code: def op(
      name, data, display_name=None, description=None, collections=None
  ):
      """Create a legacy scalar summary op.
  
      Arguments:
        name: A unique name for the generated summary node.
        data: A real numeric rank-0 `Tensor`. Must have `dtype` castable
          to `float32`.
        display_name: Optional name for this summary in TensorBoard, as a
          constant `str`. Defaults to `name`.
        description: Optional long-form description for this summary, as a
          constant `str`. Markdown is supported. Defaults to empty.
        collections: Optional list of graph collections keys. The new
          summary op is added to these collections. Defaults to
          `[Graph Keys.SUMMARIES]`.
  
      Returns:
        A TensorFlow summary op.
      """
      # TODO(nickfelt): remove on-demand imports once dep situation is fixed.
      import tensorflow.compat.v1 as tf
  
      if display_name is None:
          display_name = name
      summary_metadata = metadata.create_summary_metadata(
          display_name=display_name, description=description
      )
      with tf.name_scope(name):
          with tf.control_dependencies([tf.assert_scalar(data)]):
              return tf.summary.tensor_summary(
                  name="scalar_summary",
                  tensor=tf.cast(data, tf.float32),
                  collections=collections,
                  summary_metadata=summary_metadata,
              )
  
imports: import numpy
  from tensorboard.plugins.scalar import metadata
  from tensorboard.plugins.scalar import summary_v2
label_desc: Use image node_id 1 for calling a global function with example usage: op(name, data, display_name, description, collections) and returns: tf