code: def forward_cpu(self, x):
      global _erf_cpu
      if _erf_cpu is None:
          try:
              from scipy import special
  
              _erf_cpu = special.erf
          except ImportError:
              warnings.warn(
                  "SciPy is not available. Forward computation of erf in CPU"
                  " can be slow without SciPy.",
                  chainer.warnings.PerformanceWarning,
              )
              _erf_cpu = numpy.vectorize(math.erf)
      self.retain_inputs((0,))
      return (utils.force_array(_erf_cpu(x[0]), dtype=x[0].dtype),)
  
file_path: chainer/chainer/functions/math/erf.py
imports: import math
  import warnings
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import function_node
  from chainer import utils
  from chainer.utils import type_check
label_desc: Use image node_id 3 for calling the Erf obj's underlying member method code with example usage: obj.forward_cpu(x) and returns: utils