class_docstr: A minimal (but valid) convolutional kernel for sequences of variable
  length.
code: def diag(self, X):
      return np.array([self._f(x, x) for x in X])
  
file_path: scikit-learn/sklearn/gaussian_process/tests/_mini_sequence_kernel.py
imports: import numpy
  from sklearn.base import clone
  from sklearn.gaussian_process.kernels import GenericKernelMixin, Hyperparameter, Kernel, StationaryKernelMixin
label_desc: Use image node_id 6 for calling the MiniSeqKernel obj's underlying member method code with example usage: obj.diag(X) and returns: np