mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-21 19:39:13 +03:00
43b960c01b
* Update with WIP * Update with WIP * Update with pipeline serialization * Update types and pipe factories * Add deep merge, tidy up and add tests * Fix pipe creation from config * Don't validate default configs on load * Update spacy/language.py Co-authored-by: Ines Montani <ines@ines.io> * Adjust factory/component meta error * Clean up factory args and remove defaults * Add test for failing empty dict defaults * Update pipeline handling and methods * provide KB as registry function instead of as object * small change in test to make functionality more clear * update example script for EL configuration * Fix typo * Simplify test * Simplify test * splitting pipes.pyx into separate files * moving default configs to each component file * fix batch_size type * removing default values from component constructors where possible (TODO: test 4725) * skip instead of xfail * Add test for config -> nlp with multiple instances * pipeline.pipes -> pipeline.pipe * Tidy up, document, remove kwargs * small cleanup/generalization for Tok2VecListener * use DEFAULT_UPSTREAM field * revert to avoid circular imports * Fix tests * Replace deprecated arg * Make model dirs require config * fix pickling of keyword-only arguments in constructor * WIP: clean up and integrate full config * Add helper to handle function args more reliably Now also includes keyword-only args * Fix config composition and serialization * Improve config debugging and add visual diff * Remove unused defaults and fix type * Remove pipeline and factories from meta * Update spacy/default_config.cfg Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Update spacy/default_config.cfg * small UX edits * avoid printing stack trace for debug CLI commands * Add support for language-specific factories * specify the section of the config which holds the model to debug * WIP: add Language.from_config * Update with language data refactor WIP * Auto-format * Add backwards-compat handling for Language.factories * Update morphologizer.pyx * Fix morphologizer * Update and simplify lemmatizers * Fix Japanese tests * Port over tagger changes * Fix Chinese and tests * Update to latest Thinc * WIP: xfail first Russian lemmatizer test * Fix component-specific overrides * fix nO for output layers in debug_model * Fix default value * Fix tests and don't pass objects in config * Fix deep merging * Fix lemma lookup data registry Only load the lookups if an entry is available in the registry (and if spacy-lookups-data is installed) * Add types * Add Vocab.from_config * Fix typo * Fix tests * Make config copying more elegant * Fix pipe analysis * Fix lemmatizers and is_base_form * WIP: move language defaults to config * Fix morphology type * Fix vocab * Remove comment * Update to latest Thinc * Add morph rules to config * Tidy up * Remove set_morphology option from tagger factory * Hack use_gpu * Move [pipeline] to top-level block and make [nlp.pipeline] list Allows separating component blocks from component order – otherwise, ordering the config would mean a changed component order, which is bad. Also allows initial config to define more components and not use all of them * Fix use_gpu and resume in CLI * Auto-format * Remove resume from config * Fix formatting and error * [pipeline] -> [components] * Fix types * Fix tagger test: requires set_morphology? Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
63 lines
2.5 KiB
Python
63 lines
2.5 KiB
Python
import pytest
|
|
from spacy.util import get_lang_class
|
|
|
|
# Only include languages with no external dependencies
|
|
# "is" seems to confuse importlib, so we're also excluding it for now
|
|
# excluded: ja, ru, th, uk, vi, zh, is
|
|
LANGUAGES = [
|
|
pytest.param("fr", marks=pytest.mark.slow()),
|
|
pytest.param("af", marks=pytest.mark.slow()),
|
|
pytest.param("ar", marks=pytest.mark.slow()),
|
|
pytest.param("bg", marks=pytest.mark.slow()),
|
|
"bn",
|
|
pytest.param("ca", marks=pytest.mark.slow()),
|
|
pytest.param("cs", marks=pytest.mark.slow()),
|
|
pytest.param("da", marks=pytest.mark.slow()),
|
|
pytest.param("de", marks=pytest.mark.slow()),
|
|
"el",
|
|
"en",
|
|
pytest.param("es", marks=pytest.mark.slow()),
|
|
pytest.param("et", marks=pytest.mark.slow()),
|
|
pytest.param("fa", marks=pytest.mark.slow()),
|
|
pytest.param("fi", marks=pytest.mark.slow()),
|
|
"fr",
|
|
pytest.param("ga", marks=pytest.mark.slow()),
|
|
pytest.param("he", marks=pytest.mark.slow()),
|
|
pytest.param("hi", marks=pytest.mark.slow()),
|
|
pytest.param("hr", marks=pytest.mark.slow()),
|
|
"hu",
|
|
pytest.param("id", marks=pytest.mark.slow()),
|
|
pytest.param("it", marks=pytest.mark.slow()),
|
|
pytest.param("kn", marks=pytest.mark.slow()),
|
|
pytest.param("lb", marks=pytest.mark.slow()),
|
|
pytest.param("lt", marks=pytest.mark.slow()),
|
|
pytest.param("lv", marks=pytest.mark.slow()),
|
|
pytest.param("nb", marks=pytest.mark.slow()),
|
|
pytest.param("nl", marks=pytest.mark.slow()),
|
|
"pl",
|
|
pytest.param("pt", marks=pytest.mark.slow()),
|
|
pytest.param("ro", marks=pytest.mark.slow()),
|
|
pytest.param("si", marks=pytest.mark.slow()),
|
|
pytest.param("sk", marks=pytest.mark.slow()),
|
|
pytest.param("sl", marks=pytest.mark.slow()),
|
|
pytest.param("sq", marks=pytest.mark.slow()),
|
|
pytest.param("sr", marks=pytest.mark.slow()),
|
|
pytest.param("sv", marks=pytest.mark.slow()),
|
|
pytest.param("ta", marks=pytest.mark.slow()),
|
|
pytest.param("te", marks=pytest.mark.slow()),
|
|
pytest.param("tl", marks=pytest.mark.slow()),
|
|
pytest.param("tr", marks=pytest.mark.slow()),
|
|
pytest.param("tt", marks=pytest.mark.slow()),
|
|
pytest.param("ur", marks=pytest.mark.slow()),
|
|
]
|
|
|
|
|
|
@pytest.mark.parametrize("lang", LANGUAGES)
|
|
def test_tokenizer_explain(lang):
|
|
tokenizer = get_lang_class(lang)().tokenizer
|
|
examples = pytest.importorskip(f"spacy.lang.{lang}.examples")
|
|
for sentence in examples.sentences:
|
|
tokens = [t.text for t in tokenizer(sentence) if not t.is_space]
|
|
debug_tokens = [t[1] for t in tokenizer.explain(sentence)]
|
|
assert tokens == debug_tokens
|