code: def pb(name, data, display_name=None, description=None):
    
    # TODO(nickfelt): remove on-demand imports once dep situation is fixed.
    import tensorflow.compat.v1 as tf
  
    data = np.array(data)
    if data.shape != ():
      raise ValueError('Expected scalar shape for data, saw shape: %s.'
                       % data.shape)
    if data.dtype.kind not in ('b', 'i', 'u', 'f'):  # bool, int, uint, float
      raise ValueError('Cast %s to float is not supported' % data.dtype.name)
    tensor = tf.make_tensor_proto(data.astype(np.float32))
  
    if display_name is None:
      display_name = name
    summary_metadata = metadata.create_summary_metadata(
        display_name=display_name, description=description)
    tf_summary_metadata = tf.SummaryMetadata.FromString(
        summary_metadata.SerializeToString())
    summary = tf.Summary()
    summary.value.add(tag='%s/scalar_summary' % name,
                      metadata=tf_summary_metadata,
                      tensor=tensor)
    return summary
docs: Create a legacy scalar summary protobuf.
  
    Arguments:
      name: A unique name for the generated summary, including any desired
        name scopes.
      data: A rank-0 `np.array` or array-like form (so raw `int`s and
        `float`s are fine, too).
      display_name: Optional name for this summary in TensorBoard, as a
        `str`. Defaults to `name`.
      description: Optional long-form description for this summary, as a
        `str`. Markdown is supported. Defaults to empty.
  
    Returns:
      A `tf.Summary` protobuf object.