class_docstr: Baseline model that uses last known target value to make prediction.
  
  Example:
  
  .. code-block:: python
  
      from pytorch_forecasting import BaseModel, MAE
  
      # generating predictions
      predictions = Baseline().predict(dataloader)
  
      # calculate baseline performance in terms of mean absolute error (MAE)
      metric = MAE()
      model = Baseline()
      for x, y in dataloader:
          metric.update(model(x), y)
  
      metric.compute()
code: def to_prediction(
      self, out: Dict[str, Any], use_metric: bool = True, **kwargs
  ):
      return out.prediction
  
file_path: pytorch-forecasting/pytorch_forecasting/models/baseline.py
imports: from typing import Any, Dict
  import torch
  from pytorch_forecasting.models import BaseModel
label_desc: Use image node_id 3 for calling the Baseline obj's underlying member method code with example usage: obj.to_prediction(out, use_metric) and returns: out