def predict(self, X_test):
        X_test = check_array(X_test, accept_sparse="csc", dtype=np.float64,
                             order="F")
        assert sp.isspmatrix_csc(X_test)
        assert X_test.shape[1] == len(self.w_)
        return ffm.ffm_predict(self.w0_, self.w_, self.V_, X_test)
Create a new ``BlockDeviceDeployer``.
dataset/ETHPy150Open ibayer/fastFM/fastFM/base.py/FactorizationMachine.predict--crossover with--dataset/ETHPy150Open ClusterHQ/flocker/flocker/node/agents/test/test_blockdevice.py/create_blockdevicedeployer