code: def test_sequence_output_feature(sequence_type: str):
      output_feature_def = sequence_feature(
          decoder={
              "type": "generator",
              "max_len": SEQ_SIZE,
              "max_sequence_length": SEQ_SIZE,
              "vocab_size": VOCAB_SIZE,
          },
          input_size=VOCAB_SIZE,
      )
      output_feature_def[TYPE] = sequence_type
  
      feature_cls = (
          SequenceOutputFeature
          if sequence_type == SEQUENCE
          else TextOutputFeature
      )
      schema_cls = (
          SequenceOutputFeatureConfig
          if sequence_type == SEQUENCE
          else ECDTextOutputFeatureConfig
      )
      sequence_config = schema_cls.from_dict(output_feature_def)
      output_feature_obj = feature_cls(sequence_config, {}).to(DEVICE)
      combiner_outputs = {
          "combiner_output": torch.randn(
              [BATCH_SIZE, SEQ_SIZE, VOCAB_SIZE], dtype=torch.float32
          ).to(DEVICE)
      }
  
      text_output = output_feature_obj(combiner_outputs, {})
  
      assert LAST_HIDDEN in text_output
      assert LOGITS in text_output
      assert text_output[LOGITS].size() == torch.Size(
          [BATCH_SIZE, SEQ_SIZE, VOCAB_SIZE]
      )
  
imports: from typing import List, Tuple
  import numpy
  import pytest
  import torch
  import torchtext
  from ludwig.constants import ENCODER_OUTPUT, LAST_HIDDEN, LOGITS, SEQUENCE, TEXT, TYPE
  from ludwig.features.sequence_feature import _SequencePreprocessing, SequenceInputFeature, SequenceOutputFeature
  from ludwig.features.text_feature import TextInputFeature, TextOutputFeature
  from ludwig.schema.features.sequence_feature import SequenceInputFeatureConfig, SequenceOutputFeatureConfig
  from ludwig.schema.features.text_feature import ECDTextInputFeatureConfig, ECDTextOutputFeatureConfig
  from ludwig.utils.torch_utils import get_torch_device
  from tests.integration_tests.utils import ENCODERS, sequence_feature
label_desc: Use image node_id 3 for calling a global function with example usage: test_sequence_output_feature(sequence_type) without return types