class_docstr: Representation of a kernel :math:`k: \mathcal{X}^2 \to \mathbb{R}` as an
  n-dimensional feature map :math:`\phi: \mathcal{X} \to \mathbb{R}^n` satisfying:
  :math:`k(x, x') ≈ \phi(x)^\top \phi(x')`.
code: def batch_shape(self) -> Size:
      return self.kernel.batch_shape
  
imports: from __future__ import annotations
  from typing import Optional, Union
  import torch
  from botorch.sampling.pathwise.utils import TInputTransform, TOutputTransform, TransformedModuleMixin
  from gpytorch.kernels import Kernel
  from linear_operator.operators import LinearOperator
  from torch import Size, Tensor
  from torch.nn import Module
label_desc: Use image node_id 4 for calling the KernelFeatureMap obj's underlying member method code with example usage: obj.batch_shape() and returns: self