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4653e06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | #!/bin/bash
af3_input_json=$1
input_dir=$2
prediction_dir=$3
evaluation_dir=$4
gpu_id=$5
PYTHON_PATH="/opt/conda/bin/python"
# convert af3 input data to model format
$PYTHON_PATH ./preprocess.py --af3_input_json="$af3_input_json" --input_dir="$input_dir"
# run inference
export CUDA_VISIBLE_DEVICES=$gpu_id
N_sample=5
N_step=200
N_cycle=10
# seed=42
seed=42,66,101,2024,8888
$PYTHON_PATH /algo/Protenix/runner/inference.py \
--seeds ${seed} \
--dump_dir ${prediction_dir} \
--input_json_path $input_dir/inputs.json \
--model.N_cycle ${N_cycle} \
--sample_diffusion.N_sample ${N_sample} \
--sample_diffusion.N_step ${N_step} \
--use_msa_server
# Convert predictions to the general cif format,
# and generate evaluation prediction_reference.csv in evaluation_dir
$PYTHON_PATH ./postprocess.py --input_dir="$input_dir" --prediction_dir="$prediction_dir" --evaluation_dir="$evaluation_dir" |