class_docstr: Root mean square error
  
  Defined as ``(y_pred - target)**2``
class_docstr_tok: ["Root","mean","square","error","Defined","as","``","(","y_pred","-","target",")","*","*","2","``"]
code: def loss(self, y_pred: Dict[str, torch.Tensor], target):
      loss = torch.pow(self.to_prediction(y_pred) - target, 2)
      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 2 for calling the RMSE obj's underlying member method code with example usage: obj.loss(y_pred, target) and returns: loss