class_docstr: A feature map defined by centering a kernel at a set of points.
docstr: Initializes a KernelEvaluationMap instance:
  
  .. code-block:: text
  
      feature_map(x) = output_transform(kernel(input_transform(x), points)).
  
  Args:
      kernel: The kernel :math:`k` used to define the feature map.
      points: A tensor passed as the kernel's second argument.
      input_transform: An optional input transform for the module.
      output_transform: An optional output transform for the module.
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code: def __init__(
      self,
      kernel: Kernel,
      points: Tensor,
      input_transform: Optional[TInputTransform] = None,
      output_transform: Optional[TOutputTransform] = None,
  ) -> None:
      r"""Initializes a KernelEvaluationMap instance:
  
      .. code-block:: text
  
          feature_map(x) = output_transform(kernel(input_transform(x), points)).
  
      Args:
          kernel: The kernel :math:`k` used to define the feature map.
          points: A tensor passed as the kernel's second argument.
          input_transform: An optional input transform for the module.
          output_transform: An optional output transform for the module.
      """
      try:
          torch.broadcast_shapes(points.shape[:-2], kernel.batch_shape)
      except RuntimeError:
          raise RuntimeError(
              f"Shape mismatch: {points.shape=}, but {kernel.batch_shape=}."
          )
  
      super().__init__()
      self.kernel = kernel
      self.points = points
      self.input_transform = input_transform
      self.output_transform = output_transform
  
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 1 to create a new KernelEvaluationMap object from inherited base classes: FeatureMap with example: obj = KernelEvaluationMap(kernel, points, input_transform, output_transform)