  from spacy.attrs import POS, TAG, HEAD, DEP, LEMMA
  
  
  @contextlib.contextmanager
  def make_tempfile(mode="r"):
      f = tempfile.TemporaryFile(mode=mode)
      yield f
      f.close()
 
</s> remove 
def get_batch(batch_size):
    vocab = Vocab()
    docs = []
    start = 0
    for size in range(1, batch_size + 1):
        # Make the words numbers, so that they're distinct
        # across the batch, and easy to track.
        numbers = [str(i) for i in range(start, start + size)]
        docs.append(Doc(vocab, words=numbers))
        start += size
    return docs
 </s> add from .util import get_batch </s> remove from spacy.tests.util import make_tempdir
 </s> add  </s> remove         return dY
 </s> add         return [] </s> remove     tok2vec.initialize()
 </s> add     tok2vec.initialize(docs)
from spacy.vocab import Vocab

  from spacy.attrs import POS, TAG, HEAD, DEP, LEMMA
  
from spacy.vocab import Vocab

  
  @contextlib.contextmanager
  def make_tempfile(mode="r"):
      f = tempfile.TemporaryFile(mode=mode)
      yield f
      f.close()
keep add keep keep keep keep keep keep
 Train textcat with config (#5143)

* bring back default build_text_classifier method

* remove _set_dims_ hack in favor of proper dim inference

* add tok2vec initialize to unit test

* small fixes

* add unit test for various textcat config settings

* logistic output layer does not have nO

* fix window_size setting

* proper fix

* fix W initialization

* Update textcat training example

* Use ml_datasets
* Convert training data to `Example` format
* Use `n_texts` to set proportionate dev size

* fix _init renaming on latest thinc

* avoid setting a non-existing dim

* update to thinc==8.0.0a2

* add BOW and CNN defaults for easy testing

* various experiments with train_textcat script, fix softmax activation in textcat bow

* allow textcat train script to work on other datasets as well

* have dataset as a parameter

* train textcat from config, with example config

* add config for training textcat

* formatting

* fix exclusive_classes

* fixing BOW for GPU

* bump thinc to 8.0.0a3 (not published yet so CI will fail)

* add in link_vectors_to_models which got deleted

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com> 
spacy/tests/util.py