code: def get_run_start_intro(
      run_call_count,
      fetches,
      feed_dict,
      tensor_filters,
      is_callable_runner=False,
  ):
      """Generate formatted intro for run-start UI.
  
      Args:
        run_call_count: (int) Run call counter.
        fetches: Fetches of the `Session.run()` call. See doc of `Session.run()`
          for more details.
        feed_dict: Feeds to the `Session.run()` call. See doc of `Session.run()`
          for more details.
        tensor_filters: (dict) A dict from tensor-filter name to tensor-filter
          callable.
        is_callable_runner: (bool) whether a runner returned by
            Session.make_callable is being run.
  
      Returns:
        (RichTextLines) Formatted intro message about the `Session.run()` call.
      """
  
      fetch_lines = common.get_flattened_names(fetches)
  
      if not feed_dict:
          feed_dict_lines = [debugger_cli_common.RichLine("  (Empty)")]
      else:
          feed_dict_lines = []
          for feed_key in feed_dict:
              feed_key_name = common.get_graph_element_name(feed_key)
              feed_dict_line = debugger_cli_common.RichLine("  ")
              feed_dict_line += debugger_cli_common.RichLine(
                  feed_key_name,
                  debugger_cli_common.MenuItem(
                      None, "pf '%s'" % feed_key_name
                  ),
              )
              # Surround the name string with quotes, because feed_key_name may contain
              # spaces in some cases, e.g., SparseTensors.
              feed_dict_lines.append(feed_dict_line)
      feed_dict_lines = (
          debugger_cli_common.rich_text_lines_from_rich_line_list(
              feed_dict_lines
          )
      )
  
      out = debugger_cli_common.RichTextLines(_HORIZONTAL_BAR)
      if is_callable_runner:
          out.append(
              "Running a runner returned by Session.make_callable()"
          )
      else:
          out.append("Session.run() call #%d:" % run_call_count)
          out.append("")
          out.append("Fetch(es):")
          out.extend(
              debugger_cli_common.RichTextLines(
                  ["  " + line for line in fetch_lines]
              )
          )
          out.append("")
          out.append("Feed dict:")
          out.extend(feed_dict_lines)
      out.append(_HORIZONTAL_BAR)
      out.append("")
      out.append(
          "Select one of the following commands to proceed ---->"
      )
  
      out.extend(
          _recommend_command(
              "run",
              "Execute the run() call with debug tensor-watching",
              create_link=True,
          )
      )
      out.extend(
          _recommend_command(
              "run -n",
              "Execute the run() call without debug tensor-watching",
              create_link=True,
          )
      )
      out.extend(
          _recommend_command(
              "run -t <T>",
              "Execute run() calls (T - 1) times without debugging, then "
              "execute run() once more with debugging and drop back to the CLI",
          )
      )
      out.extend(
          _recommend_command(
              "run -f <filter_name>",
              "Keep executing run() calls until a dumped tensor passes a given, "
              "registered filter (conditional breakpoint mode)",
          )
      )
  
      more_lines = ["    Registered filter(s):"]
      if tensor_filters:
          filter_names = []
          for filter_name in tensor_filters:
              filter_names.append(filter_name)
              command_menu_node = debugger_cli_common.MenuItem(
                  "", "run -f %s" % filter_name
              )
              more_lines.append(
                  RL("        * ") + RL(filter_name, command_menu_node)
              )
      else:
          more_lines.append("        (None)")
  
      out.extend(
          debugger_cli_common.rich_text_lines_from_rich_line_list(
              more_lines
          )
      )
  
      out.append("")
  
      out.append_rich_line(
          RL("For more details, see ")
          + RL("help.", debugger_cli_common.MenuItem("", "help"))
          + "."
      )
      out.append("")
  
      # Make main menu for the run-start intro.
      menu = debugger_cli_common.Menu()
      menu.append(debugger_cli_common.MenuItem("run", "run"))
      menu.append(debugger_cli_common.MenuItem("exit", "exit"))
      out.annotations[debugger_cli_common.MAIN_MENU_KEY] = menu
  
      return out
  
imports: import math
  import numpy
  from tensorflow.python.debug.cli import command_parser
  from tensorflow.python.debug.cli import debugger_cli_common
  from tensorflow.python.debug.cli import tensor_format
  from tensorflow.python.debug.lib import common
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import gfile
label_desc: Use image node_id 9 for calling a global function with example usage: get_run_start_intro(run_call_count, fetches, feed_dict, tensor_filters, is_callable_runner) and returns: out