class_docstr: Analyzer for debug data from dump directories.
class_docstr_tok: ["Analyzer","for","debug","data","from","dump","directories","."]
docstr: Make a table summarizing the source files that create nodes and tensors.
  
  Args:
    source_list: List of source files and related information as a list of
      tuples (file_path, is_tf_library, num_nodes, num_tensors, num_dumps,
      first_line).
    is_tf_py_library: (`bool`) whether this table is for files that belong
      to the TensorFlow Python library.
  
  Returns:
    The table as a `debugger_cli_common.RichTextLines` object.
docstr_tok: ["Make","a","table","summarizing","the","source","files","that","create","nodes","and","tensors",".","Args",":","source_list",":","List","of","source","files","and","related","information","as","a","list","of","tuples","(","file_path",",","is_tf_library",",","num_nodes",",","num_tensors",",","num_dumps",",","first_line",")",".","is_tf_py_library",":","(","`","bool","`",")","whether","this","table","is","for","files","that","belong","to","the","TensorFlow","Python","library",".","Returns",":","The","table","as","a","`","debugger_cli_common.RichTextLines","`","object","."]
code: def _make_source_table(self, source_list, is_tf_py_library):
      """Make a table summarizing the source files that create nodes and tensors.
  
      Args:
        source_list: List of source files and related information as a list of
          tuples (file_path, is_tf_library, num_nodes, num_tensors, num_dumps,
          first_line).
        is_tf_py_library: (`bool`) whether this table is for files that belong
          to the TensorFlow Python library.
  
      Returns:
        The table as a `debugger_cli_common.RichTextLines` object.
      """
      path_head = "Source file path"
      num_nodes_head = "#(nodes)"
      num_tensors_head = "#(tensors)"
      num_dumps_head = "#(tensor dumps)"
  
      if is_tf_py_library:
          # Use color to mark files that are guessed to belong to TensorFlow Python
          # library.
          color = cli_shared.COLOR_GRAY
          lines = [RL("TensorFlow Python library file(s):", color)]
      else:
          color = cli_shared.COLOR_WHITE
          lines = [
              RL("File(s) outside TensorFlow Python library:", color)
          ]
  
      if not source_list:
          lines.append(RL("[No files.]"))
          lines.append(RL())
          return (
              debugger_cli_common.rich_text_lines_from_rich_line_list(
                  lines
              )
          )
  
      path_column_width = (
          max(max(len(item[0]) for item in source_list), len(path_head))
          + 1
      )
      num_nodes_column_width = (
          max(
              max(len(str(item[2])) for item in source_list),
              len(num_nodes_head),
          )
          + 1
      )
      num_tensors_column_width = (
          max(
              max(len(str(item[3])) for item in source_list),
              len(num_tensors_head),
          )
          + 1
      )
  
      head = RL(
          path_head + " " * (path_column_width - len(path_head)), color
      )
      head += RL(
          num_nodes_head
          + " " * (num_nodes_column_width - len(num_nodes_head)),
          color,
      )
      head += RL(
          num_tensors_head
          + " " * (num_tensors_column_width - len(num_tensors_head)),
          color,
      )
      head += RL(num_dumps_head, color)
  
      lines.append(head)
  
      for (
          file_path,
          _,
          num_nodes,
          num_tensors,
          num_dumps,
          first_line_num,
      ) in source_list:
          path_attributes = [color]
          if source_utils.is_extension_uncompiled_python_source(
              file_path
          ):
              path_attributes.append(
                  debugger_cli_common.MenuItem(
                      None, "ps %s -b %d" % (file_path, first_line_num)
                  )
              )
  
          line = RL(file_path, path_attributes)
          line += " " * (path_column_width - len(line))
          line += RL(
              str(num_nodes)
              + " " * (num_nodes_column_width - len(str(num_nodes))),
              color,
          )
          line += RL(
              str(num_tensors)
              + " "
              * (num_tensors_column_width - len(str(num_tensors))),
              color,
          )
          line += RL(str(num_dumps), color)
          lines.append(line)
      lines.append(RL())
  
      return debugger_cli_common.rich_text_lines_from_rich_line_list(
          lines
      )
  
imports: import argparse
  import copy
  import re
  from tensorflow.python.debug.cli import cli_config
  from tensorflow.python.debug.cli import cli_shared
  from tensorflow.python.debug.cli import command_parser
  from tensorflow.python.debug.cli import debugger_cli_common
  from tensorflow.python.debug.cli import evaluator
  from tensorflow.python.debug.cli import ui_factory
  from tensorflow.python.debug.lib import debug_graphs
  from tensorflow.python.debug.lib import source_utils
label_desc: Use image node_id 19 for calling the DebugAnalyzer obj's underlying member method code with example usage: obj._make_source_table(source_list, is_tf_py_library) and returns: debugger_cli_common, debugger_cli_common