docstr: Tests pooling with random inputs.
docstr_tok: ["Tests","pooling","with","random","inputs","."]
code: def test_pool_random(
      self, num_input_vertices, num_output_vertices, num_features
  ):
      """Tests pooling with random inputs."""
      pool_map = 0.001 + np.random.uniform(
          size=(num_output_vertices, num_input_vertices)
      )
      data = np.random.uniform(size=(num_input_vertices, num_features))
      true_weighted = np.matmul(pool_map, data)
      true_max = np.tile(
          np.max(data, axis=0, keepdims=True), (num_output_vertices, 1)
      )
      pool_map = _dense_to_sparse(pool_map)
  
      with self.subTest(name="max"):
          pooled_max = gp.pool(data, pool_map, None, algorithm="max")
          self.assertAllClose(pooled_max, true_max)
  
      with self.subTest(name="weighted"):
          pooled_weighted = gp.pool(
              data, pool_map, None, algorithm="weighted"
          )
          self.assertAllClose(pooled_weighted, true_weighted)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  import tensorflow
  import tensorflow_graphics.geometry.convolution.graph_pooling
  from tensorflow_graphics.geometry.convolution.tests import utils_test
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 7 for calling the GraphPoolingTestPoolTests obj's underlying member method code with example usage: obj.test_pool_random(num_input_vertices, num_output_vertices, num_features) without return types