wqflyx/mfnas

MF-NAS

This code is based on the implementation of DARTS.

Requirements

To install requirements:

pip install -r requirements.txt

Running

To train the model architectures, run this command:

python main.py

To search the model architectures by MF-NAS, set the hyper-parameters in config.py as such:

Hyper-parameters	Value
dataset_root	path_to_dataset

Quickly Evaluation with Pre-trained Models

We provide one of the model architecture searched by MF-NAS and the trained weights on CIFAR10 of the model.

To evaluate the performance of pre-trained model on CIFAR10, run:

python evaluate.py

Results

One of the model achieved by MF-NAS on CIFAR10:

Model name	Top 1 Acc	Params (M)
MF-NAS	97.52%	3.3