class_docstr: The interface of state metrics for a component (e.g., optimizer, qat).
class_docstr_tok: ["The","interface","of","state","metrics","for","a","component","(","e.g.",",","optimizer",",","qat",")","."]
code: def get_metrics(self) -> Dict[str, MetricValue]:
      pass
  
imports: import abc
  import logging
  import time
  from typing import Any, Dict, List, Optional, Type, Union
  import torch
  import torch.distributed
  import torch.nn
  from torch.profiler import record_function
  from torchrec.metrics.accuracy import AccuracyMetric
  from torchrec.metrics.auc import AUCMetric
  from torchrec.metrics.auprc import AUPRCMetric
  from torchrec.metrics.calibration import CalibrationMetric
  from torchrec.metrics.ctr import CTRMetric
  from torchrec.metrics.mae import MAEMetric
  from torchrec.metrics.metrics_config import MetricsConfig, RecMetricEnum, RecMetricEnumBase, RecTaskInfo, StateMetricEnum
  from torchrec.metrics.metrics_namespace import compose_customized_metric_key, compose_metric_namespace, MetricNamespace
  from torchrec.metrics.model_utils import parse_task_model_outputs
  from torchrec.metrics.mse import MSEMetric
  from torchrec.metrics.multiclass_recall import MulticlassRecallMetric
  from torchrec.metrics.ndcg import NDCGMetric
  from torchrec.metrics.ne import NEMetric
  from torchrec.metrics.rec_metric import RecMetric, RecMetricList
  from torchrec.metrics.recall_session import RecallSessionMetric
  from torchrec.metrics.segmented_ne import SegmentedNEMetric
  from torchrec.metrics.throughput import ThroughputMetric
  from torchrec.metrics.tower_qps import TowerQPSMetric
  from torchrec.metrics.weighted_avg import WeightedAvgMetric
label_desc: Use image node_id 1 for calling the StateMetric obj's underlying member method code with example usage: obj.get_metrics() without return types