docstr: Generates output predictions for the input samples,
  processing the samples in a batched way.
  
  # Arguments
      x: the input data, as a Numpy array or list of Numpy array for local mode.
         as RDD[Sample] for distributed mode
      is_distributed: used to control run in local or cluster. the default value is False
  # Returns
      A Numpy array or RDD[Sample] of predictions.
docstr_tok: ["Generates","output","predictions","for","the","input","samples",",","processing","the","samples","in","a","batched","way",".","#","Arguments","x",":","the","input","data",",","as","a","Numpy","array","or","list","of","Numpy","array","for","local","mode",".","as","RDD","[","Sample","]","for","distributed","mode","is_distributed",":","used","to","control","run","in","local","or","cluster",".","the","default","value","is","False","#","Returns","A","Numpy","array","or","RDD","[","Sample","]","of","predictions","."]
code: def predict(
      self, x, batch_size=None, verbose=None, is_distributed=False
  ):
      """Generates output predictions for the input samples,
      processing the samples in a batched way.
  
      # Arguments
          x: the input data, as a Numpy array or list of Numpy array for local mode.
             as RDD[Sample] for distributed mode
          is_distributed: used to control run in local or cluster. the default value is False
      # Returns
          A Numpy array or RDD[Sample] of predictions.
      """
      if batch_size or verbose:
          invalidInputError(
              False, "we don't support batch_size or verbose for now"
          )
      if is_distributed:
          if isinstance(x, np.ndarray):
              input = to_sample_rdd(x, np.zeros([x.shape[0]]))
          #  np.asarray(self.bmodel.predict(x_rdd).collect())
          elif isinstance(x, RDD):
              input = x
          return self.bmodel.predict(input)
      else:
          if isinstance(x, np.ndarray):
              return self.bmodel.predict_local(x)
      invalidInputError(False, "not supported type: %s" % x)
  
file_path: BigDL/python/dllib/src/bigdl/dllib/nn/keras/backend.py
imports: from bigdl.dllib.nn.keras.optimization import *
  from bigdl.dllib.utils.common import *
label_desc: Use image node_id 3 for calling the KerasModelWrapper obj's underlying member method code with example usage: obj.predict(x, batch_size, verbose, is_distributed) and returns: self, self