spacy 2.0.12 / thinc 6.10.3 crashing django on heroku

[kevinzen]

This may be a bug in my code somehow or it may be that I've run across a bug in spacy or thinc. I'm not sure yet.

I'm having an issue with v2.0.12 that I've traced into thinc. pip list shows me:

msgpack (0.5.6)
msgpack-numpy (0.4.3.1)
murmurhash (0.28.0)
regex (2017.4.5)
scikit-learn (0.19.2)
scipy (1.1.0)
spacy (2.0.12)
thinc (6.10.3)

I have code that works fine on my Mac, but fails in production. The stack trace goes into spacy and then into thinc -- and then django literally crashes. This all worked when I used an earlier version of spacy -- this has only come about since I'm attempting to upgrade to v2.0.12.

My requirements.txt file has these lines:

regex==2017.4.5
spacy==2.0.12
scikit-learn==0.19.2
scipy==1.1.0
https:/explosion/spacy-models/releases/download/en_core_web_sm-2.0.0/en_core_web_sm-2.0.0.tar.gz

The last line pulls the en_core_web_sm down during deployment. I'm doing this so I can get those models loaded on Heroku during deployment.

I then load the parser like this:

import en_core_web_sm
en_core_web_sm.load()

Then the stack trace shows the problem here in thinc:

File "spacy/language.py", line 352, in __call__
  doc = proc(doc)
File "pipeline.pyx", line 426, in spacy.pipeline.Tagger.__call__
File "pipeline.pyx", line 438, in spacy.pipeline.Tagger.predict
File "thinc/neural/_classes/model.py", line 161, in __call__
  return self.predict(x)
File "thinc/api.py", line 55, in predict
  X = layer(X)
File "thinc/neural/_classes/model.py", line 161, in __call__
  return self.predict(x)
File "thinc/api.py", line 293, in predict
  X = layer(layer.ops.flatten(seqs_in, pad=pad))
File "thinc/neural/_classes/model.py", line 161, in __call__
  eturn self.predict(x)
File "thinc/api.py", line 55, in predict
  X = layer(X)
File "thinc/neural/_classes/model.py", line 161, in __call__
  return self.predict(x)
File "thinc/neural/_classes/model.py", line 125, in predict
  y, _ = self.begin_update(X)
File "thinc/api.py", line 374, in uniqued_fwd
  Y_uniq, bp_Y_uniq = layer.begin_update(X_uniq, drop=drop)
File "thinc/api.py", line 61, in begin_update
  X, inc_layer_grad = layer.begin_update(X, drop=drop)
File "thinc/neural/_classes/layernorm.py", line 51, in begin_update
  X, backprop_child = self.child.begin_update(X, drop=0.)
File "thinc/neural/_classes/maxout.py", line 69, in begin_update
  output__boc = self.ops.batch_dot(X__bi, W)
File "gunicorn/workers/base.py", line 192, in handle_abort
  sys.exit(1)

Again -- this all works on my laptop.

Is there something wrong with how I'm loading? Or is my version of thinc out of date? If so, what should my requirements.txt file look like?

[kevinzen]

Stack overflow link: https://stackoverflow.com/questions/51686456/spacy-2-0-12-thinc-6-10-3-crashing-django-on-heroku

[kevinzen]

@honnibal - does something obvious jump out at you?

[kevinzen]

I was able to track down the underlying issue. It turns out that Heroku had simply aborted the thread because it was taking too long. I'll close this issue.

[lock]

This thread has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.