MobileOne

The ResNet model is based on the “An Improved One millisecond Mobile Backbone” paper.

Architecture overview

This architecture optimizes the model for inference speed at inference time on mobile device.

The key takeaways from the paper are the following:

• reuse the reparametrization concept of RepVGG while adding overparametrization in the block branches.

• each block is composed of two consecutive reparametrizeable blocks (in a similar fashion than RepVGG): a depth-wise convolutional block, a point-wise convolutional block.

Model builders

The following model builders can be used to instantiate a MobileOne model, with or without pre-trained weights. All the model builders internally rely on the holocron.models.classification.mobileone.MobileOne base class. Please refer to the source code for more details about this class.

mobileone_s0([pretrained, checkpoint, progress])	MobileOne-S0 from "An Improved One millisecond Mobile Backbone"
mobileone_s1([pretrained, checkpoint, progress])	MobileOne-S1 from "An Improved One millisecond Mobile Backbone"
mobileone_s2([pretrained, checkpoint, progress])	MobileOne-S2 from "An Improved One millisecond Mobile Backbone"
mobileone_s3([pretrained, checkpoint, progress])	MobileOne-S3 from "An Improved One millisecond Mobile Backbone"