class_docstr: The Cosine kernel. Functions drawn from a GP with this kernel are sinusoids
  (with a random phase).  The kernel equation is
  
      k(r) = σ² cos{2πd}
  
  where:
  d  is the sum of the per-dimension differences between the input points, scaled by the
  lengthscale parameter ℓ (i.e. Σᵢ [(X - X2ᵀ) / ℓ]ᵢ),
  σ² is the variance parameter.
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code: def K_d(self, d: TensorType) -> tf.Tensor:
      d = tf.reduce_sum(d, axis=-1)
      return self.variance * tf.cos(2 * np.pi * d)
  
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 Cosine obj's underlying member method code with example usage: obj.K_d(d) and returns: unknown