examples/model_selection/TRAILS-Database-Native-Model-Selection/internal/ml/model_selection/scripts/latency_embedding_cache_concurrent.sh

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export PYTHONPATH=$PYTHONPATH:./internal/ml/model_selection
conda activate trails



########################## CPU ##############################
# this is run on cpu, only change the device==cpu for all above

# frappe
python3 ./internal/ml/model_selection/exps/micro/benchmark_filtering_latency_concurrent.py \
  --concurrency=8 \
  --embedding_cache_filtering=True \
  --tfmem=express_flow \
  --models_explore=5000 \
  --log_name=score_based \
  --search_space=mlp_sp \
  --num_layers=4 \
  --hidden_choice_len=20 \
  --base_dir=/hdd1/xingnaili/exp_data/ \
  --num_labels=2 \
  --device=cpu \
  --batch_size=32 \
  --dataset=frappe \
  --nfeat=5500 \
  --nfield=10 \
  --nemb=10 \
  --workers=0 \
  --result_dir=./internal/ml/model_selection/exp_current_filter_cache/ \
  --log_folder=log_score_time_frappe_cache

#criteo
python3 ./internal/ml/model_selection/exps/micro/benchmark_filtering_latency_concurrent.py \
  --embedding_cache_filtering=True \
  --tfmem=express_flow \
  --models_explore=5000 \
  --log_name=score_based \
  --search_space=mlp_sp \
  --num_layers=4 \
  --hidden_choice_len=10 \
  --base_dir=/hdd1/xingnaili/exp_data/ \
  --num_labels=2 \
  --device=cpu \
  --batch_size=32 \
  --dataset=criteo \
  --nfeat=2100000 \
  --nfield=39 \
  --nemb=10 \
  --workers=0 \
  --result_dir=./internal/ml/model_selection/exp_current_filter_cache/ \
  --log_folder=log_score_time_frappe_cache

# uci
python3 ./internal/ml/model_selection/exps/micro/benchmark_filtering_latency_concurrent.py \
  --embedding_cache_filtering=True \
  --tfmem=express_flow \
  --models_explore=5000 \
  --log_name=score_based \
  --search_space=mlp_sp \
  --num_layers=4 \
  --hidden_choice_len=20 \
  --base_dir=/hdd1/xingnaili/exp_data/ \
  --num_labels=2 \
  --device=cpu \
  --batch_size=32 \
  --dataset=uci_diabetes \
  --nfeat=369 \
  --nfield=43 \
  --nemb=10 \
  --workers=0 \
  --result_dir=./internal/ml/model_selection/exp_current_filter_cache/ \
  --log_folder=log_score_time_frappe_cache


# here is concurrent run but no embedding cache
#######################################################################################

# frappe
python3 ./internal/ml/model_selection/exps/micro/benchmark_filtering_latency_concurrent.py \
  --tfmem=express_flow \
  --models_explore=5000 \
  --log_name=score_based \
  --search_space=mlp_sp \
  --num_layers=4 \
  --hidden_choice_len=20 \
  --base_dir=/hdd1/xingnaili/exp_data/ \
  --num_labels=2 \
  --device=cpu \
  --batch_size=32 \
  --dataset=frappe \
  --nfeat=5500 \
  --nfield=10 \
  --nemb=10 \
  --workers=0 \
  --result_dir=./internal/ml/model_selection/exp_current_filter_no_cache/ \
  --log_folder=log_score_time_frappe_cache

#criteo
python3 ./internal/ml/model_selection/exps/micro/benchmark_filtering_latency_concurrent.py \
  --tfmem=express_flow \
  --models_explore=5000 \
  --log_name=score_based \
  --search_space=mlp_sp \
  --num_layers=4 \
  --hidden_choice_len=10 \
  --base_dir=/hdd1/xingnaili/exp_data/ \
  --num_labels=2 \
  --device=cpu \
  --batch_size=32 \
  --dataset=criteo \
  --nfeat=2100000 \
  --nfield=39 \
  --nemb=10 \
  --workers=0 \
  --result_dir=./internal/ml/model_selection/exp_current_filter_no_cache/ \
  --log_folder=log_score_time_frappe_cache

# uci
python3 ./internal/ml/model_selection/exps/micro/benchmark_filtering_latency_concurrent.py \
  --tfmem=express_flow \
  --models_explore=5000 \
  --log_name=score_based \
  --search_space=mlp_sp \
  --num_layers=4 \
  --hidden_choice_len=20 \
  --base_dir=/hdd1/xingnaili/exp_data/ \
  --num_labels=2 \
  --device=cpu \
  --batch_size=32 \
  --dataset=uci_diabetes \
  --nfeat=369 \
  --nfield=43 \
  --nemb=10 \
  --workers=0 \
  --result_dir=./internal/ml/model_selection/exp_filter_exp_current_filter_no_cachecache/ \
  --log_folder=log_score_time_frappe_cache