2017-10-20 167 views
1

在下面的代碼中,我嘗試搜索xgboost的不同超參數。沒有使用GPU支持XGBClassifier加速

param_test1 = { 
'max_depth':list(range(3,10,2)), 
'min_child_weight':list(range(1,6,2)) 
} 
predictors = [x for x in train_data.columns if x not in ['target', 'id']] 
gsearch1 = GridSearchCV(estimator=XGBClassifier(learning_rate =0.1, n_estimators=100, max_depth=5, 
               min_child_weight=1, gamma=0, subsample=0.8, colsample_bytree=0.8, 
               objective= 'binary:logistic', n_jobs=4, scale_pos_weight=1, seed=27, 
               kvargs={'tree_method':'gpu_hist'}), 
        param_grid=param_test1, scoring='roc_auc', n_jobs=4, iid=False, cv=5, verbose=2) 
gsearch1.fit(train_data[predictors], train_data['target']) 

即使我使用kvargs={tree_method':'gpu_hist'},我在實現中沒有加速。按照nvidia-smi,該GPU並不多參與計算:

+-----------------------------------------------------------------------------+ 
| NVIDIA-SMI 375.66     Driver Version: 375.66     | 
|-------------------------------+----------------------+----------------------+ 
| GPU Name  Persistence-M| Bus-Id  Disp.A | Volatile Uncorr. ECC | 
| Fan Temp Perf Pwr:Usage/Cap|   Memory-Usage | GPU-Util Compute M. | 
|===============================+======================+======================| 
| 0 GeForce GTX 1080 Off | 0000:01:00.0  On |     N/A | 
| 0% 39C P8 10W/200W | 338MiB/8112MiB |  1%  Default | 
+-------------------------------+----------------------+----------------------+ 

+-----------------------------------------------------------------------------+ 
| Processes:              GPU Memory | 
| GPU  PID Type Process name        Usage  | 
|=============================================================================| 
| 0  961 G /usr/lib/xorg/Xorg        210MiB | 
| 0  1675 G compiz           124MiB | 
| 0  2359 G /usr/lib/firefox/firefox       2MiB | 
+-----------------------------------------------------------------------------+ 

我已經安裝了支持xgboost在Ubuntu使用以下命令的GPU:

$ git clone --recursive https://github.com/dmlc/xgboost 
$ mkdir build 
$ cd build 
$ cmake .. -DUSE_CUDA=ON 
$ make -j 

什麼是可能的原因是什麼?

+0

您確定CUDA toolkit和gpu xgboost安裝正確嗎?也可以嘗試使用'tree_method':'gpu_hist',而不將其包裝在'kvargs {}'中。與其他所有參數相同。 –

+0

@VivekKumar是的,我認爲是。關於'tree_method'參數,我認爲它沒有被定義爲正常參數,我們應該把它包含在kvargs中。 – Hossein

+0

你有什麼解決方案嗎?問題對我來說是實際的。 – QtRoS

回答