code: def get_config(self):
      # Remove config items we don't accept or they will be passed to __init__.
      base_config = super().get_config()
      return {
          "name": base_config["name"],
          "dtype": base_config["dtype"],
      }
  
imports: from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import tensorflow
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.metrics import tf_metric_wrapper
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 3 for calling the _CustomConfusionMatrixMetric obj's underlying member method code with example usage: obj.get_config() and returns: dict