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BTS-MTGNN
Commit 1193e9d5 by zlj
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no update when traiing is false

parent aedbd706
Showing with 83 additions and 84 deletions
examples/test_all.sh
...@@ -6,10 +6,10 @@ addr="192.168.1.107" ...@@ -6,10 +6,10 @@ addr="192.168.1.107"
partition_params=("ours") partition_params=("ours")
#"metis" "ldg" "random") #"metis" "ldg" "random")
#("ours" "metis" "ldg" "random") #("ours" "metis" "ldg" "random")
partitions="16" partitions="4"
node_per="4" node_per="4"
nnodes="4" nnodes="1"
node_rank="1" node_rank="0"
probability_params=("0.1") probability_params=("0.1")
sample_type_params=("boundery_recent_decay") sample_type_params=("boundery_recent_decay")
#sample_type_params=("recent" "boundery_recent_decay") #"boundery_recent_uniform") #sample_type_params=("recent" "boundery_recent_decay") #"boundery_recent_uniform")
...@@ -19,7 +19,7 @@ memory_type=("historical") ...@@ -19,7 +19,7 @@ memory_type=("historical")
#memory_type=("local" "all_update" "historical" "all_reduce") #memory_type=("local" "all_update" "historical" "all_reduce")
shared_memory_ssim=("0.3") shared_memory_ssim=("0.3")
#data_param=("WIKI" "REDDIT" "LASTFM" "WikiTalk") #data_param=("WIKI" "REDDIT" "LASTFM" "WikiTalk")
data_param=("LASTFM" "WikiTalk") data_param=("WikiTalk")
# "StackOverflow" "GDELT") # "StackOverflow" "GDELT")
#"GDELT") #"GDELT")
#data_param=("WIKI" "REDDIT" "LASTFM" "DGraphFin" "WikiTalk" "StackOverflow") #data_param=("WIKI" "REDDIT" "LASTFM" "DGraphFin" "WikiTalk" "StackOverflow")
...@@ -32,71 +32,71 @@ data_param=("LASTFM" "WikiTalk") ...@@ -32,71 +32,71 @@ data_param=("LASTFM" "WikiTalk")
#seed=(( RANDOM % 1000000 + 1 )) #seed=(( RANDOM % 1000000 + 1 ))
mkdir -p all_"$seed" mkdir -p all_"$seed"
# for data in "${data_param[@]}"; do for data in "${data_param[@]}"; do
# model="TGN_large" model="JODIE_large"
# if [ "$data" = "WIKI" ] || [ "$data" = "REDDIT" ] || [ "$data" = "LASTFM" ]; then if [ "$data" = "WIKI" ] || [ "$data" = "REDDIT" ] || [ "$data" = "LASTFM" ]; then
# model="TGN" model="JODIE"
# fi fi
# #model="APAN" #model="APAN"
# mkdir all_"$seed"/"$data" mkdir all_"$seed"/"$data"
# mkdir all_"$seed"/"$data"/"$model" mkdir all_"$seed"/"$data"/"$model"
# mkdir all_"$seed"/"$data"/"$model"/comm mkdir all_"$seed"/"$data"/"$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 --seed "$seed" > all_"$seed"/"$data"/"$model"/1.out & #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 --seed "$seed" > all_"$seed"/"$data"/"$model"/1.out &
# wait wait
# for partition in "${partition_params[@]}"; do for partition in "${partition_params[@]}"; do
# for sample in "${sample_type_params[@]}"; do for sample in "${sample_type_params[@]}"; do
# if [ "$sample" = "recent" ]; then if [ "$sample" = "recent" ]; then
# for mem in "${memory_type[@]}"; do for mem in "${memory_type[@]}"; do
# if [ "$mem" = "historical" ]; then if [ "$mem" = "historical" ]; then
# for ssim in "${shared_memory_ssim[@]}"; do for ssim in "${shared_memory_ssim[@]}"; do
# if [ "$partition" = "ours" ]; then if [ "$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 "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out &
# wait wait
# fi fi
# done done
# elif [ "$mem" = "all_reduce" ]; then elif [ "$mem" = "all_reduce" ]; then
# if [ "$partition" = "ours" ]; then if [ "$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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
# wait wait
# fi fi
# else 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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out & torchrun --nnodes "$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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out &
# wait wait
# #if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then #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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out & # 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
# wait wait
# #fi #fi
# fi fi
# done done
# else else
# for pro in "${probability_params[@]}"; do for pro in "${probability_params[@]}"; do
# for mem in "${memory_type[@]}"; do for mem in "${memory_type[@]}"; do
# if [ "$mem" = "historical" ]; then if [ "$mem" = "historical" ]; then
# for ssim in "${shared_memory_ssim[@]}"; do for ssim in "${shared_memory_ssim[@]}"; do
# if [ "$partition" = "ours" ]; then if [ "$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" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample"-"$pro".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample"-"$pro".out &
# wait wait
# fi fi
# done done
# elif [ "$mem" = "all_reduce" ]; then elif [ "$mem" = "all_reduce" ]; then
# if [ "$partition" = "ours"]; then if [ "$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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out& 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out&
# wait wait
# fi fi
# else 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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out & torchrun --nnodes "$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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out &
# wait wait
# if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then 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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out &
# wait wait
# fi fi
# fi fi
# done done
# done done
# fi fi
# done done
# done done
# done done
for data in "${data_param[@]}"; do for data in "${data_param[@]}"; do
model="JODIE_large" model="JODIE_large"
...@@ -117,20 +117,20 @@ for data in "${data_param[@]}"; do ...@@ -117,20 +117,20 @@ for data in "${data_param[@]}"; do
if [ "$mem" = "historical" ]; then if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then if [ "$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 "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out &
wait wait
fi fi
done done
elif [ "$mem" = "all_reduce" ]; then elif [ "$mem" = "all_reduce" ]; then
if [ "$partition" = "ours" ]; then if [ "$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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
wait wait
fi fi
else 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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out & torchrun --nnodes "$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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out &
wait wait
# if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then # 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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out & # 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
# wait # wait
# fi # fi
fi fi
...@@ -141,20 +141,20 @@ for data in "${data_param[@]}"; do ...@@ -141,20 +141,20 @@ for data in "${data_param[@]}"; do
if [ "$mem" = "historical" ]; then if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then if [ "$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" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample"-"$pro".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample"-"$pro".out &
wait wait
fi fi
done done
elif [ "$mem" = "all_reduce" ]; then elif [ "$mem" = "all_reduce" ]; then
if [ "$partition" = "ours"]; then if [ "$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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out& 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out&
wait wait
fi fi
else 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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out & #torchrun --nnodes "$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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out &
wait wait
if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then 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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out &
wait wait
fi fi
fi fi
...@@ -184,20 +184,20 @@ for data in "${data_param[@]}"; do ...@@ -184,20 +184,20 @@ for data in "${data_param[@]}"; do
if [ "$mem" = "historical" ]; then if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then if [ "$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 "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample".out &
wait wait
fi fi
done done
elif [ "$mem" = "all_reduce" ]; then elif [ "$mem" = "all_reduce" ]; then
if [ "$partition" = "ours" ]; then if [ "$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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
wait wait
fi fi
else 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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out & torchrun --nnodes "$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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample".out &
wait wait
# if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then # 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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out & # 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 "$partition" --topk 0.02 --sample_type "$sample" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample".out &
# wait # wait
# fi # fi
fi fi
...@@ -208,20 +208,20 @@ for data in "${data_param[@]}"; do ...@@ -208,20 +208,20 @@ for data in "${data_param[@]}"; do
if [ "$mem" = "historical" ]; then if [ "$mem" = "historical" ]; then
for ssim in "${shared_memory_ssim[@]}"; do for ssim in "${shared_memory_ssim[@]}"; do
if [ "$partition" = "ours" ]; then if [ "$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" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample"-"$pro".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --shared_memory_ssim "$ssim" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$ssim"-"$sample"-"$pro".out &
wait wait
fi fi
done done
elif [ "$mem" = "all_reduce" ]; then elif [ "$mem" = "all_reduce" ]; then
if [ "$partition" = "ours"]; then if [ "$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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out& 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out&
wait wait
fi fi
else 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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out & #torchrun --nnodes "$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 "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-"$partition"-0-"$mem"-"$sample"-"$pro".out &
wait wait
if [ "$partition" = "ours" ] && [ "$mem" != "all_local" ]; then 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" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out & 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 "$partition" --topk 0.02 --sample_type "$sample" --probability "$pro" --memory_type "$mem" --seed "$seed" > all_"$seed"/"$data"/"$model"/"$partitions"-ours_shared-0.01-"$mem"-"$sample"-"$pro".out &
wait wait
fi fi
fi fi
......
examples/train_boundery.py
...@@ -471,9 +471,6 @@ def main(): ...@@ -471,9 +471,6 @@ def main():
for roots,mfgs,metadata in trainloader: for roots,mfgs,metadata in trainloader:
end = time_count.elapsed_event(start) end = time_count.elapsed_event(start)
total += end total += end
print('batch {} time {} {}\n'.format(b_cnt,end,total))
b_cnt = b_cnt + 1 b_cnt = b_cnt + 1
t1 = time_count.start_gpu() t1 = time_count.start_gpu()
...@@ -511,7 +508,9 @@ def main(): ...@@ -511,7 +508,9 @@ def main():
ada_param.update_gnn_aggregate_time(ada_param.last_start_event_gnn_aggregate) ada_param.update_gnn_aggregate_time(ada_param.last_start_event_gnn_aggregate)
edge_feat[1].wait() edge_feat[1].wait()
node_feat0[1].wait() node_feat0[1].wait()
if ada_param is not None: if ada_param is not None:
ada_param.update_fetch_time(ada_param.last_start_event_fetch) ada_param.update_fetch_time(ada_param.last_start_event_fetch)
ada_param.update_parameter() ada_param.update_parameter()
loss.backward() loss.backward()
......
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