class_docstr: Base class for isotropic stationary kernels, i.e. kernels that only
  depend on
  
      r = ‖x - x'‖
  
  Derived classes should implement one of:
  
      K_r2(self, r2): Returns the kernel evaluated on r² (r2), which is the
      squared scaled Euclidean distance Should operate element-wise on r2.
  
      K_r(self, r): Returns the kernel evaluated on r, which is the scaled
      Euclidean distance. Should operate element-wise on r.
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code: def K(
      self, X: TensorType, X2: Optional[TensorType] = None
  ) -> tf.Tensor:
      r2 = self.scaled_squared_euclid_dist(X, X2)
      return self.K_r2(r2)
  
imports: from typing import Any, Optional
  import numpy
  import tensorflow
  from check_shapes import check_shapes, inherit_check_shapes
  from ..base import Parameter, TensorType
  from ..utilities import positive
  from ..utilities.ops import difference_matrix, square_distance
  from .base import ActiveDims, Kernel
label_desc: Use image node_id 1 for calling the IsotropicStationary obj's underlying member method code with example usage: obj.K(X, X2) and returns: self