class_docstr: Abstract base class for wrapper metrics.
  
  Wrapper metrics are characterized by them wrapping another metric, and forwarding all calls to the wrapped metric.
  This means that all logic regarding synchronization etc. is handled by the wrapped metric, and the wrapper metric
  should not do anything in this regard.
  
  This class therefore overwrites all methods that are related to synchronization, and does nothing in them.
  
  Additionally, the forward method is not implemented by default as custom logic is required for each wrapper metric.
docstr: Overwrite to do nothing, because the default wrapped functionality is handled by the wrapped metric.
docstr_tok: ["Overwrite","to","do","nothing",",","because","the","default","wrapped","functionality","is","handled","by","the","wrapped","metric","."]
code: def forward(self, *args: Any, **kwargs: Any) -> Any:
      """Overwrite to do nothing, because the default wrapped functionality is handled by the wrapped metric."""
      raise NotImplementedError
  
imports: from typing import Any, Callable
  from torchmetrics.metric import Metric
label_desc: Use image node_id 3 for calling the WrapperMetric obj's underlying member method code with example usage: obj.forward() without return types