class_docstr: Reports F1 Score for a target class.
class_docstr_tok: ["Reports","F1","Score","for","a","target","class","."]
code: def __init__(self, num_classes: int, target_class: int, name: str):
      self.target_class = target_class
      super().__init__(num_classes=num_classes, name=name)
  
imports: import gc
  import os
  import re
  from typing import Any, Dict, Optional, Tuple
  import warnings
  from absl import app
  from absl import flags
  from absl import logging
  from ml_collections.config_flags import config_flags
  import tensorflow
  import tensorflow_addons
  from deepvariant import data_providers
  from deepvariant import dv_constants
  from deepvariant import dv_utils
  from deepvariant import keras_modeling
  from deepvariant.average_model_checkpoint_patched import AverageModelCheckpointPatched
  from third_party.nucleus.io import sharded_file_utils
  from official.modeling import optimization
label_desc: Use image node_id 1 to create a new F1ScorePerClass object from inherited base classes: tfa.metrics with example: obj = F1ScorePerClass(num_classes, target_class, name)