class_docstr: Abstract two-dimensional layer that downsamples values in a kernel to a single value.
  
  Parameters
  ----------
  input_size : tuple
      the size of the input.
  output_size : tuple
      the size of the output.
  strides : matrix-like
      stride of the 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: Returns the input index corresponding to the output at `out_index`
  and the kernel index `kernel_index`.
docstr_tok: ["Returns","the","input","index","corresponding","to","the","output","at","`","out_index","`","and","the","kernel","index","`","kernel_index","`","."]
code: def get_input_index(self, out_index, kernel_index):
      """
      Returns the input index corresponding to the output at `out_index`
      and the kernel index `kernel_index`.
      """
      out_d, out_r, out_c = out_index
      for (
          candidate_kernel_index,
          input_index,
      ) in self.kernel_index_with_input_indexes(out_d, out_r, out_c):
          if kernel_index == candidate_kernel_index:
              return input_index
  
imports: import itertools
  import numpy
label_desc: Use image node_id 6 for calling the Layer2D obj's underlying member method code with example usage: obj.get_input_index(out_index, kernel_index) and returns: input_index