code: def forward_expected(self, inputs):
      (x,) = inputs
      x_two_dim = _as_two_dim(x)
      y_expect = np.empty(len(x), dtype=self.dtype)
      for n in six.moves.range(len(x)):
          y_expect[n] = sum(map(lambda x: x * x, x_two_dim[n]))
      return (y_expect,)
  
file_path: chainer/tests/chainer_tests/functions_tests/math_tests/test_batch_l2_norm_squared.py
imports: import unittest
  import numpy
  import six
  import chainer
  from chainer import functions
  from chainer import testing
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the TestBatchL2NormSquared obj's underlying member method code with example usage: obj.forward_expected(inputs) and returns: y_expect