Multimodal extreme classification

@InProceedings{Mittal22, author = {Mittal, A. and Dahiya, K. and Malani, S. and Ramaswamy, J. and Kuruvilla, S. and  Ajmera, J. and Chang, K. and Agrawal, S. and Kar, P. and Varma, M.}, title = {Multimodal extreme classification},
booktitle = {CVPR}, month = {June},
year = {2022}
}

SETUP WORKSPACE

mkdir -p ${HOME}/scratch/XC/data mkdir -p ${HOME}/scratch/XC/programs

SETUP DATASET

Download dataset from XML Repository

cd${HOME}/scratch/XC/data
gdown --id 1bV5d_SOw6pNXWrQecihcSc2xkqUcXMFO (from gdrive url)
unzip MM-AmazonTitles-300K.zip
cd -

NOTE: If you need pre-downloaded images (128x128) kindly fill out this form

SETUP MUFIN

cd${HOME}/scratch/XC/programs
git clone https://github.com/anshumitts/CafeXC.git
conda env create -f CafeXC/CafeXC.yml
conda activate xc
pip install hnswlib Cython git+https://github.com/kunaldahiya/pyxclib.git
git clone https://github.com/Extreme-classification/MUFIN.git

RUNNING MUFIN

cd${HOME}/scratch/XC/programs/MUFIN
chmod +x run_MUFIN.sh
./run_MUFIN.sh <ALL_GPU_IDS><TYPE><DATASET><FOLDER_NAME><IMG_ENCODER><TXT_ENCODER><KEEP_TOP_K><RESTRICTMEM># TYPE :	MufinMultiModal PreTrainedMufinMultiModal# DATASET :	MM-AmazonTitles-300K# FOLDER_NAME :	USER's choice# IMG_ENCODER :	ViT resnet18 vgg11 resnet50FPN# TXT_ENCODER :	sentencebert BoW Seq VisualBert # KEEP_TOP_K : USE ONLY K images [-1, inf]; -1 will use all images# RESTRICTMEM : 0 will load all data in RAM while 1 will load from disk.
e.g.
./run_MUFIN.sh 0,1 PreTrainedMufinMultiModal MM-AmazonTitles-300K MUFIN_pretrained ViT sentencebert -1 0
./run_MUFIN.sh 0,1 MufinMultiModal MM-AmazonTitles-300K MUFIN ViT sentencebert -1 0