mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-26 01:46:28 +03:00
37c7c85a86
* Support nowrap setting in util.prints * Tidy up and fix whitespace * Simplify script and use read_jsonl helper * Add JSON schemas (see #2928) * Deprecate Doc.print_tree Will be replaced with Doc.to_json, which will produce a unified format * Add Doc.to_json() method (see #2928) Converts Doc objects to JSON using the same unified format as the training data. Method also supports serializing selected custom attributes in the doc._. space. * Remove outdated test * Add write_json and write_jsonl helpers * WIP: Update spacy train * Tidy up spacy train * WIP: Use wasabi for formatting * Add GoldParse helpers for JSON format * WIP: add debug-data command * Fix typo * Add missing import * Update wasabi pin * Add missing import * 💫 Refactor CLI (#2943) To be merged into #2932. ## Description - [x] refactor CLI To use [`wasabi`](https://github.com/ines/wasabi) - [x] use [`black`](https://github.com/ambv/black) for auto-formatting - [x] add `flake8` config - [x] move all messy UD-related scripts to `cli.ud` - [x] make converters function that take the opened file and return the converted data (instead of having them handle the IO) ### Types of change enhancement ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information. * Update wasabi pin * Delete old test * Update errors * Fix typo * Tidy up and format remaining code * Fix formatting * Improve formatting of messages * Auto-format remaining code * Add tok2vec stuff to spacy.train * Fix typo * Update wasabi pin * Fix path checks for when train() is called as function * Reformat and tidy up pretrain script * Update argument annotations * Raise error if model language doesn't match lang * Document new train command
45 lines
1.2 KiB
Python
45 lines
1.2 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from spacy.cli.schemas import validate_json, get_schema
|
|
import pytest
|
|
|
|
|
|
@pytest.fixture(scope="session")
|
|
def training_schema():
|
|
return get_schema("training")
|
|
|
|
|
|
def test_json_schema_get():
|
|
schema = get_schema("training")
|
|
assert schema
|
|
with pytest.raises(ValueError):
|
|
schema = get_schema("xxx")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"data",
|
|
[
|
|
{"text": "Hello world"},
|
|
{"text": "Hello", "ents": [{"start": 0, "end": 5, "label": "TEST"}]},
|
|
],
|
|
)
|
|
def test_json_schema_training_valid(data, training_schema):
|
|
errors = validate_json([data], training_schema)
|
|
assert not errors
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"data,n_errors",
|
|
[
|
|
({"spans": []}, 1),
|
|
({"text": "Hello", "ents": [{"start": "0", "end": "5", "label": "TEST"}]}, 2),
|
|
({"text": "Hello", "ents": [{"start": 0, "end": 5}]}, 1),
|
|
({"text": "Hello", "ents": [{"start": 0, "end": 5, "label": "test"}]}, 1),
|
|
({"text": "spaCy", "tokens": [{"pos": "PROPN"}]}, 2),
|
|
],
|
|
)
|
|
def test_json_schema_training_invalid(data, n_errors, training_schema):
|
|
errors = validate_json([data], training_schema)
|
|
assert len(errors) == n_errors
|