code: def build_weights_dict(self, input_shape):
      # input_shape dimensions: [color, y, x]
      output_shape = list(input_shape)
      for i in [0, 1]:
          assert (
              input_shape[i + 1] % self.pool_shape[i] == 0
          ), "maxpool shape should tile input exactly"
          output_shape[i + 1] = input_shape[i + 1] / self.pool_shape[i]
      return 0, output_shape
  
imports: from __future__ import absolute_import
  from __future__ import print_function
  from builtins import range
  import autograd.numpy
  import autograd.numpy.random
  import autograd.scipy.signal
  from autograd import grad
  import data_mnist
label_desc: Use image node_id 2 for calling the maxpool_layer obj's underlying member method code with example usage: obj.build_weights_dict(input_shape) and returns: int,  output_shape