code: def setUp(self):
      self.inputs = tuple(
          [
              self._setup_tensor(-1, 1, shape, self.dtype)
              for shape in self.shapes
          ]
      )
      if self.dtype == numpy.float16:
          # Avoid numpy issue #10899
          self.forward_answer = numpy.einsum(
              *self._get_args(self.inputs), dtype=numpy.float64
          ).astype(self.dtype)
      else:
          self.forward_answer = numpy.einsum(
              *self._get_args(self.inputs)
          )
      self.g = self._setup_tensor(
          -1, 1, self.forward_answer.shape, self.dtype
      )
      self.gg_inputs = tuple(
          [
              self._setup_tensor(-1, 1, shape, self.dtype)
              for shape in self.shapes
          ]
      )
      self.op = lambda *xs: einsum.einsum(*self._get_args(xs))
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer.functions.math import einsum
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer import utils
label_desc: Use image node_id 1 for calling the TestEinSum obj's underlying member method code with example usage: obj.setUp() without return types