[Inductor] Autotuner Model Training
Labels: open source, module: inductor, module: dynamo, ciflow/inductor

```sh
# Model Training
## XGB BASELINE
python3 inductor_autotuner/model/data_gen.py --data_dir /scratch/bohanhou/fresh/data --model_type 0 --output_dir /scratch/bohanhou/fresh/new_experiments/xgb_baseline/
python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/xgb_baseline/train.py --data_dir new_experiments/xgb_baseline/ --output_dir new_experiments/xgb_baseline/
python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/xgb_baseline/train.py --data_dir new_experiments/xgb_baseline/ --output_dir new_experiments/xgb_baseline/ --full_train
python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/test.py --data-dir new_experiments/xgb_baseline/ --model-name xgb_baseline.pkl
## NN Pointwise
python3 inductor_autotuner/model/data_gen.py --data_dir /scratch/bohanhou/fresh/data --model_type 1 --output_dir /scratch/bohanhou/fresh/new_experiments/nn_pointwise/
CUDA_VISIBLE_DEVICES=0 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/nn_pointwise/train.py --data_dir new_experiments/nn_pointwise/ --output_dir new_experiments/nn_pointwise/
CUDA_VISIBLE_DEVICES=1 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/nn_pointwise/train.py --data_dir new_experiments/nn_pointwise/ --output_dir new_experiments/nn_pointwise/ --full_train
CUDA_VISIBLE_DEVICES=1 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/test.py --data-dir new_experiments/nn_pointwise/ --model-name nn_pointwise_False_1400_0.09660947996426718_0.05548533260289992.pkl
CUDA_VISIBLE_DEVICES=1 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/test.py --data-dir new_experiments/nn_pointwise/ --model-name nn_pointwise_True_1400_0.0420697318410453_0.02314407822228018.pkl
## NN L2R
python3 inductor_autotuner/model/data_gen.py --data_dir /scratch/bohanhou/fresh/data --model_type 2 --output_dir /scratch/bohanhou/fresh/new_experiments/nn_l2r/
CUDA_VISIBLE_DEVICES=2 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/nn_l2r/train.py --data_dir new_experiments/nn_l2r/ --output_dir new_experiments/nn_l2r/
CUDA_VISIBLE_DEVICES=3 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/nn_l2r/train.py --data_dir new_experiments/nn_l2r/ --output_dir new_experiments/nn_l2r/ --full_train
CUDA_VISIBLE_DEVICES=1 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/test.py --data-dir new_experiments/nn_l2r/ --model-name nn_l2r_False_700_0.011643019712382935_0.8144301772117615.pkl
## NN L2R SMALL
python3 inductor_autotuner/model/data_gen.py --data_dir /scratch/bohanhou/fresh/data --model_type 3 --output_dir /scratch/bohanhou/fresh/new_experiments/nn_l2r_small/
CUDA_VISIBLE_DEVICES=4 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/nn_l2r_small/train.py --data_dir new_experiments/nn_l2r_small/ --output_dir new_experiments/nn_l2r_small/
CUDA_VISIBLE_DEVICES=5 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/nn_l2r_small/train.py --data_dir new_experiments/nn_l2r_small/ --output_dir new_experiments/nn_l2r_small/ --full_train
CUDA_VISIBLE_DEVICES=5 python3 pytorch/benchmarks/dynamo/inductor_autotuner/model/test.py --data-dir new_experiments/nn_l2r_small/ --model-name nn_l2r_small_False_750_0.016344008184915007_0.8171488046646118.pkl
```

Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom):
* __->__ #107615
* #107489
* #107488



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