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add N4C32 shell for PETRV2 #1662

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add N4C32 shell for PETRV2 #1662

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17 changes: 17 additions & 0 deletions frame_benchmark/pytorch/dynamic/Paddle3D/scripts/petrv2/N4C32/petrv2_bs1_fp16_DP.sh
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Original file line number Diff line number Diff line change
@@ -0,0 +1,17 @@
model_item=petrv2
bs_item=1
fp_item=fp16
run_process_type=MultiP
run_mode=DP
device_num=N4C32
max_iter=-1
num_workers=32

node_num=${PADDLE_TRAINERS_NUM}
node_rank=${PADDLE_TRAINER_ID}
master_addr=${POD_0_IP}
master_port=14333

sed -i '/set\ -xe/d' run_benchmark.sh
bash PrepareEnv.sh ${model_item};
bash run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_mode} ${device_num} ${max_iter} ${num_workers} ${node_num} ${node_rank} ${master_addr} ${master_port} 2>&1;
17 changes: 17 additions & 0 deletions frame_benchmark/pytorch/dynamic/Paddle3D/scripts/petrv2/N4C32/petrv2_bs1_fp32_DP.sh
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Original file line number Diff line number Diff line change
@@ -0,0 +1,17 @@
model_item=petrv2
bs_item=1
fp_item=fp32
run_process_type=MultiP
run_mode=DP
device_num=N4C32
max_iter=-1
num_workers=32

node_num=${PADDLE_TRAINERS_NUM}
node_rank=${PADDLE_TRAINER_ID}
master_addr=${POD_0_IP}
master_port=14333

sed -i '/set\ -xe/d' run_benchmark.sh
bash PrepareEnv.sh ${model_item};
bash run_benchmark.sh ${model_item} ${bs_item} ${fp_item} ${run_mode} ${device_num} ${max_iter} ${num_workers} ${node_num} ${node_rank} ${master_addr} ${master_port} 2>&1;
1 change: 1 addition & 0 deletions frame_benchmark/pytorch/dynamic/Paddle3D/scripts/petrv2/benchmark_common/analysis_log.py
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Expand Up @@ -55,6 +55,7 @@ def analyze(model_name, batch_size, log_file, res_log_file, device_num):
"frame_version": os.getenv('frame_version'),
}
json_info = json.dumps(info)
print(json_info)
with open(res_log_file, "w") as of:
of.write(json_info)

Expand Down
15 changes: 13 additions & 2 deletions frame_benchmark/pytorch/dynamic/Paddle3D/scripts/petrv2/benchmark_common/run_benchmark.sh
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Expand Up @@ -17,6 +17,13 @@ function _set_params(){
max_iter=${6:-"100"} # （可选）需保证模型执行时间在5分钟内，需要修改代码提前中断的直接提PR 合入套件 或是max_epoch
num_workers=${7:-"4"} # (可选)

# Added for distributed training
node_num=${8:-"2"} #（可选） 节点数量
node_rank=${9:-"0"} # (可选) 节点rank
master_addr=${10:-"127.0.0.1"} # (可选) 主节点ip地址
master_port=${11:-"1928"} # (可选) 主节点端口号
# Added for distributed training

# 以下为通用拼接log路径，无特殊可不用修改
model_name=${model_item}_bs${base_batch_size}_${fp_item}_${run_mode} # (必填) 切格式不要改动,与平台页面展示对齐
device=${CUDA_VISIBLE_DEVICES//,/ }
Expand All @@ -41,6 +48,7 @@ function _analysis_log(){
python analysis_log.py ${model_item} ${base_batch_size} ${log_file} ${speed_log_file} ${device_num}
}

#N4C32) train_cmd="PYTHONPATH="$(dirname $0)/..":$PYTHONPATH ; \
function _train(){
batch_size=${base_batch_size}
echo "current ${model_name} CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES, gpus=${device_num}, batch_size=${batch_size}"
Expand All @@ -50,7 +58,10 @@ function _train(){
case ${device_num} in
N1C1) train_cmd="./tools/dist_train.sh ${train_config} 1 --work-dir ${train_options}" ;;
N1C8) train_cmd="./tools/dist_train.sh ${train_config} 8 --work-dir ${train_options}" ;;
*) echo "choose device_num(N1C1, N1C8)"; exit 1;
N4C32) train_cmd="python3 -m torch.distributed.launch --nproc_per_node=8 --nnodes=$node_num \
--node_rank=$node_rank --master_addr=$master_addr --master_port=$master_port \
$(dirname "$0")/tools/train.py ${train_config} --launcher pytorch --work-dir ${train_options}" ;;
*) echo "choose device_num(N1C1, N1C8, N4C32)"; exit 1;
esac

timeout 5m ${train_cmd} > ${log_file} 2>&1
Expand All @@ -75,4 +86,4 @@ job_bt=`date '+%Y%m%d%H%M%S'`
_train
job_et=`date '+%Y%m%d%H%M%S'`
export model_run_time=$((${job_et}-${job_bt}))
_analysis_log
_analysis_log