Setup

This project requires python 3.8 (!)

1. Install bigbio

git clone [email protected]:bigscience-workshop/biomedical.git
cd biomedical
pip install -e .
cd ..

2. Install pytorch

conda install pytorch==1.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge

3. Install our fork of allennlp v 1.3 with DDP + gradient accumulation patch backported

pip install git+https://github.com/leonweber/allennlp

4. Clone our fork of Machamp:

git clone https://github.com/leonweber/machamp.git

5. Clone the biomuppet repository and install dependencies

git clone [email protected]:leonweber/biomuppet.git
pip install --no-deps -r biomuppet/requirements.txt

6. Generate the machamp training data

cd biomuppet; bash generate_machamp_data.sh [MACHAMP_ROOT_PATH]; cd ..

7a. Run Machamp training (single node)

cd [MACHAMP_ROOT_PATH]; python train.py --dataset_config configs/bigbio_debug.json

7b. Run Machamp training (multiple nodes)

Set correct distributed settings in [MACHAMP_ROOT_PATH]/configs/params.json:

    "distributed": {
        "cuda_devices": [0, 1, 2, 3], # note that all nodes have to have the same number of GPUs for AllenNLP multi node training to work
        "master_address": "[ADDRESS of main node]",
        "master_port": "29500", # some free port
        "num_nodes": [Total number of nodes]
        }

Start training:

cd [MACHAMP_ROOT_PATH]; python train.py --dataset_config configs/bigbio_debug.json --node_rank [rank of local node]