captum/attr/_core/layer/layer_conductance.py [335:350]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        scaled_features_tpl = tuple(
            torch.cat(
                [baseline + alpha * (input - baseline) for alpha in alphas], dim=0
            ).requires_grad_()
            for input, baseline in zip(inputs, baselines)
        )

        additional_forward_args = _format_additional_forward_args(
            additional_forward_args
        )
        # apply number of steps to additional forward args
        # currently, number of steps is applied only to additional forward arguments
        # that are nd-tensors. It is assumed that the first dimension is
        # the number of batches.
        # dim -> (#examples * #steps x additional_forward_args[0].shape[1:], ...)
        input_additional_args = (
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captum/attr/_core/neuron/neuron_conductance.py [341:356]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        scaled_features_tpl = tuple(
            torch.cat(
                [baseline + alpha * (input - baseline) for alpha in alphas], dim=0
            ).requires_grad_()
            for input, baseline in zip(inputs, baselines)
        )

        additional_forward_args = _format_additional_forward_args(
            additional_forward_args
        )
        # apply number of steps to additional forward args
        # currently, number of steps is applied only to additional forward arguments
        # that are nd-tensors. It is assumed that the first dimension is
        # the number of batches.
        # dim -> (#examples * #steps x additional_forward_args[0].shape[1:], ...)
        input_additional_args = (
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -