code: def _create_example(pathuni):
      """Bulk of dataset processing. Converts str path to serialized tf.Example."""
      path, uni, binary_fp = pathuni
      final = {}
  
      # zoom out
      path = svg_utils.zoom_out(path)
      # make clockwise
      path = svg_utils.canonicalize(path)
  
      # render path for training
      final["rendered"] = svg_utils.per_step_render(path, absolute=True)
  
      # make path relative
      path = svg_utils.make_relative(path)
      # convert to vector
      vector = svg_utils.path_to_vector(path, categorical=True)
      # make simple vector
      vector = np.array(vector)
      vector = np.concatenate(
          [np.take(vector, [0, 4, 5, 9], axis=-1), vector[..., -6:]],
          axis=-1,
      )
  
      # count some stats
      final["seq_len"] = np.shape(vector)[0]
      final["class"] = int(svg_utils.map_uni_to_alphanum(uni))
      final["binary_fp"] = str(binary_fp)
  
      # append eos
      vector = svg_utils.append_eos(vector.tolist(), True, 10)
  
      # pad path to 51 (with eos)
      final["sequence"] = np.concatenate(
          (vector, np.zeros(((50 - final["seq_len"]), 10))), 0
      )
  
      # make pure list:
      final["rendered"] = (
          np.reshape(final["rendered"][..., 0], [64 * 64])
          .astype(np.float32)
          .tolist()
      )
      final["sequence"] = (
          np.reshape(final["sequence"], [51 * 10])
          .astype(np.float32)
          .tolist()
      )
      final["class"] = (
          np.reshape(final["class"], [1]).astype(np.int64).tolist()
      )
      final["seq_len"] = (
          np.reshape(final["seq_len"], [1]).astype(np.int64).tolist()
      )
  
      return generator_utils.to_example(final).SerializeToString()
  
imports: from absl import app
  from absl import flags
  import apache_beam
  from magenta.models.svg_vae import svg_utils
  import numpy
  from tensor2tensor.data_generators import generator_utils
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling a global function with example usage: _create_example(pathuni) and returns: generator_utils