code: def predict(self, x):
      y_pred_local = self.model(x)
      data_map = {"input": y_pred_local.numpy()}
      response = self.fl_client.predict(data_map)
      return response.data.tensorMap["result"]
  
imports: import logging
  import os
  import shutil
  import tempfile
  from numpy import ndarray
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.ppml.fl.nn.fl_client import FLClient
  from bigdl.ppml.fl.nn.nn_client import NNClient
  from bigdl.ppml.fl.nn.utils import file_chunk_generate, print_file_size_in_dir, tensor_map_to_ndarray_map
  import tensorflow
  from tensorflow.keras.layers import Dense, Flatten, Conv2D
  from tensorflow.keras import Model
  from bigdl.ppml.fl.nn.generated.nn_service_pb2 import ByteChunk
  from nn_service_pb2 import LoadModelRequest, SaveModelRequest
label_desc: Use image node_id 8 for calling the TensorflowEstimator obj's underlying member method code with example usage: obj.predict(x) and returns: response