class_docstr: Mean absolute error function.
class_docstr_tok: ["Mean","absolute","error","function","."]
code: def backward(self, indexes, grad_outputs):
      (gy,) = grad_outputs
      coeff = gy * gy.data.dtype.type(1.0 / self.diff.size)
      coeff = chainer.functions.broadcast_to(coeff, self.diff.shape)
      gx0 = coeff * backend.get_array_module(gy.data).sign(self.diff)
      return gx0, -gx0
  
file_path: chainer/chainer/functions/loss/mean_absolute_error.py
imports: import numpy
  import chainer
  from chainer import backend
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the MeanAbsoluteError obj's underlying member method code with example usage: obj.backward(indexes, grad_outputs) and returns: gx0,  unknown