  
  import plac
  import random
  from pathlib import Path
  
  import spacy
  from spacy import util
  from spacy.util import minibatch, compounding
  from spacy.gold import Example, GoldParse
  
 
</s> remove import ml_datasets
 </s> add  </s> remove from spacy.ml._layers import PrecomputableAffine
from spacy.ml._layers import _backprop_precomputable_affine_padding
 </s> add from spacy.ml._precomputable_affine import PrecomputableAffine, _backprop_precomputable_affine_padding </s> remove from spacy.tests.util import make_tempdir
 </s> add 
from ml_datasets import loaders
  
  import plac
  import random
  from pathlib import Path
from ml_datasets import loaders
  
  import spacy
  from spacy import util
  from spacy.util import minibatch, compounding
  from spacy.gold import Example, GoldParse
  
keep keep 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> 
examples/training/train_textcat.py