code: def optimum_objective_scatter(
      optimum: float,
      num_iterations: int,
      optimum_color: Tuple[int] = COLORS.ORANGE.value,
  ) -> go.Scatter:
      """Creates a graph object for the line representing optimal objective.
  
      Args:
          optimum: value of the optimal objective
          num_iterations: how many trials were in the optimization (used to
              determine the width of the plot)
          trace_color: tuple of 3 int values representing an RGB color.
              Defaults to orange.
  
      Returns:
          go.Scatter: plotly graph objects for the optimal objective line
      """
      return go.Scatter(
          x=[1, num_iterations],
          y=[optimum] * 2,
          mode="lines",
          line={"dash": "dash", "color": rgba(optimum_color)},
          name="Optimum",
      )
  
imports: from datetime import datetime, timedelta
  from typing import Any, Dict, List, Optional, Tuple, Union
  import numpy
  import pandas
  import plotly.graph_objs
  from ax.core.experiment import Experiment
  from ax.plot.base import AxPlotConfig, AxPlotTypes
  from ax.plot.color import COLORS, DISCRETE_COLOR_SCALE, rgba
  from ax.utils.common.timeutils import timestamps_in_range
  from ax.utils.common.typeutils import not_none
  from plotly import express
  from plotly.express.colors import sample_colorscale
label_desc: Use image node_id 6 for calling a global function with example usage: optimum_objective_scatter(optimum, num_iterations, optimum_color) and returns: go