code: def test_sequence_embed_encoder(
      enc_embedding_size: int, input_sequence: torch.Tensor
  ) -> None:
      encoder_parameters["embedding_size"] = enc_embedding_size
  
      encoder_obj = get_encoder_cls(SEQUENCE, "embed")(
          **encoder_parameters
      )
  
      encoder_out = encoder_obj(input_sequence)
  
      assert (
          encoder_out[ENCODER_OUTPUT].size()[1:]
          == encoder_obj.output_shape
      )
  
file_path: ludwig/tests/integration_tests/test_sequence_encoders.py
imports: import logging
  from typing import Union
  import numpy
  import pytest
  import torch
  from ludwig.constants import ENCODER_OUTPUT, ENCODER_OUTPUT_STATE, SEQUENCE
  from ludwig.encoders.registry import get_encoder_cls
  from tests.integration_tests.utils import ENCODERS
label_desc: Use image node_id 4 for calling a global function with example usage: test_sequence_embed_encoder(enc_embedding_size, input_sequence) without return types