most_similar() not working as expected (KeyError)

[neurotroph]

How to reproduce the behaviour

Using the en_core_web_lg model, I try to find the most similar word(s) for a given word or word vector:

import spacy
import numpy as np

nlp = spacy.load("en_core_web_lg")
tvec = nlp(u"dog").vector
# According to documentation in the source code (https:/explosion/spaCy/blob/3141e04822a8c40e0d64e51a040305ade3f66d8c/spacy/vectors.pyx#L269), an array with one or more vectors should be supplied
nlp.vocab.vectors.most_similar(np.array([tvec]))

This yields a KeyError:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "vectors.pyx", line 302, in spacy.vectors.Vectors.most_similar
KeyError: 0

Your Environment

• spaCy version: 2.0.11
• Platform: Windows-10-10.0.16299-SP0
• Python version: 3.6.6

[poke1024]

Same problem here :(

spacy 2.0.11, macOS 10.13.6, python 3.6.6

[ahmedmagdiosman]

Same issue 😭
spacy 2.0.12, Ubuntu 16.04, python 3.6

[PadenZach]

Also having this issue...

spaCy version      2.0.12         
Location           /usr/lib/python3.7/site-packages/spacy
Platform           Linux-4.19.4-arch1-1-ARCH-x86_64-with-arch-18.9-Minimal-ISO-Rolling
Python version     3.7.1          
Models             en_core_web_lg 

Tried passing the vector in several ways, and all end up giving an error.

[honnibal]

Thanks for the report, and sorry for the delay getting to this. Would you mind making a pull request with an xfail-ed test? The test should go in spacy/tests/regression.

[lock]

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