def _verify_past_future_covariates(self, past_covariates, future_covariates):
        """
        Verify that any non-None covariates comply with the model type.
        """
        invalid_covs = []
        if past_covariates is not None and not self.supports_past_covariates:
            invalid_covs.append("`past_covariates`")
        if future_covariates is not None and not self.supports_future_covariates:
            invalid_covs.append("`future_covariates`")
        if self.uses_static_covariates and not self.supports_static_covariates:
            invalid_covs.append("`static_covariates`")
        if invalid_covs:
            supported_covs = []
            if self.supports_past_covariates:
                supported_covs.append("`past_covariates`")
            if self.supports_future_covariates:
                supported_covs.append("`future_covariates`")
            if self.supports_static_covariates:
                supported_covs.append("`static_covariates`")
            if supported_covs:
                add_txt = f"It only supports {', '.join(supported_covs)}."
            else:
                add_txt = "It does not support any covariates."

            raise_log(
                ValueError(
                    f"The model does not support {', '.join(invalid_covs)}. " + add_txt
                ),
                logger=logger,
            )

        Verify that any non-None covariates comply with the model type.
        
darts/models/forecasting/torch_forecasting_model.py