code: def from_outputs(cls, sess, outputs):
      dataset, inputs = TFPredictor._get_datasets_and_inputs(outputs)
      return cls(sess, outputs, inputs, dataset)
  
file_path: analytics-zoo/pyzoo/zoo/tfpark/tf_predictor.py
imports: import sys
  from zoo.pipeline.api.net.utils import find_placeholders, _check_the_same
  from zoo.tfpark.tfnet import TFNet
  from zoo.tfpark.tf_dataset import TFNdarrayDataset, check_data_compatible
  from zoo.tfpark.tf_dataset import _standarize_feature_dataset
label_desc: Use image node_id 3 for calling the TFPredictor obj's underlying member method code with example usage: obj.from_outputs(cls, sess, outputs) and returns: cls