Test on TVM

Supported Models

Model	Codebase	Model config
RetinaNet	MMDetection	config
Faster R-CNN	MMDetection	config
YOLOv3	MMDetection	config
YOLOX	MMDetection	config
Mask R-CNN	MMDetection	config
SSD	MMDetection	config
ResNet	MMPretrain	config
ResNeXt	MMPretrain	config
SE-ResNet	MMPretrain	config
MobileNetV2	MMPretrain	config
ShuffleNetV1	MMPretrain	config
ShuffleNetV2	MMPretrain	config
VisionTransformer	MMPretrain	config
FCN	MMSegmentation	config
PSPNet	MMSegmentation	config
DeepLabV3	MMSegmentation	config
DeepLabV3+	MMSegmentation	config
UNet	MMSegmentation	config

The table above list the models that we have tested. Models not listed on the table might still be able to converted. Please have a try.

Test

• Ubuntu 20.04

• tvm 0.9.0

mmpretrain	metric	PyTorch	TVM
ResNet-18	top-1	69.90	69.90
ResNeXt-50	top-1	77.90	77.90
ShuffleNet V2	top-1	69.55	69.55
MobileNet V2	top-1	71.86	71.86

mmdet(*)	metric	PyTorch	TVM
SSD	box AP	25.5	25.5

*: We only test model on ssd since dynamic shape is not supported for now.

mmseg	metric	PyTorch	TVM
FCN	mIoU	72.25	72.36
PSPNet	mIoU	78.55	77.90