code: def ensure_shape(vectors_loc):
      """Ensure that the first line of the data is the vectors shape.
      If it's not, we read in the data and output the shape as the first result,
      so that the reader doesn't have to deal with the problem.
      """
      lines = open_file(vectors_loc)
      first_line = next(lines)
      try:
          shape = tuple(int(size) for size in first_line.split()[:2])
      except ValueError:
          shape = None
      if shape is not None:
          # All good, give the data
          yield first_line
          yield from lines
      else:
          # Figure out the shape, make it the first value, and then give the
          # rest of the data.
          width = len(first_line.split()) - 1
          length = 1
          for _ in lines:
              length += 1
          yield f"{length} {width}"
          # Reading the lines in again from file. This to avoid having to
          # store all the results in a list in memory
          lines2 = open_file(vectors_loc)
          yield from lines2
          lines2.close()
      lines.close()
  
imports: import gzip
  import tarfile
  import warnings
  import zipfile
  from itertools import islice
  from pathlib import Path
  from typing import IO, TYPE_CHECKING, Any, Dict, Optional, Union
  import numpy
  import srsly
  import tqdm
  from thinc.api import Config, ConfigValidationError, fix_random_seed, set_gpu_allocator
  from ..errors import Errors, Warnings
  from ..lookups import Lookups
  from ..schemas import ConfigSchemaTraining
  from ..util import DEFAULT_OOV_PROB, OOV_RANK, ensure_path, get_sourced_components, load_model, load_model_from_config, logger, registry, resolve_dot_names
  from ..vectors import Mode
  from ..vectors import Vectors
  from .pretrain import get_tok2vec_ref
label_desc: Use image node_id 8 for calling a global function with example usage: ensure_shape(vectors_loc) without return types