code: def predict_step(self, batch, batch_idx, dataloader_idx: int = 0):
      with torch.no_grad():
          out = []
          for _ in range(self.inference_iteration):
              out.append(
                  self.parent_module.predict_step(
                      batch, batch_idx, dataloader_idx=dataloader_idx
                  )["preds"]
              )
  
      # BaaL expects a shape [num_samples, num_classes, num_iterations]
      return torch.stack(out).permute((1, 2, 0))
  
imports: import torch
  import flash
  from flash.core.utilities.imports import _BAAL_AVAILABLE, _BAAL_GREATER_EQUAL_1_5_2
label_desc: Use image node_id 2 for calling the InferenceMCDropoutTask obj's underlying member method code with example usage: obj.predict_step(batch, batch_idx, dataloader_idx) and returns: torch