Latency Prediction on NNLQP (Same Distribution)
1.18MAPENAR-Former V2
Evaluation results
| Method | Links | ||
|---|---|---|---|
| NAR-Former V2Test Model=NasBench201, Aggregation=best2023.06 | 1.18 | 100 | |
| NNLPTest Model=NasBench201, Aggregation=best2023.06 | 1.31 | 100 | |
| NNLPTest Model=NasBench201, Aggregation=avg2023.06 | 1.46 | 100 | |
| NAR-Former V2Test Model=MnasNet, Aggregation=best2023.06 | 1.7 | 100 | |
| NAR-Former V2Test Model=MobileNetV2, Aggregation=best2023.06 | 1.72 | 100 | |
| NAR-Former V2Test Model=MnasNet, Aggregation=avg2023.06 | 1.8 | 99.7 | |
| NAR-Former V2Test Model=NasBench201, Aggregation=avg2023.06 | 1.82 | 100 | |
| NAR-Former V2Test Model=MobileNetV2, Aggregation=avg2023.06 | 1.83 | 99.9 | |
| NAR-Former V2Test Model=EfficientNet, Aggregation=best2023.06 | 2.22 | 100 | |
| NAR-Former V2Test Model=EfficientNet, Aggregation=avg2023.06 | 2.34 | 98.5 | |
| NNLPTest Model=MobileNetV2, Aggregation=best2023.06 | 2.37 | 99.5 | |
| NNLPTest Model=MnasNet, Aggregation=best2023.06 | 2.46 | 98.5 | |
| NNLPTest Model=MobileNetV2, Aggregation=avg2023.06 | 2.47 | 99.3 | |
| NNLPTest Model=MnasNet, Aggregation=avg2023.06 | 2.6 | 97.7 | |
| NNLPTest Model=EfficientNet, Aggregation=best2023.06 | 2.82 | 97 | |
| NAR-Former V2Test Model=ResNet, Aggregation=best2023.06 | 2.89 | 99 | |
| NAR-Former V2Test Model=MobileNetV3, Aggregation=best2023.06 | 2.98 | 98 | |
| NAR-Former V2Test Model=All, Aggregation=best2023.06 | 3 | 96.3 | |
| NNLPTest Model=EfficientNet, Aggregation=avg2023.06 | 3.04 | 98 | |
| NAR-Former V2Test Model=All, Aggregation=avg2023.06 | 3.07 | 96.41 | |
| NAR-Former V2Test Model=ResNet, Aggregation=avg2023.06 | 3.11 | 98.55 | |
| NAR-Former V2Test Model=MobileNetV3, Aggregation=avg2023.06 | 3.12 | 96.75 | |
| NNLPTest Model=ResNet, Aggregation=best2023.06 | 3.25 | 98.5 | |
| NAR-Former V2Test Model=VGG, Aggregation=best2023.06 | 3.29 | 96 | |
| NAR-Former V2Test Model=SqueezeNet, Aggregation=best2023.06 | 3.34 | 96.5 | |
| NNLPTest Model=ResNet, Aggregation=avg2023.06 | 3.34 | 98.4 | |
| NNLPTest Model=MobileNetV3, Aggregation=best2023.06 | 3.43 | 96 | |
| NNLPTest Model=All, Aggregation=best2023.06 | 3.44 | 95.5 | |
| NAR-Former V2Test Model=GoogleNet, Aggregation=best2023.06 | 3.46 | 95.5 | |
| NNLPTest Model=All, Aggregation=avg2023.06 | 3.47 | 95.25 | |
| NNLPTest Model=MobileNetV3, Aggregation=avg2023.06 | 3.5 | 95.35 | |
| NAR-Former V2Test Model=VGG, Aggregation=avg2023.06 | 3.51 | 95.85 | |
| NAR-Former V2Test Model=SqueezeNet, Aggregation=avg2023.06 | 3.54 | 95.95 | |
| NAR-Former V2Test Model=GoogleNet, Aggregation=avg2023.06 | 3.63 | 95.95 | |
| NNLPTest Model=VGG, Aggregation=best2023.06 | 3.63 | 96.5 | |
| NNLPTest Model=VGG, Aggregation=avg2023.06 | 3.73 | 95.25 | |
| NNLPTest Model=SqueezeNet, Aggregation=best2023.06 | 3.97 | 93 | |
| NNLPTest Model=SqueezeNet, Aggregation=avg2023.06 | 4.03 | 93.25 | |
| NNLPTest Model=GoogleNet, Aggregation=best2023.06 | 4.12 | 93.5 | |
| NNLPTest Model=GoogleNet, Aggregation=avg2023.06 | 4.18 | 93.7 | |
| NAR-Former V2Test Model=AlexNet, Aggregation=best2023.06 | 5.97 | 84 | |
| NAR-Former V2Test Model=AlexNet, Aggregation=avg2023.06 | 6.18 | 81.9 | |
| NNLPTest Model=AlexNet, Aggregation=best2023.06 | 6.21 | 84.5 | |
| NNLPTest Model=AlexNet, Aggregation=avg2023.06 | 6.37 | 81.75 |