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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _process_health_pill_value(self, wall_time, step, device_name, output_slot, node_name, tensor_proto, node_name_set=None):
 """Creates a HealthPillEvent containing various properties of a health pill. Args: wall_time: The wall time in seconds. step: The session run step of the event. device_name: The name of the node's device. output_slot: The numeric output slot. node_name: The name of the node (without the output slot). tensor_proto: A tensor proto of data. node_name_set: An optional set of node names that are relevant. If not provided, no filtering by relevance occurs. Returns: An event_accumulator.HealthPillEvent. Or None if one could not be created. """

    if node_name_set and node_name not in node_name_set:
      # This event is not relevant.
      return None

    # Since we seek health pills for a specific step, this function
    # returns 1 health pill per node per step. The wall time is the
    # seconds since the epoch.
    elements = list(tensor_util.make_ndarray(tensor_proto))
    return HealthPillEvent(
        wall_time=wall_time,
        step=step,
        device_name=device_name,
        output_slot=output_slot,
        node_name=node_name,
        dtype=repr(tf.as_dtype(elements[12])),
        shape=elements[14:],
        value=elements)