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Unverified Commit e317f715 authored by Da Zheng's avatar Da Zheng Committed by GitHub
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deprecate DGL-KE. (#1432) 



* deprecate DGL-KE.

* Update README.md

* remove from CI.

* remove tests.
Co-authored-by: default avatarZheng <dzzhen@3c22fb0ed81b.ant.amazon.com>
parent 8d20c249
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View file @ e317f715
......@@ -69,14 +69,6 @@ def unit_test_win64(backend, dev) {
}
}
def kg_test_linux(backend, dev) {
init_git()
unpack_lib("dgl-${dev}-linux", dgl_linux_libs)
timeout(time: 20, unit: 'MINUTES') {
sh "bash tests/scripts/task_kg_test.sh ${backend} ${dev}"
}
}
def example_test_linux(backend, dev) {
init_git()
unpack_lib("dgl-${dev}-linux", dgl_linux_libs)
......@@ -370,61 +362,6 @@ pipeline {
}
}
}
stage("App") {
parallel {
stage("Knowledge Graph CPU") {
agent {
docker {
label "linux-cpu-node"
image "dgllib/dgl-ci-cpu:conda"
}
}
stages {
stage("Torch test") {
steps {
kg_test_linux("pytorch", "cpu")
}
}
stage("MXNet test") {
steps {
kg_test_linux("mxnet", "cpu")
}
}
}
post {
always {
cleanWs disableDeferredWipeout: true, deleteDirs: true
}
}
}
stage("Knowledge Graph GPU") {
agent {
docker {
label "linux-gpu-node"
image "dgllib/dgl-ci-gpu:conda"
args "--runtime nvidia"
}
}
stages {
stage("Torch test") {
steps {
kg_test_linux("pytorch", "gpu")
}
}
stage("MXNet test") {
steps {
kg_test_linux("mxnet", "gpu")
}
}
}
post {
always {
cleanWs disableDeferredWipeout: true, deleteDirs: true
}
}
}
}
}
}
post {
always {
......
apps/kg/README.md
View file @ e317f715
# DGL - Knowledge Graph Embedding
**Note: DGL-KE is moved to [here](https://github.com/awslabs/dgl-ke). DGL-KE in this folder is deprecated.**
## Introduction
......
tests/scripts/task_kg_test.sh deleted 100644 → 0
View file @ 8d20c249
#!/bin/bash
. /opt/conda/etc/profile.d/conda.sh
KG_DIR="./apps/kg/"
function fail {
echo FAIL: $@
exit -1
}
function usage {
echo "Usage: $0 backend device"
}
# check arguments
if [ $# -ne 2 ]; then
usage
fail "Error: must specify device and bakend"
fi
if [ "$2" == "cpu" ]; then
dev=-1
elif [ "$2" == "gpu" ]; then
export CUDA_VISIBLE_DEVICES=0
dev=0
else
usage
fail "Unknown device $2"
fi
export DGLBACKEND=$1
export DGL_LIBRARY_PATH=${PWD}/build
export PYTHONPATH=${PWD}/python:$KG_DIR:$PYTHONPATH
export DGL_DOWNLOAD_DIR=${PWD}
conda activate ${DGLBACKEND}-ci
# test
pushd $KG_DIR> /dev/null
python3 -m pytest tests/test_score.py || fail "run test_score.py on $1"
if [ "$2" == "cpu" ]; then
# verify CPU training DistMult
python3 train.py --model DistMult --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --valid --test -adv --eval_interval 30 --eval_percent 0.01 \
--save_emb DistMult_FB15k_emb --data_path /data/kg || fail "run DistMult on $2"
# verify saving training result
python3 eval.py --model_name DistMult --dataset FB15k --hidden_dim 100 \
--gamma 500.0 --batch_size 16 --model_path DistMult_FB15k_emb/ \
--eval_percent 0.01 --data_path /data/kg || fail "eval DistMult on $2"
elif [ "$2" == "gpu" ]; then
# verify GPU training DistMult
python3 train.py --model DistMult --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --gpu 0 --valid --test -adv --eval_interval 30 --eval_percent 0.01 \
--data_path /data/kg || fail "run DistMult on $2"
# verify mixed CPU GPU training
python3 train.py --model DistMult --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --gpu 0 --valid --test -adv --mix_cpu_gpu --eval_percent 0.01 \
--save_emb DistMult_FB15k_emb --data_path /data/kg || fail "run mix with async CPU/GPU DistMult"
# verify saving training result
python3 eval.py --model_name DistMult --dataset FB15k --hidden_dim 100 \
--gamma 500.0 --batch_size 16 --gpu 0 --model_path DistMult_FB15k_emb/ \
--eval_percent 0.01 --data_path /data/kg || fail "eval DistMult on $2"
if [ "$1" == "pytorch" ]; then
# verify mixed CPU GPU training with async_update
python3 train.py --model DistMult --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --gpu 0 --valid --test -adv --mix_cpu_gpu --eval_percent 0.01 \
--async_update --data_path /data/kg || fail "run mix CPU/GPU DistMult"
# verify mixed CPU GPU training with random partition
python3 train.py --model DistMult --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --num_proc 2 --gpu 0 --valid --test -adv --mix_cpu_gpu \
--eval_percent 0.01 --async_update --force_sync_interval 100 \
--data_path /data/kg || fail "run multiprocess async CPU/GPU DistMult"
# verify mixed CPU GPU training with random partition async_update
python3 train.py --model DistMult --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --num_proc 2 --gpu 0 --valid --test -adv --mix_cpu_gpu \
--eval_percent 0.01 --rel_part --async_update --force_sync_interval 100 \
--data_path /data/kg || fail "run multiprocess async CPU/GPU DistMult"
# multi process training TransR
python3 train.py --model TransR --dataset FB15k --batch_size 128 \
--neg_sample_size 16 --hidden_dim 100 --gamma 500.0 --lr 0.1 --max_step 100 \
--batch_size_eval 16 --num_proc 2 --gpu 0 --valid --test -adv --eval_interval 30 \
--eval_percent 0.01 --data_path /data/kg --mix_cpu_gpu --rel_part --async_update \
--save_emb TransR_FB15k_emb || fail "run multiprocess TransR on $2"
python3 eval.py --model_name TransR --dataset FB15k --hidden_dim 100 \
--gamma 500.0 --batch_size 16 --num_proc 2 --gpu 0 --model_path TransR_FB15k_emb/ \
--eval_percent 0.01 --mix_cpu_gpu --data_path /data/kg || fail "eval multiprocess TransR on $2"
fi
fi
popd > /dev/null
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