Update the ImageNet-1k inference accuracy, based on Gluon-model zoo (pre-trained model), comparison target is NVidia-GPU. (Model including: AlexNet, VGG16, Resnet50-v1/v2, Inception-v3, DenseNet, SqueezeNet, MobileNetv1.0)
On Python2 toplogy | CPU-top1 | CPU-top5 | GPU-top1 | GPU-top5 -- | -- | -- | -- | -- alexnet | 0.556455 | 0.785575 | 0.556455 | 0.785523 resnet50_v1 | 0.753367 | 0.926907 | 0.753367 | 0.926907 resnet50_v2 | 0.761327 | 0.929354 | 0.761327 | 0.929354 vgg16 | 0.720138 | 0.90662 | 0.720138 | 0.90662 densenet121 | 0.736587 | 0.917328 | 0.736587 | 0.917328 squeezenet1.1 | 0.561469 | 0.792099 | 0.561481 | 0.792099 mobilenet1.0 | 0.693531 | 0.889003 | 0.693531 | 0.889003 inceptionv3 | 0.762979 | 0.928074 | 0.762979 | 0.92814 On Python3 toplogy | CPU-top1 | CPU-top5 | GPU-top1 | GPU-top5 -- | -- | -- | -- | -- alexnet | 0.556455 | 0.785575 | 0.556455 | 0.785523 resnet50_v1 | 0.753367 | 0.926907 | 0.753367 | 0.926907 resnet50_v2 | 0.761327 | 0.929354 | 0.761327 | 0.929354 vgg16 | 0.720138 | 0.90662 | 0.720138 | 0.90662 densenet121 | 0.736587 | 0.917328 | 0.736587 | 0.917328 squeezenet1.1 | 0.561469 | 0.792099 | 0.561481 | 0.792099 mobilenet1.0 | 0.693531 | 0.889003 | 0.693531 | 0.889003 inceptionv3 | 0.762979 | 0.928074 | 0.762979 | 0.92814 [ Full content available at: https://github.com/apache/incubator-mxnet/pull/12591 ] This message was relayed via gitbox.apache.org for [email protected]
