/MobileNetV3-pytorch

Implementation of MobileNetV3 in pytorch

Primary LanguagePythonMIT LicenseMIT

MobileNetV3 in PyTorch

An implementation of MobileNetV3 in PyTorch. MobileNetV3 is an efficient convolutional neural network architecture for mobile devices. For more information check the paper: Searching for MobileNetV3

Usage

Clone the repo:

git clone https://github.com/Randl/MobileNetV3-pytorch
pip install -r requirements.txt

Use the model defined in MobileNetV3.py to run ImageNet example:

python3 -m torch.distributed.launch --nproc_per_node=8 imagenet.py --dataroot "/path/to/imagenet/" --sched clr -b 128 --seed 42 --world-size 8 --sync-bn```

To continue training from checkpoint

python imagenet.py --dataroot "/path/to/imagenet/" --resume "/path/to/checkpoint/folder"

Results

WIP

Classification Checkpoint MACs (M) Parameters (M) Top-1 Accuracy Top-5 Accuracy Claimed top-1 Claimed top-5 Inference time
MobileNetV3 Large x1.0 224 219.80 5.481 73.53 91.14 75.2 - ~258ms
mobilenet_v2_1.0_224 300 3.47 72.10 90.48 71.8 91.0 ~461ms

Inference time is for single 1080 ti per batch of 128.

You can test it with

python imagenet.py --dataroot "/path/to/imagenet/" --resume "results/mobilenetv3large-v1/model_best0.pth.tar" -e

Other implementations

Code used