class_docstr: Computes the Poisson metric between labels and
  predictions.
  
  Usage:
  
  ```python
  pred = torch.tensor([[1, 1], [0, 0]])
  target = torch.tensor([[0, 1], [0, 0]])
  poisson = Poisson()
  poisson(pred, target)
  assert abs(poisson.compute() - 0.49999997) < 1e-6
  ```
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code: def __init__(self):
      self.total = torch.tensor(0)
      self.poisson = torch.tensor(0)
  
imports: import torch
  from abc import ABC, abstractmethod
label_desc: Use image node_id 1 to create a new Poisson object from inherited base classes: PytorchMetric with example: obj = Poisson()