def METHOD_NAME(self, **kwargs) -> None:
    """Create and log the SHAP charts to the WandB run.
    For the active WandB run, logs SHAP charts, which include:
    - Scatter plot for each numerical feature.
    - Bar plot for each categorical feature.
    - Single Bar plot for the general feature importance.
    Parameters
    ----------
    **kwargs :
        Additional keyword arguments
        (see https://docs.wandb.ai/ref/python/init) to the active WandB run.
    """
    from giskard.integrations.wandb.wandb_utils import wandb_run
    from giskard.integrations.wandb.wandb_utils import _wandb_bar_plot, _wandb_general_bar_plot, _wandb_scatter_plot
    self._validate_wandb_config()
    with wandb_run(**kwargs) as run:
        try:
            charts = dict()
            # Create general SHAP feature importance plot.
            general_bar_plot = _wandb_general_bar_plot(self.explanations, list(self.feature_types.keys()))
            charts.update({f"{PanelNames.GENERAL}/general_shap_bar_plot": general_bar_plot})
            counter = {"category": 0, "numeric": 0, "text": 0}
            for t in self.feature_types.values():
                counter[t] += 1
            analytics.track(
                "wandb_integration:shap_result:shap_result",
                {
                    "wandb_run_id": run.id,
                    "cat_feat_cnt": counter["category"],
                    "num_feat_cnt": counter["numeric"],
                    "text_feat_cnt": counter["text"],
                },
            )
            # Create per-feature SHAP plots.
            for feature_name, feature_type in self.feature_types.items():
                if feature_type == "category":
                    bar_plot = _wandb_bar_plot(self.explanations, feature_name)
                    charts.update({f"{PanelNames.CATEGORICAL}/{feature_name}_shap_bar_plot": bar_plot})
                elif feature_type == "numeric":
                    scatter_plot = _wandb_scatter_plot(self.explanations, feature_name)
                    charts.update({f"{PanelNames.NUMERICAL}/{feature_name}_shap_scatter_plot": scatter_plot})
                else:
                    warning_msg = (
                        f"We do not support the wandb logging of ShapResult for text features yet. The "
                        f"SHAP plot for '{feature_name}' won't be logged into wandb."
                    )
                    analytics.track(
                        "wandb_integration:shap_result:warning:text_not_supported",
                        {
                            "wandb_run_id": run.id,
                            "warning": str(warning_msg),
                        },
                    )
                    warning(warning_msg)
        except Exception as e:
            analytics.track(
                "wandb_integration:shap_result:error:unknown",
                {
                    "wandb_run_id": run.id,
                    "error": str(e),
                },
            )
            raise ValueError(
                "An error occurred while logging the SHAP results into wandb. "
                "Please submit the traceback as a GitHub issue in the following "
                "repository for further assistance: https://github.com/Giskard-AI/giskard."
            ) from e
        # Log created plots.
        run.log(charts)