updated to ignore mypy error relating to undefined models in base class

src/arc_spice/variational_pipelines/RTC_variational_pipeline.py

@@ -110,15 +110,15 @@ def variational_inference(self, x: torch.Tensor) -> tuple[dict, dict]:
         # for each model in pipeline
         for model_key, pl in self.pipeline_map.items():
             # turn on dropout for this model
-            set_dropout(model=pl.model, dropout_flag=True)
+            set_dropout(model=pl.model, dropout_flag=True)  # type: ignore[union-attr]
             torch.nn.functional.dropout = dropout_on
             # do n runs of the inference
             for run_idx in range(self.n_variational_runs):
                 var_output[model_key][run_idx] = self.func_map[model_key](
                     input_map[model_key]
                 )
             # turn off dropout for this model
-            set_dropout(model=pl.model, dropout_flag=False)
+            set_dropout(model=pl.model, dropout_flag=False)  # type: ignore[union-attr]
             torch.nn.functional.dropout = dropout_off
 
         # run metric helper functions