def distributed_predict(self, inputs, sc):
data_type = inputs.map(lambda x: x.__class__.__name__).first()
input_is_table = False
if data_type == "list":
input_is_table = True
jinputs = inputs.map(lambda x: Layer.check_input(x)[0])
output = callZooFunc(self.bigdl_type, "inferenceModelDistriPredict",
self.value, sc, jinputs, input_is_table)
return output.map(lambda x: KerasNet.convert_output(x))
def predict(self, inputs):
"""
Do prediction on inputs.
:param inputs: A numpy array or a list of numpy arrays or JTensor or a list of JTensors.
"""
jinputs, input_is_table = Layer.check_input(inputs)
output = callZooFunc(self.bigdl_type, "inferenceModelPredict",
self.value, jinputs, input_is_table)
return KerasNet.convert_output(output)