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[hotfix] add DISTPAN argument for benchmark (#2412)

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* change the benchmark config file

* change config

* revert config file

* rename distpan to distplan
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HELSON 2023-01-10 11:39:25 +08:00 committed by GitHub
parent 7d5640b9db
commit d84e747975
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3 changed files with 9 additions and 7 deletions
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6
examples/language/gpt/gemini/benchmark_gemini.sh
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@ -1,5 +1,5 @@
for MODEL_TYPE in "gpt2_medium"; do for MODEL_TYPE in "gpt2_medium"; do
for DISPAN in "colossalai"; do for DISTPLAN in "colossalai"; do
for BATCH_SIZE in 16; do for BATCH_SIZE in 16; do
for GPUNUM in 1 2 4 8; do for GPUNUM in 1 2 4 8; do
for TPDEGREE in 1 2 4 8; do for TPDEGREE in 1 2 4 8; do
@ -8,8 +8,8 @@ for MODEL_TYPE in "gpt2_medium"; do
fi fi
for PLACEMENT in "cpu" "auto"; do for PLACEMENT in "cpu" "auto"; do
echo "****************** Begin ***************************" echo "****************** Begin ***************************"
echo "+ benchmrking MODEL ${MODEL_TYPE} DISPAN ${DISPAN} GPU ${GPUNUM} BS ${BATCH_SIZE} TP ${TPDEGREE} POLICY ${PLACEMENT}" echo "+ benchmrking MODEL ${MODEL_TYPE} DISTPLAN ${DISTPLAN} GPU ${GPUNUM} BS ${BATCH_SIZE} TP ${TPDEGREE} POLICY ${PLACEMENT}"
MODEL_TYPE=${MODEL_TYPE} DISPAN=${DISPAN} BATCH_SIZE=${BATCH_SIZE} GPUNUM=${GPUNUM} TPDEGREE=${TPDEGREE} PLACEMENT=${PLACEMENT} \ MODEL_TYPE=${MODEL_TYPE} DISTPLAN=${DISTPLAN} BATCH_SIZE=${BATCH_SIZE} GPUNUM=${GPUNUM} TPDEGREE=${TPDEGREE} PLACEMENT=${PLACEMENT} \
bash ./run_gemini.sh bash ./run_gemini.sh
echo "****************** Finished ***************************" echo "****************** Finished ***************************"
echo "" echo ""

8
examples/language/gpt/gemini/run_gemini.sh
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@ -1,8 +1,8 @@
set -x set -x
# distplan in ["colossalai", "zero1", "zero2", "torch_ddp", "torch_zero"] # distplan in ["colossalai", "zero1", "zero2", "torch_ddp", "torch_zero"]
export DISTPAN=${DISTPAN:-"colossalai"} export DISTPLAN=${DISTPLAN:-"colossalai"}
# The following options only valid when DISTPAN="colossalai" # The following options only valid when DISTPLAN="colossalai"
export GPUNUM=${GPUNUM:-1} export GPUNUM=${GPUNUM:-1}
export TPDEGREE=${TPDEGREE:-1} export TPDEGREE=${TPDEGREE:-1}
export PLACEMENT=${PLACEMENT:-"cpu"} export PLACEMENT=${PLACEMENT:-"cpu"}
@ -20,5 +20,5 @@ torchrun --standalone --nproc_per_node=${GPUNUM} ./train_gpt_demo.py \
--batch_size=${BATCH_SIZE} \ --batch_size=${BATCH_SIZE} \
--placement=${PLACEMENT} \ --placement=${PLACEMENT} \
--shardinit=${USE_SHARD_INIT} \ --shardinit=${USE_SHARD_INIT} \
--distplan=${DISTPAN} \ --distplan=${DISTPLAN} \
2>&1 | tee ./gemini_logs/${MODEL_TYPE}_${DISTPAN}_gpu_${GPUNUM}_bs_${BATCH_SIZE}_tp_${TPDEGREE}_${PLACEMENT}.log 2>&1 | tee ./gemini_logs/${MODEL_TYPE}_${DISTPLAN}_gpu_${GPUNUM}_bs_${BATCH_SIZE}_tp_${TPDEGREE}_${PLACEMENT}.log

2
examples/language/gpt/gemini/train_gpt_demo.py
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@ -290,9 +290,11 @@ def main():
from torch.distributed.optim import ZeroRedundancyOptimizer from torch.distributed.optim import ZeroRedundancyOptimizer
optimizer = ZeroRedundancyOptimizer(model.parameters(), optimizer_class=torch.optim.Adam, lr=0.01) optimizer = ZeroRedundancyOptimizer(model.parameters(), optimizer_class=torch.optim.Adam, lr=0.01)
elif args.distplan.startswith("zero"): elif args.distplan.startswith("zero"):
model = model.half()
partition_flag = args.distplan == "zero2" partition_flag = args.distplan == "zero2"
optimizer = torch.optim.Adam(model.parameters(), lr=0.01) optimizer = torch.optim.Adam(model.parameters(), lr=0.01)
optimizer = LowLevelZeroOptimizer(optimizer, optimizer = LowLevelZeroOptimizer(optimizer,
reduce_bucket_size=12 * 1024 * 1024,
overlap_communication=True, overlap_communication=True,
partition_grad=partition_flag, partition_grad=partition_flag,
verbose=True) verbose=True)