def test_deepfm_train(self): model_def = "deepfm_functional_api.deepfm_functional_api.custom_model" self._create_pserver(model_def, 2) db, test_db = get_frappe_dataset(self._batch_size) self._create_worker(1) worker_results = self._worker_train( 0, train_db=db, test_db=test_db, stop_step=100 ) acc = max([r[1] for r in worker_results]) self.assertLess(0.65, acc)
def _test_deepfm_train(self, num_ps, num_worker, stop_step): model_def = "deepfm_functional_api.deepfm_functional_api.custom_model" self._create_pserver(model_def, num_ps) db, test_db = get_frappe_dataset(self._batch_size) self._create_worker(num_worker) threads = [] for w in range(num_worker): t = Thread(target=self._worker_train, args=(w, db, test_db, stop_step)) t.start() threads.append(t) for t in threads: t.join()
def test_train_acceleration_with_embedding(self): model_def = "deepfm_functional_api.deepfm_functional_api.custom_model" self._create_pserver(model_def, 2) db, test_db = get_frappe_dataset(self._batch_size) self._create_worker(1) worker_results = self._worker_train( 0, train_db=db, test_db=test_db, stop_step=100, use_tf_function=True, ) acc = max([r[1] for r in worker_results]) self.assertLess(0.65, acc) self._close_channels()