class_docstr: Base metric class, that allows fields for pre-defined metrics.
class_docstr_tok: ["Base","metric","class",",","that","allows","fields","for","pre-defined","metrics","."]
docstr: Set a specific metric attribute.
docstr_tok: ["Set","a","specific","metric","attribute","."]
code: def __setattr__(self, key: str, value: Tensor) -> None:
      """Set a specific metric attribute."""
      self[key] = value
  
imports: import logging
  from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
  import numpy
  import torch
  import torch.distributed
  from torch import IntTensor, Tensor
  from torchmetrics.detection.helpers import _fix_empty_tensors, _input_validator
  from torchmetrics.metric import Metric
  from torchmetrics.utilities.data import _cumsum
  from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _PYCOCOTOOLS_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_8
  from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
label_desc: Use image node_id 2 for calling the BaseMetricResults obj's underlying member method code with example usage: obj.__setattr__(key, value) without return types