code: def test_explainer_api_text_outputs(tmpdir):
      input_features = [
          text_feature(
              encoder={"type": "parallel_cnn", "reduce_output": None}
          )
      ]
      output_features = [
          text_feature(output_feature=True, decoder={"type": "tagger"})
      ]
      run_test_explainer_api(
          IntegratedGradientsExplainer,
          MODEL_ECD,
          output_features,
          {},
          tmpdir,
          input_features=input_features,
      )
  
imports: import logging
  import os
  import numpy
  import pandas
  import pytest
  from ludwig.api import LudwigModel
  from ludwig.constants import BATCH_SIZE, BINARY, CATEGORY, MINIMUM_BATCH_SIZE, MODEL_ECD, MODEL_GBM, TYPE
  from ludwig.explain.captum import IntegratedGradientsExplainer
  from ludwig.explain.explainer import Explainer
  from ludwig.explain.explanation import Explanation
  from ludwig.explain.gbm import GBMExplainer
  from tests.integration_tests.utils import binary_feature, category_feature, date_feature, generate_data, image_feature, LocalTestBackend, number_feature, sequence_feature, set_feature, text_feature, timeseries_feature, vector_feature
label_desc: Use image node_id 10 for calling a global function with example usage: test_explainer_api_text_outputs(tmpdir) without return types