pyspark/bigdl/nn/layer.py
def get_weights(self):
        """
        Get weights for this layer

        :return: list of numpy arrays which represent weight and bias
        """
        tensorWeights = callBigDlFunc(self.bigdl_type,
                              "getWeights", self.value)
        if tensorWeights is not None:
            return [tensor.to_ndarray() for tensor in tensorWeights]
        else:
            print("The layer does not have weight/bias")
            return None
def get_weights(self):
        tensorWeights = callBigDlFunc(self.bigdl_type,
                              "getWeights", self.value)
        if tensorWeights is not None:
            return [tensor.to_ndarray() for tensor in tensorWeights]
        else:
            print("The layer does not have weight/bias")
            return None
def get_weights ( self ) : tensorWeights = callBigDlFunc ( self . bigdl_type , "getWeights" , self . value ) if tensorWeights is not None : return [ tensor . to_ndarray ( ) for tensor in tensorWeights ] else : print ( "The layer does not have weight/bias" ) return None
Get weights for this layer

        :return: list of numpy arrays which represent weight and bias
Get weights for this layer