--> config model
done
--> Loading model
W The target_platform is not set in config, using default target platform rk1808.
done
--> Building model
done
--> Export RKNN model
done
--> Init runtime environment
librknn_runtime version 1.7.3 (5047ff8 build: 2022-08-13 12:11:22 base: 1131)
done
--> Running model
mobilenet_v1
-----TOP 5-----
[156]: 0.8642578125
[155]: 0.083740234375
[205]: 0.01241302490234375
[284]: 0.006565093994140625
[194]: 0.002044677734375
done
--> Evaluate model performance
W When performing performance evaluation, inputs can be set to None to use fake inputs.
========================================================================
Performance
========================================================================
Layer ID Name Time(us)
60 openvx.tensor_transpose_3 72
1 convolution.relu.pooling.layer2_2 369
3 convolution.relu.pooling.layer2_2 211
5 convolution.relu.pooling.layer2_2 184
7 convolution.relu.pooling.layer2_2 315
9 convolution.relu.pooling.layer2_2 99
11 convolution.relu.pooling.layer2_2 137
13 convolution.relu.pooling.layer2_2 103
15 convolution.relu.pooling.layer2_2 116
17 convolution.relu.pooling.layer2_2 95
19 convolution.relu.pooling.layer2_2 102
21 convolution.relu.pooling.layer2_2 151
23 convolution.relu.pooling.layer2_2 95
25 convolution.relu.pooling.layer2_2 109
27 convolution.relu.pooling.layer2_2 106
29 convolution.relu.pooling.layer2_2 211
31 convolution.relu.pooling.layer2_2 106
33 convolution.relu.pooling.layer2_2 211
35 convolution.relu.pooling.layer2_2 106
37 convolution.relu.pooling.layer2_2 211
39 convolution.relu.pooling.layer2_2 106
41 convolution.relu.pooling.layer2_2 211
43 convolution.relu.pooling.layer2_2 106
45 convolution.relu.pooling.layer2_2 211
47 convolution.relu.pooling.layer2_2 108
49 convolution.relu.pooling.layer2_2 163
51 convolution.relu.pooling.layer2_2 206
53 convolution.relu.pooling.layer2_2 319
55 pooling.layer2 34
56 fullyconnected.relu.layer_3 110
58 softmaxlayer2.layer 39
Total Time(us): 4722
FPS(600MHz): 158.83
FPS(800MHz): 211.77
Note: Time of each layer is converted according to 800MHz!
========================================================================
done
---------开发板评估-----------
--> config model
done
--> Loading model
done
--> Building model
done
--> Export RKNN model
done
--> Init runtime environment
W Flag perf_debug has been set, it will affect the performance of inference!
I NPUTransfer: Starting NPU Transfer Client, Transfer version 2.1.0 (b5861e7@2020-11-23T11:50:36)
D RKNNAPI: ==============================================
D RKNNAPI: RKNN VERSION:
D RKNNAPI: API: 1.7.3 (0cfd4a1 build: 2022-08-15 17:08:57)
D RKNNAPI: DRV: 1.7.0 (7880361 build: 2021-08-16 14:05:08)
D RKNNAPI: ==============================================
done
--> Running model
mobilenet_v1
-----TOP 5-----
[156]: 0.8515625
[155]: 0.091796875
[205]: 0.0135955810546875
[284]: 0.0064697265625
[194 260]: 0.002239227294921875