code: def forward_cpu(self, inputs):
      n, x = inputs
      global _polygamma_cpu
      if _polygamma_cpu is None:
          try:
              from scipy import special
  
              _polygamma_cpu = special.polygamma
          except ImportError:
              raise ImportError(
                  "SciPy is not available. Forward computation"
                  " of polygamma can not be done."
              )
      self.retain_inputs((0, 1))
      return (utils.force_array(_polygamma_cpu(n, x), dtype=x.dtype),)
  
file_path: chainer/chainer/functions/math/polygamma.py
imports: 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 PolyGamma obj's underlying member method code with example usage: obj.forward_cpu(inputs) and returns: utils