AI Benchmark Alpha is an open source python library for evaluating AI performance of various hardware platforms, including CPUs, GPUs and TPUs. The benchmark is relying on TensorFlow machine learning library, and is providing a lightweight and accurate solution for assessing inference and training speed for key Deep Learning models.
In total, AI Benchmark consists of 42 tests and 19 sections provided below:
- MobileNet-V2
[classification] - Inception-V3
[classification] - Inception-V4
[classification] - Inception-ResNet-V2
[classification] - ResNet-V2-50
[classification] - ResNet-V2-152
[classification] - VGG-16
[classification] - SRCNN 9-5-5
[image-to-image mapping] - VGG-19
[image-to-image mapping] - ResNet-SRGAN
[image-to-image mapping] - ResNet-DPED
[image-to-image mapping] - U-Net
[image-to-image mapping] - Nvidia-SPADE
[image-to-image mapping] - ICNet
[image segmentation] - PSPNet
[image segmentation] - DeepLab
[image segmentation] - Pixel-RNN
[inpainting] - LSTM
[sentence sentiment analysis] - GNMT
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For more information and results, please visit the project website: http://ai-benchmark.com/alpha
sudo docker build -t odyssee/ai-benchmark:latest"
sudo docker run --gpus all -it odyssee/ai-benchmark:latest"