def predict_proba(self,X):
        """Get predictions."""
        pred = []
        for part in range(self.partsTest):
            start = part*len(X)//self.partsTest-self.delay*(part>0)
            stop = (part+1)*len(X)//self.partsTest
            testData = self.addDelay(X[slice(start,stop)], delay=self.delay, skip=self.skip, 
                                       jump=self.jump)[self.delay*(0 > part):]
            if self.isCNN:
                testData = testData.reshape((testData.shape[0],1,testData.shape[1],1))
            pred.append(self.model.predict_proba(testData, batch_size=512,verbose=0))
            testData = None
        pred = np.concatenate(pred)
        return pred
dataset/ETHPy150Open alexandrebarachant/Grasp-and-lift-EEG-challenge/ensembling/NeuralNet.py/NeuralNet.predict_proba/swapped operands of `>`