xgboost_release_memory.py

import numpy as np
import GPUtil
import xgboost as xgb

print("Xgboost version: {}".format(xgb.__version__))
n = 10000
m = 100
X = np.random.randn(n, m)
y = np.random.randn(n)
exp_models = []
for i in range(3):
   clf = xgb.XGBRegressor(
       tree_method='gpu_hist', eta=0.1, max_depth=6, verbosity=0)
   trained_model = clf.fit(X, y, verbose=False)
   exp_models.append(trained_model)
   print("Iteration {} device memory utilisation: {}mb".format(i, GPUtil.getGPUs()[0].memoryUsed))