def test_persistence(self): # Test save/load for LDA, LocalLDAModel, DistributedLDAModel. df = self.spark.createDataFrame([ [1, Vectors.dense([0.0, 1.0])], [2, Vectors.sparse(2, {0: 1.0})], ], ["id", "features"]) # Fit model lda = LDA(k=2, seed=1, optimizer="em") distributedModel = lda.fit(df) self.assertTrue(distributedModel.isDistributed()) localModel = distributedModel.toLocal() self.assertFalse(localModel.isDistributed()) # Define paths path = tempfile.mkdtemp() lda_path = path + "/lda" dist_model_path = path + "/distLDAModel" local_model_path = path + "/localLDAModel" # Test LDA lda.save(lda_path) lda2 = LDA.load(lda_path) self._compare(lda, lda2) # Test DistributedLDAModel distributedModel.save(dist_model_path) distributedModel2 = DistributedLDAModel.load(dist_model_path) self._compare(distributedModel, distributedModel2) # Test LocalLDAModel localModel.save(local_model_path) localModel2 = LocalLDAModel.load(local_model_path) self._compare(localModel, localModel2) # Clean up try: rmtree(path) except OSError: pass
def load_lda_model(self): print('start to load LDA model:') self.model = DistributedLDAModel.load(self.lda_model_path) self.lda = LDA.load(self.lda_path) print('finished load LDA model........') return self.model