class_docstr: Determine which FPN level each RoI in a set of RoIs should map to based
  on the heuristic in the FPN paper.
  
  Args:
      k_min (int)
      k_max (int)
      canonical_scale (int)
      canonical_level (int)
      eps (float)
code: def __init__(
      self,
      k_min: int,
      k_max: int,
      canonical_scale: int = 224,
      canonical_level: int = 4,
      eps: float = 1e-6,
  ):
      self.k_min = k_min
      self.k_max = k_max
      self.s0 = canonical_scale
      self.lvl0 = canonical_level
      self.eps = eps
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.fx
  import torchvision
  from torch import nn, Tensor
  from torchvision.ops.boxes import box_area
  from ..utils import _log_api_usage_once
  from .roi_align import roi_align
label_desc: Use image node_id 1 to create a new LevelMapper object  with example: obj = LevelMapper(k_min, k_max, canonical_scale, canonical_level, eps)