code: def run_test_encoder_on_device(self, device):
      train, _ = create_synthetic_data(20, ptrain=1)
      output_enc = BinaryEncoder(is_target=True)
      output_enc.prepare(train["label"])
      encoded_target_values = output_enc.encode(train["label"])
      enc = PretrainedLangEncoder(
          stop_after=10,
          embed_mode=False,
          output_type=dtype.binary,
          device=device,
      )
      enc.prepare(
          train["text"],
          pd.DataFrame(),
          encoded_target_values=encoded_target_values,
      )
      self.assertEqual(
          list(enc._model.parameters())[0].device.type, device
      )
  
imports: import unittest
  import numpy
  import random
  import torch
  from torch.nn.functional import softmax
  from sklearn.metrics import accuracy_score
  from lightwood.encoder import BinaryEncoder, NumericEncoder
  from lightwood.encoder.text import PretrainedLangEncoder
  from type_infer.dtype import dtype
  import pandas
  import os
  import pathlib
label_desc: Use image node_id 4 for calling the TestPretrainedLangEncoder obj's underlying member method code with example usage: obj.run_test_encoder_on_device(device) without return types