code: def _IncrementMetricsCounters(
      metric_name: str, version: str, model_type: str
  ):
      # LINT.IfChange
      metric_name = "metric_computed_%s_%s_%s" % (
          metric_name,
          version,
          model_type,
      )
      # LINT.ThenChange(../../../../learning/fairness/infra/plx/scripts/tfma_metrics_computed_tracker_macros.sql)
      metrics_counter = beam.metrics.Metrics.counter(
          constants.METRICS_NAMESPACE, metric_name
      )
      metrics_counter.inc(1)
  
file_path: model-analysis/tensorflow_model_analysis/evaluators/counter_util.py
imports: from typing import List, Set
  import apache_beam
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: _IncrementMetricsCounters(metric_name, version, model_type) without return types