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()
docstr: Network forward pass.
  
  Args:
      x (Dict[str, torch.Tensor]): network input
  
  Returns:
      Dict[str, torch.Tensor]: netowrk outputs
docstr_tok: ["Network","forward","pass",".","Args",":","x","(","Dict","[","str",",","torch.Tensor","]",")",":","network","input","Returns",":","Dict","[","str",",","torch.Tensor","]",":","netowrk","outputs"]
code: def forward(
      self, x: Dict[str, torch.Tensor]
  ) -> Dict[str, torch.Tensor]:
      """
      Network forward pass.
  
      Args:
          x (Dict[str, torch.Tensor]): network input
  
      Returns:
          Dict[str, torch.Tensor]: netowrk outputs
      """
      if isinstance(
          x["encoder_target"], (list, tuple)
      ):  # multiple targets
          prediction = [
              self.forward_one_target(
                  encoder_lengths=x["encoder_lengths"],
                  decoder_lengths=x["decoder_lengths"],
                  encoder_target=encoder_target,
              )
              for encoder_target in x["encoder_target"]
          ]
      else:  # one target
          prediction = self.forward_one_target(
              encoder_lengths=x["encoder_lengths"],
              decoder_lengths=x["decoder_lengths"],
              encoder_target=x["encoder_target"],
          )
      return self.to_network_output(prediction=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 1 for calling the Baseline obj's underlying member method code with example usage: obj.forward(x) and returns: self