code: def _batch_sparse_eye(batch_shape, num_vertices, dtype):
      """Generate a batch of identity matrices."""
      eye = np.eye(num_vertices, dtype=dtype)
      num_batch_dims = len(batch_shape)
      expand_shape = np.concatenate(
          (
              np.ones(num_batch_dims, dtype=np.int32),
              (num_vertices, num_vertices),
          ),
          axis=0,
      )
      eye = np.reshape(eye, expand_shape)
      tile_shape = np.concatenate((batch_shape, (1, 1)), axis=0)
      return _dense_to_sparse(np.tile(eye, tile_shape))
  
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 2 for calling a global function with example usage: _batch_sparse_eye(batch_shape, num_vertices, dtype) and returns: _dense_to_sparse