class_docstr: Implementation of Polynomial kernel:
  
      :math:`k(x, z) = \sigma^2(\text{bias} + x \cdot z)^d.`
  
  :param torch.Tensor bias: Bias parameter of this kernel. Should be positive.
  :param int degree: Degree :math:`d` of the polynomial.
code: def forward(self, X, Z=None, diag=False):
      return self.variance * (
          (self.bias + self._dot_product(X, Z, diag)) ** self.degree
      )
  
file_path: pyro/pyro/contrib/gp/kernels/dot_product.py
imports: import torch
  from torch.distributions import constraints
  from pyro.contrib.gp.kernels.kernel import Kernel
  from pyro.nn.module import PyroParam
label_desc: Use image node_id 2 for calling the Polynomial obj's underlying member method code with example usage: obj.forward(X, Z, diag) and returns: unknown