code: def test_predict_dataframe(use_gpu):
      predictor = TensorflowPredictor(
          model=build_model_multi_input(), use_gpu=use_gpu
      )
  
      data_batch = pd.DataFrame(
          {"A": [0.0, 0.0, 0.0], "B": [1.0, 2.0, 3.0]}
      )
      predictions = predictor.predict(data_batch)
  
      assert len(predictions) == 3
      assert predictions.to_numpy().flatten().tolist() == [
          1.0,
          2.0,
          3.0,
      ]
  
imports: import re
  from typing import Tuple
  import numpy
  import pandas
  import pytest
  import tensorflow
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.air.util.data_batch_conversion import _convert_batch_type_to_pandas, _convert_pandas_to_batch_type
  from ray.data.preprocessor import Preprocessor
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.tensorflow import TensorflowCheckpoint, TensorflowPredictor
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
label_desc: Use image node_id 13 for calling a global function with example usage: test_predict_dataframe(use_gpu) without return types