code: def _get_boundary_locations(
      image_height: TensorLike,
      image_width: TensorLike,
      num_points_per_edge: TensorLike,
  ) -> TensorLike:
      """Compute evenly-spaced indices along edge of image."""
      image_height = tf.cast(image_height, tf.float32)
      image_width = tf.cast(image_width, tf.float32)
      y_range = tf.linspace(
          0.0, image_height - 1, num_points_per_edge + 2
      )
      x_range = tf.linspace(
          0.0, image_width - 1, num_points_per_edge + 2
      )
      ys, xs = tf.meshgrid(y_range, x_range, indexing="ij")
      is_boundary = tf.logical_or(
          tf.logical_or(tf.equal(xs, 0), tf.equal(xs, image_width - 1)),
          tf.logical_or(
              tf.equal(ys, 0), tf.equal(ys, image_height - 1)
          ),
      )
      return tf.stack(
          [
              tf.boolean_mask(ys, is_boundary),
              tf.boolean_mask(xs, is_boundary),
          ],
          axis=-1,
      )
  
file_path: addons/tensorflow_addons/image/sparse_image_warp.py
imports: import tensorflow
  from tensorflow_addons.image import dense_image_warp
  from tensorflow_addons.image import interpolate_spline
  from tensorflow_addons.image import utils
  from tensorflow_addons.utils.types import TensorLike, FloatTensorLike
label_desc: Use image node_id 3 for calling a global function with example usage: _get_boundary_locations(image_height, image_width, num_points_per_edge) and returns: tf