(self, trigger)
Attaches a synthetic gradient update operation to `trigger`.

        Returns a `Variable` with the same `data` as `trigger`, that during
        the backward pass will intercept gradient passing through it and use
        this gradient to update the `Synthesizer`'s estimate.

        Works only in `training` mode, otherwise just returns the input
        `trigger`.

        Returns:
            A copy of `trigger` with a synthetic gradient update operation
            attached.
Attaches a synthetic gradient update operation to `trigger`.
Attaches a synthetic gradient update operation to trigger .
def make_trigger(self, trigger):
        """Attaches a synthetic gradient update operation to `trigger`.

        Returns a `Variable` with the same `data` as `trigger`, that during
        the backward pass will intercept gradient passing through it and use
        this gradient to update the `Synthesizer`'s estimate.

        Works only in `training` mode, otherwise just returns the input
        `trigger`.

        Returns:
            A copy of `trigger` with a synthetic gradient update operation
            attached.
        """
        if self.training:
            return _SyntheticGradientUpdater.apply(
                trigger,
                self.synthesizer(trigger, _Manager.get_current_context())
            )
        else:
            return trigger
def make_trigger ( self , trigger ) : if self . training : return _SyntheticGradientUpdater . apply ( trigger , self . synthesizer ( trigger , _Manager . get_current_context ( ) ) ) else : return trigger