code: def __init__(
      self,
      results: List[common.Measurement],
      colorize: Colorize,
      trim_significant_figures: bool,
      highlight_warnings: bool,
  ):
      assert len({r.label for r in results}) == 1
  
      self.results = results
      self._colorize = colorize
      self._trim_significant_figures = trim_significant_figures
      self._highlight_warnings = highlight_warnings
      self.label = results[0].label
      self.time_unit, self.time_scale = common.select_unit(
          min(r.median for r in results)
      )
  
      self.row_keys = common.ordered_unique(
          [self.row_fn(i) for i in results]
      )
      self.row_keys.sort(
          key=lambda args: args[:2]
      )  # preserve stmt order
      self.column_keys = common.ordered_unique(
          [self.col_fn(i) for i in results]
      )
      self.rows, self.columns = self.populate_rows_and_columns()
  
imports: import collections
  import enum
  import itertools
  from typing import DefaultDict, List, Optional, Tuple
  from torch.utils.benchmark.utils import common
  from torch import tensor
label_desc: Use image node_id 1 to create a new Table object  with example: obj = Table(results, colorize, trim_significant_figures, highlight_warnings)