docstr: Tests graph pooling with identity maps.
docstr_tok: ["Tests","graph","pooling","with","identity","maps","."]
code: def test_pool_identity(
      self, batch_shape, num_vertices, num_features, data_type
  ):
      """Tests graph pooling with identity maps."""
      data_shape = np.concatenate(
          (batch_shape, (num_vertices, num_features))
      )
      data = np.random.uniform(size=data_shape).astype(data_type)
      pool_map = _batch_sparse_eye(batch_shape, num_vertices, data_type)
  
      pooled_max = gp.pool(data, pool_map, sizes=None, algorithm="max")
      pooled_weighted = gp.pool(
          data, pool_map, sizes=None, algorithm="weighted"
      )
  
      self.assertAllClose(pooled_max, data)
      self.assertAllClose(pooled_weighted, data)
  
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 4 for calling the GraphPoolingTestPoolTests obj's underlying member method code with example usage: obj.test_pool_identity(batch_shape, num_vertices, num_features, data_type) without return types