code: def test_forward_train(self):
      out_enc = torch.randn(1, 192, 1, 25)
      tmp_dir = tempfile.TemporaryDirectory()
      max_seq_len = 25
      dict_file = osp.join(tmp_dir.name, "fake_chars.txt")
      create_dummy_dict_file(dict_file)
      dict_cfg = dict(
          type="Dictionary",
          dict_file=dict_file,
          with_start=True,
          with_end=True,
          same_start_end=True,
          with_padding=True,
          with_unknown=True,
      )
      loss_cfg = dict(type="CTCModuleLoss", letter_case="lower")
      decoder = SVTRDecoder(
          in_channels=192,
          dictionary=dict_cfg,
          module_loss=loss_cfg,
          max_seq_len=max_seq_len,
      )
      data_samples = decoder.module_loss.get_targets(self.data_info)
      output = decoder.forward_train(
          out_enc=out_enc, data_samples=data_samples
      )
      self.assertTupleEqual(tuple(output.shape), (1, max_seq_len, 39))
  
file_path: mmocr/tests/test_models/test_textrecog/test_decoders/test_svtr_decoder.py
imports: import os.path
  import tempfile
  from unittest import TestCase
  import torch
  from mmengine.structures import LabelData
  from mmocr.models.textrecog.decoders.svtr_decoder import SVTRDecoder
  from mmocr.structures import TextRecogDataSample
  from mmocr.testing import create_dummy_dict_file
label_desc: Use image node_id 3 for calling the TestSVTRDecoder obj's underlying member method code with example usage: obj.test_forward_train() without return types