class_docstr: The base class for models in Analytics Zoo.
class_docstr_tok: ["The","base","class","for","models","in","Analytics","Zoo","."]
docstr: Predict for classes. By default, label predictions start from 0.
  
  # Arguments
  x: Prediction data. A Numpy array or RDD of Sample.
  batch_size: Number of samples per batch. Default is 32.
  zero_based_label: Boolean. Whether result labels start from 0.
                    Default is True. If False, result labels start from 1.
docstr_tok: ["Predict","for","classes",".","By","default",",","label","predictions","start","from","0",".","#","Arguments","x",":","Prediction","data",".","A","Numpy","array","or","RDD","of","Sample",".","batch_size",":","Number","of","samples","per","batch",".","Default","is","32.","zero_based_label",":","Boolean",".","Whether","result","labels","start","from","0",".","Default","is","True",".","If","False",",","result","labels","start","from","1","."]
code: def predict_classes(self, x, batch_size=32, zero_based_label=True):
      """
      Predict for classes. By default, label predictions start from 0.
  
      # Arguments
      x: Prediction data. A Numpy array or RDD of Sample.
      batch_size: Number of samples per batch. Default is 32.
      zero_based_label: Boolean. Whether result labels start from 0.
                        Default is True. If False, result labels start from 1.
      """
      if isinstance(x, np.ndarray):
          data_rdd = to_sample_rdd(x, np.zeros([x.shape[0]]))
      elif isinstance(x, RDD):
          data_rdd = x
      else:
          raise TypeError(
              "Unsupported prediction data type: %s" % type(x)
          )
      return callZooFunc(
          self.bigdl_type,
          "zooModelPredictClasses",
          self.value,
          data_rdd,
          batch_size,
          zero_based_label,
      )
  
imports: from bigdl.nn.layer import Container, Layer
  from bigdl.util.common import *
  from zoo.pipeline.api.keras.engine.topology import KerasNet
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 1 for calling the ZooModel obj's underlying member method code with example usage: obj.predict_classes(x, batch_size, zero_based_label) and returns: callZooFunc