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Exception during xgboost prediction: can not initialize DMatrix from DMatrix

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I trained a xgboost model in Python using the Scikit-Learn Python API, and serialized it using pickle library. I uploaded the model to ML Engine, but when I try to do online predictions, i get the following exception:

Prediction failed: Exception during xgboost prediction: can not initialize DMatrix from DMatrix

An example of the json I'm using for prediction is the following:

{  
   "instances":[  
      [  
         24.90625,
         21.6435643564356,
         20.3762376237624,
         24.3679245283019,
         30.2075471698113,
         28.0947368421053,
         16.7797359774725,
         14.9262079299572,
         17.9888028979966,
         15.3333284503293,
         19.6535308744024,
         17.1501961307627,
         0.0,
         0.0,
         0.0,
         0.0,
         0.0,
         509.0,
         497.0,
         439.0,
         427.0,
         407.0,
         1.0,
         1.0,
         1.0,
         1.0,
         1.0,
         2.0,
         23.0,
         10.0,
         58.0,
         11.0,
         20.0,
         23.3617021276596,
         23.3617021276596,
         23.3617021276596,
         23.3617021276596,
         23.3617021276596,
         23.9423076923077,
         26.3082269243683,
         23.6212606363851,
         22.6752334301282,
         27.4343583104833,
         34.0090408101173,
         11.1991944104063,
         7.33420726455092,
         8.15160392948917,
         11.4119236389594,
         17.9429092915607,
         18.0573102225845,
         32.8902876598084,
         -0.00286123032904149,
         -0.00286123032904149,
         -0.00286123032904149,
         -0.00286123032904149,
         -0.00286123032904149,
         -0.0028328611898017,
         0.0534138904223018,
         0.0534138904223018,
         0.0534138904223018,
         0.0534138904223018,
         0.0534138904223018,
         0.0531491870801522
      ]
   ]
}

I use the following code to train my model:

def _train_model(X, y):
    clf = xgb.XGBClassifier(max_depth=6,
                            learning_rate=0.01,
                            n_estimators=100,
                            n_jobs=-1)
    clf.fit(X, y)
    return clf

Where X and y are both numpy.ndarray:

Type of X: <class 'numpy.ndarray'> Type of y: <class 'numpy.ndarray'>

Also I'm using xgboost 0.72.1, Python 3.5 and ML runtime 1.9.

Any one knows what can be the source of the problem?

Thanks!

like image 553
Lukas Avatar asked Nov 27 '18 19:11

Lukas


1 Answers

Seems like the issue is due to the pickling. I was able to reproduce it and working on a fix, but meanwhile could you try exporting your classifier like below instead?

clf._Booster.save_model('./model.bst') 

That should unblock you for now. If it didn't, feel free to reach out to [email protected].

like image 188
N3da Avatar answered Oct 04 '22 03:10

N3da