code: def predict(self, input_datas):
      outputs = []
      for data in input_datas:
          data = paddle.to_tensor(data, "float32")
          d1, d2, d3, d4, d5, d6, d7 = self.model(data)
          outputs.append(d1.numpy())
  
      outputs = np.concatenate(outputs, 0)
  
      return outputs
  
file_path: PaddleHub/modules/image/Image_gan/style_transfer/U2Net_Portrait/module.py
imports: import os
  import paddle
  import paddle.nn
  import numpy
  from U2Net_Portrait.u2net import U2NET
  from U2Net_Portrait.processor import Processor
  from paddlehub.module.module import moduleinfo
label_desc: Use image node_id 2 for calling the U2Net_Portrait obj's underlying member method code with example usage: obj.predict(input_datas) and returns: outputs