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BTS-MTGNN
Commit 9359ae3b by zlj
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fix smooth aggregation

parent ff19c482
Showing with 78 additions and 80 deletions
examples/test_all.sh
#!/bin/bash
# 定义数组变量
addr="192.168.1.105"
addr="192.168.1.107"
partition_params=("ours" )
#"metis" "ldg" "random")
#("ours" "metis" "ldg" "random")
......@@ -9,17 +9,16 @@ partitions="4"
node_per="4"
nnodes="1"
node_rank="0"
probability_params=("1" "0.5" "0.1" "0.05" "0.01" "0")
sample_type_params=("recent" "boundery_recent_decay" "boundery_recent_uniform")
probability_params=("0.1" "0.05" "0.01" "0")
sample_type_params=("boundery_recent_decay")
#sample_type_params=("recent" "boundery_recent_decay") #"boundery_recent_uniform")
sample_type_params=("recent")
#memory_type=("all_update" "p2p" "all_reduce" "historical" "local")
memory_type=("all_update" "local")
#"historical" "all_update") #"local" "historical")
#memory_type=("all_update" "historical" "local")
memory_type=("historical")
#memory_type=("local" "all_update" "historical" "all_reduce")
shared_memory_ssim=("0" "0.3" "0.5" "0.7")
shared_memory_ssim=("0.3" "0.7")
#data_param=("WIKI" "REDDIT" "LASTFM" "WikiTalk")
data_param=("WIKI" "LASTFM")
data_param=("LASTFM" "WikiTalk" "StackOverflow" "GDELT" "TaoBao")
#data_param=("WIKI" "REDDIT" "LASTFM" "DGraphFin" "WikiTalk" "StackOverflow")
#data_param=("WIKI" "REDDIT" "LASTFM" "WikiTalk" "StackOverflow")
#data_param=("REDDIT" "WikiTalk")
......@@ -28,7 +27,7 @@ mkdir -p all
# 遍历数组并执行命令
for data in "${data_param[@]}"; do
model="TGN"
model="TGN_large"
if [ "$data" = "WIKI" ] || [ "$data" = "REDDIT" ] || [ "$data" = "LASTFM" ]; then
model="TGN"
fi
......@@ -45,6 +44,74 @@ for data in "${data_param[@]}"; do
if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.1 --sample_type "$sample" --memory_type "$mem" --shared_memory_ssim "$ssim" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out &
wait
fi
done
elif [ "$mem" = "all_reduce" ]; then
if [ "$partition" = "ours" ]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.1 --sample_type "$sample" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
wait
fi
else
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0 --sample_type "$sample" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out &
wait
if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.1 --sample_type "$sample" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
wait
fi
fi
done
else
for pro in "${probability_params[@]}"; do
for mem in "${memory_type[@]}"; do
if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.1 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --shared_memory_ssim "$ssim" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01"$mem"-"$ssim"-"$sample"-"$pro".out &
wait
fi
done
elif [ "$mem" = "all_reduce" ]; then
if [ "$partition" = "ours"]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.1 --sample_type "$sample" --probability "$pro" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out&
wait
fi
else
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0 --sample_type "$sample" --probability "$pro" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out &
wait
if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.1 --sample_type "$sample" --probability "$pro" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out &
wait
fi
fi
done
done
fi
done
done
done
for data in "${data_param[@]}"; do
model="JODILE"
if [ "$data" = "WIKI" ] || [ "$data" = "REDDIT" ] || [ "$data" = "LASTFM" ]; then
model="JODIE"
fi
#model="APAN"
mkdir all/"$data"
mkdir all/"$data"/"$model"
mkdir all/"$data"/"$model"/comm
#torchrun --nnodes "$nnodes" --node_rank 0 --nproc-per-node 1 --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition ours --memory_type local --sample_type recent --topk 0 > all/"$data"/"$model"/1.out &
wait
for partition in "${partition_params[@]}"; do
for sample in "${sample_type_params[@]}"; do
if [ "$sample" = "recent" ]; then
for mem in "${memory_type[@]}"; do
if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then
torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --memory_type "$mem" --shared_memory_ssim "$ssim" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out &
wait
fi
......@@ -93,72 +160,3 @@ for data in "${data_param[@]}"; do
done
done
done
# for data in "${data_param[@]}"; do
# model="JODILE"
# if [ "$data" = "WIKI" ] || [ "$data" = "REDDIT" ] || [ "$data" = "LASTFM" ]; then
# model="JODIE"
# fi
# #model="APAN"
# mkdir all/"$data"
# mkdir all/"$data"/"$model"
# mkdir all/"$data"/"$model"/comm
# #torchrun --nnodes "$nnodes" --node_rank 0 --nproc-per-node 1 --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition ours --memory_type local --sample_type recent --topk 0 > all/"$data"/"$model"/1.out &
# wait
# for partition in "${partition_params[@]}"; do
# for sample in "${sample_type_params[@]}"; do
# if [ "$sample" = "recent" ]; then
# for mem in "${memory_type[@]}"; do
# if [ "$mem" = "historical" ]; then
# for ssim in "${shared_memory_ssim[@]}"; do
# if [ "$partition" = "ours" ]; then
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --memory_type "$mem" --shared_memory_ssim "$ssim" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out &
# wait
# fi
# done
# elif [ "$mem" = "all_reduce" ]; then
# if [ "$partition" = "ours" ]; then
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
# wait
# fi
# else
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0 --sample_type "$sample" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out &
# wait
# if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
# wait
# fi
# fi
# done
# else
# for pro in "${probability_params[@]}"; do
# for mem in "${memory_type[@]}"; do
# if [ "$mem" = "historical" ]; then
# continue
# # for ssim in "${shared_memory_ssim[@]}"; do
# # if [ "$partition" = "ours" ]; then
# # torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --shared_memory_ssim "$ssim" > all/"$data"/"$partitions"-ours_shared-0.01"$mem"-"$ssim"-"$sample"-"$pro".out &
# # wait
# # fi
# # done
# elif [ "$mem" = "all_reduce" ]; then
# if [ "$partition" = "ours"]; then
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --probability "$pro" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out&
# wait
# fi
# else
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0 --sample_type "$sample" --probability "$pro" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out &
# wait
# if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then
# torchrun --nnodes "$nnodes" --node_rank "$node_rank" --nproc-per-node "$node_per" --master-addr "$addr" --master-port 9445 train_boundery.py --dataname "$data" --mode "$model" --partition "$partition" --topk 0.01 --sample_type "$sample" --probability "$pro" --memory_type "$mem" > all/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out &
# wait
# fi
# fi
# done
# done
# fi
# done
# done
# done
examples/train_boundery.py
......@@ -63,7 +63,7 @@ parser.add_argument('--partition', default='part', type=str, metavar='W',
help='name of model')
parser.add_argument('--topk', default='0', type=str, metavar='W',
help='name of model')
parser.add_argument('--probability', default=0.1, type=float, metavar='W',
parser.add_argument('--probability', default=1, type=float, metavar='W',
help='name of model')
parser.add_argument('--sample_type', default='recent', type=str, metavar='W',
help='name of model')
......@@ -653,7 +653,7 @@ def main():
break
else:
print('\ttrain loss:{:.4f} train ap:{:4f} val ap:{:4f} val auc:{:4f} test ap {:4f} test auc{:4f}\n'.format(total_loss,train_ap, ap, auc,test_ap,test_auc))
print('\ttotal time:{:.2f}s prep time:{:.2f}s\n test time {:.2f}'.format(time.time()-epoch_start_time, time_prep),t_test)
print('\ttotal time:{:.2f}s prep time:{:.2f}s\n test time {:.2f}'.format(time.time()-epoch_start_time, time_prep,t_test))
torch.save(model.module.state_dict(), get_checkpoint_path(e))
if args.model == 'TGN':
print('weight {} {}\n'.format(tt.weight_count_local,tt.weight_count_remote))
......
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