
        "max": 57.3086,
        "mean": 57.3086,
        "min": 57.3086,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/convolution_2d 62 -> relu 63 -> quantize_and_dequantize 103:37",
        "max": 65.9383,
        "mean": 65.9383,
        "min": 65.9383,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/mean 64 -> quantize_and_dequantize 104:38",
        "max": 23.8148,
        "mean": 23.8148,
        "min": 23.8148,
        "std": 0.0
      },
      {
        "layer_name": " Delegate/softmax 65 -> quantize_and_dequantize 105 -> quantize_and_dequantize 66:39",
        "max": 3.67901,
        "mean": 3.67901,
        "min": 3.67901,
        "std": 0.0
      }
    ],
    "max": 3855.0,
    "mean": 3700.41,
    "min": 3633.0,
    "std": 40.0,
    "troughput": null
  },
  "load_accelerator": null,
  "load_cpu": 28.666666666666668,
  "model_file_name": "squeezenetv1.1_224_tfs_int8.tflite",
  "model_size": 823976,
  "nb_inference": 81,
  "nb_parameters_model": null,
  "postprocess_time": {
    "max": null,
    "mean": null,
    "min": null,
    "std": null
  },
  "power_consumption": null,
  "preprocess_time": {
    "max": null,
    "mean": null,
    "min": null,
    "std": null
  },
  "ram_peak_usage": 1.0538930341837147,
  "ram_size": 5632765952,
  "target": "qualcommrb3gen2",
  "target_id": "c-qualcommrb3gen2-0000-0000",
  "temperature": null,
  "version": 0,
  "version_tag": ""
}