pyspark/bigdl/nn/layer.py
def stop_gradient(self, stop_layers, bigdl_type="float"):
        """
        stop the input gradient of layers that match the given ```names```
        their input gradient are not computed.
        And they will not contributed to the input gradient computation of
        layers that depend on them.
        :param stop_layers:  an array of layer names
        :param bigdl_type:
        :return:
        """
        callBigDlFunc(bigdl_type, "setStopGradient", self.value, stop_layers)
        return self
def stop_gradient(self, stop_layers, bigdl_type="float"):
        """
        stop the input gradient of layers that match the given ```names```
        their input gradient are not computed.
        And they will not contributed to the input gradient computation of
        layers that depend on them.
        :param stop_layers:  an array of layer names
        :param bigdl_type:
        :return:
        """
        callBigDlFunc(bigdl_type, "setStopGradient", self.value, stop_layers)
        return self
def stop_gradient ( self , stop_layers , bigdl_type = "float" ) : callBigDlFunc ( bigdl_type , "setStopGradient" , self . value , stop_layers ) return self
stop the input gradient of layers that match the given ```names```
        their input gradient are not computed.
        And they will not contributed to the input gradient computation of
        layers that depend on them.
        :param stop_layers:  an array of layer names
        :param bigdl_type:
        :return:
stop the input gradient of layers that match the given names their input gradient are not computed . And they will not contributed to the input gradient computation of layers that depend on them . : param stop_layers : an array of layer names : param bigdl_type : : return :