class_docstr: Mean average absolute error.
  
  Defined as ``(y_pred - target).abs()``
class_docstr_tok: ["Mean","average","absolute","error",".","Defined","as","``","(","y_pred","-","target",")",".abs","(",")","``"]
code: def loss(self, y_pred, target):
      loss = (self.to_prediction(y_pred) - target).abs()
      return loss
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import scipy.stats
  import torch
  import torch.nn.functional
  from torch.nn.utils import rnn
  from pytorch_forecasting.metrics.base_metrics import MultiHorizonMetric
  from pytorch_forecasting.utils import create_mask, unpack_sequence, unsqueeze_like
label_desc: Use image node_id 1 for calling the MAE obj's underlying member method code with example usage: obj.loss(y_pred, target) and returns: loss