<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 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)