code: def __init__(self, sample_weight, multioutput):
      if sample_weight is not None:
          raise NotImplementedError()
      if multioutput in ["uniform_average", "raw_values"]:
          self.multioutput = multioutput
      else:
          raise ValueError("invalid multioutput argument")
  
file_path: chainer/chainer/functions/evaluation/r2_score.py
imports: from chainer import backend
  from chainer import function
  from chainer.utils import type_check
label_desc: Use image node_id 1 to create a new R2_score object from inherited base classes: function with example: obj = R2_score(sample_weight, multioutput)