docstr: Tests results contain n or less tokens per cluster.
docstr_tok: ["Tests","results","contain","n","or","less","tokens","per","cluster","."]
code: def test_n_tokens_to_display(self, n_tokens_to_display):
      """Tests results contain n or less tokens per cluster."""
      config = {
          salience_clustering.SALIENCE_MAPPER_KEY: "Grad L2 Norm",
          salience_clustering.N_CLUSTERS_KEY: 2,
          salience_clustering.TOP_K_TOKENS_KEY: 2,
          salience_clustering.N_TOKENS_TO_DISPLAY_KEY: n_tokens_to_display,
      }
      result, *_ = self._call_classification_model_on_standard_input(
          config, "input_embs_grad"
      )
      top_token_results = result[salience_clustering.TOP_TOKEN_KEY][
          "input_embs_grad"
      ]
      for results_for_cluster in top_token_results:
          self.assertTrue(results_for_cluster)
          self.assertLessEqual(
              len(results_for_cluster), n_tokens_to_display
          )
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from lit_nlp.api import dataset
  from lit_nlp.api import dtypes
  from lit_nlp.components import gradient_maps
  from lit_nlp.components import lime_explainer
  from lit_nlp.components import salience_clustering
  from lit_nlp.lib import testing_utils
  import numpy
label_desc: Use image node_id 10 for calling the SalienceClusteringTest obj's underlying member method code with example usage: obj.test_n_tokens_to_display(n_tokens_to_display) without return types