class_docstr: Converts a loss function into a metric.
class_docstr_tok: ["Converts","a","loss","function","into","a","metric","."]
code: def __init__(self, loss, name=None, dtype=None):
      if name is None:
          name = loss.name
      super().__init__(name=name, dtype=dtype)
      self.loss = loss
  
imports: import collections
  import importlib
  import itertools
  from typing import Any, Dict, Iterable, List, Optional, Type, Tuple, Union
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.metrics import binary_confusion_matrices
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.metrics import tf_metric_accumulators
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.utils import model_util
label_desc: Use image node_id 1 to create a new _LossMetric object from inherited base classes: tf.keras.metrics with example: obj = _LossMetric(loss, name, dtype)