class_docstr: Base class for all class accuracy plugin metrics
code: def metric_value_name(
      self, m_value: _ExtendedPluginMetricValue
  ) -> str:
      m_value_values = vars(m_value)
      add_exp = self._emit_at == "experience"
      if not add_exp:
          del m_value_values["experience_id"]
      m_value_values["class_id"] = m_value.other_info["class_id"]
  
      return generic_get_metric_name(
          default_metric_name_template(m_value_values) + "/{class_id}",
          m_value_values,
      )
  
imports: from typing import Dict, List, Set, Union, TYPE_CHECKING, Iterable, Optional
  from collections import defaultdict, OrderedDict
  import torch
  from torch import Tensor
  from avalanche.evaluation import Metric, PluginMetric, _ExtendedGenericPluginMetric, _ExtendedPluginMetricValue
  from avalanche.evaluation.metric_utils import default_metric_name_template, generic_get_metric_name
  from avalanche.evaluation.metrics import Mean
label_desc: Use image node_id 4 for calling the ClassAccuracyPluginMetric obj's underlying member method code with example usage: obj.metric_value_name(m_value) and returns: generic_get_metric_name