class_docstr: Product of array elements over a given axis.
class_docstr_tok: ["Product","of","array","elements","over","a","given","axis","."]
code: def check_type_forward(self, in_types):
      type_check._argname(in_types, ("x",))
      type_check.expect(in_types[0].dtype.kind == "f")
  
      if self.axis is not None:
          for axis in self.axis:
              if axis >= 0:
                  type_check.expect(
                      axis < in_types[0].ndim,
                  )
              else:
                  type_check.expect(
                      -axis - 1 < in_types[0].ndim,
                  )
  
file_path: chainer/chainer/functions/math/prod.py
imports: import numpy
  import six
  from chainer import backend
  from chainer import function_node
  import chainer.functions
  from chainer.utils import type_check
label_desc: Use image node_id 2 for calling the Prod obj's underlying member method code with example usage: obj.check_type_forward(in_types) without return types