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476455e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | import argparse
import os
from sagemaker_xgboost_container.data_utils import get_dmatrix
import xgboost as xgb
model_filename = "xgboost-model"
if __name__ == "__main__":
parser = argparse.ArgumentParser()
# Sagemaker specific arguments. Defaults are set in the environment variables.
parser.add_argument(
"--model_dir", type=str, default=os.environ.get("SM_MODEL_DIR", "/opt/ml/model")
)
parser.add_argument(
"--train",
type=str,
default=os.environ.get("SM_CHANNEL_TRAIN", "/opt/ml/input/data/abalone"),
)
args, _ = parser.parse_known_args()
dtrain = get_dmatrix(args.train, "libsvm")
params = {
"max_depth": 5,
"eta": 0.2,
"gamma": 4,
"min_child_weight": 6,
"subsample": 0.7,
"verbosity": 2,
"objective": "reg:squarederror",
"tree_method": "auto",
"predictor": "auto",
}
booster = xgb.train(params=params, dtrain=dtrain, num_boost_round=50)
booster.save_model(args.model_dir + "/" + model_filename)
def model_fn(model_dir):
"""Deserialize and return fitted model.
Note that this should have the same name as the serialized model in the _xgb_train method
"""
booster = xgb.Booster()
booster.load_model(os.path.join(model_dir, model_filename))
return booster
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