class_docstr: Two-dimensional convolutional layer.
  
  Parameters
  ----------
  input_size : tuple
      the size of the input.
  output_size : tuple
      the size of the output..
  strides : matrix-like
      stride of the cross-correlation kernel.
  kernel : matrix-like
      the cross-correlation kernel.
  activation : str or None
      activation function name
  input_index_mapper : IndexMapper or None
      map indexes from this layer index to the input layer index size
docstr: Return the cross-correlation kernel
docstr_tok: ["Return","the","cross-correlation","kernel"]
code: def kernel(self):
      """Return the cross-correlation kernel"""
      return self.__kernel
  
imports: import itertools
  import numpy
label_desc: Use image node_id 5 for calling the ConvLayer2D obj's underlying member method code with example usage: obj.kernel() and returns: self