code: def _dense_to_sparse(data):
      """Converts a numpy array to a tf.SparseTensor."""
      indices = np.where(data)
      return tf.SparseTensor(
          np.stack(indices, axis=-1),
          data[indices],
          dense_shape=data.shape,
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import linalg
  import tensorflow
  from tensorflow_graphics.geometry.convolution import utils
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 1 for calling a global function with example usage: _dense_to_sparse(data) and returns: tf