code: def forward(self, inputs):
      n_args = len(inputs)
      # TODO(kataoka): Do not retain inputs if n_args == 1
      self.retain_inputs(tuple(range(n_args)))
  
      xp = backend.get_array_module(inputs[0])
      dtype = xp.result_type(*[x.dtype for x in inputs])
      y = _einsum(
          xp,
          dtype,
          self.in_subs,
          self.out_sub,
          *inputs,
          check_undefined_ellipsis_sum=True,
      )
      return (y,)
  
imports: import warnings
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import function_node
  from chainer import utils
  from chainer.utils import argument
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the EinSum obj's underlying member method code with example usage: obj.forward(inputs) and returns: y