code: def testHasAttributionsMetrics(self):
      specs_with_attributions = metric_specs.specs_from_metrics(
          {
              "output_name": [
                  tf.keras.metrics.MeanSquaredError("mse"),
                  attributions.TotalAttributions(),
              ]
          }
      )
      self.assertTrue(
          attributions.has_attributions_metrics(specs_with_attributions)
      )
      specs_without_attributions = metric_specs.specs_from_metrics(
          [
              tf.keras.metrics.MeanSquaredError("mse"),
          ]
      )
      self.assertFalse(
          attributions.has_attributions_metrics(
              specs_without_attributions
          )
      )
  
file_path: model-analysis/tensorflow_model_analysis/metrics/attributions_test.py
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 attributions
  from tensorflow_model_analysis.metrics import metric_specs
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
label_desc: Use image node_id 1 for calling the AttributionsTest obj's underlying member method code with example usage: obj.testHasAttributionsMetrics() without return types