a07d174b57d3be7914fc1ce172c87ea7d487d241,tensorforce/core/optimizers/subsampling_step.py,SubsamplingStep,step,#SubsamplingStep#Any#,56

Before Change

    def step(self, arguments, **kwargs):
        arguments = arguments.copy()
        if "states" in arguments and "horizons" in arguments:
            states = arguments.pop("states")
            horizons = arguments.pop("horizons")
        else:
            states = None

After Change

                values=(tf.math.cumsum(x=horizons[:, 1], exclusive=True), horizons[:, 1]), axis=1
            )

        for name, argument in arguments.items():
            if states is None or (name != "states" and name != "horizons"):
                subsampled_arguments[name] = tf.gather(params=argument, indices=indices)

        deltas = self.optimizer.step(arguments=subsampled_arguments, **kwargs)

        return deltas

Instances