code: def write_sample_training(tmp_dir):
      words = ["The", "players", "start", "."]
      tags = ["DT", "NN", "VBZ", "."]
      doc = Doc(English().vocab, words=words, tags=tags)
      doc_bin = DocBin()
      doc_bin.add(doc)
      train_path = f"{tmp_dir}/train.spacy"
      dev_path = f"{tmp_dir}/dev.spacy"
      doc_bin.to_disk(train_path)
      doc_bin.to_disk(dev_path)
      return train_path, dev_path
  
imports: from pathlib import Path
  import numpy
  import pytest
  import srsly
  from thinc.api import Config, get_current_ops
  from spacy import util
  from spacy.lang.en import English
  from spacy.language import DEFAULT_CONFIG_PATH, DEFAULT_CONFIG_PRETRAIN_PATH
  from spacy.ml.models.multi_task import create_pretrain_vectors
  from spacy.tokens import Doc, DocBin
  from spacy.training.initialize import init_nlp
  from spacy.training.loop import train
  from spacy.training.pretrain import pretrain
  from spacy.vectors import Vectors
  from spacy.vocab import Vocab
  from ..util import make_tempdir
label_desc: Use image node_id 9 for calling a global function with example usage: write_sample_training(tmp_dir) and returns: train_path,  dev_path