code: def test_category_passthrough_encoder(csv_filename):
      input_features = [category_feature(), category_feature()]
      output_features = [category_feature(output_feature=True)]
      config = {
          "input_features": input_features,
          "output_features": output_features,
          TRAINER: {"train_steps": 1},
          "defaults": {
              "category": {"encoder": {"type": "passthrough"}}
          },
      }
      generate_data_and_train(config, csv_filename)
  
imports: from contextlib import nullcontext
  from ludwig.api import LudwigModel
  from ludwig.constants import BINARY, TRAINER
  from tests.integration_tests.utils import binary_feature, category_feature, generate_data
label_desc: Use image node_id 2 for calling a global function with example usage: test_category_passthrough_encoder(csv_filename) without return types