|
1 | 1 | from typing import Dict, Iterable, Callable
|
2 | 2 | import pytest
|
3 |
| -from thinc.api import Config |
| 3 | +from thinc.api import Config, fix_random_seed |
4 | 4 | from spacy import Language
|
5 | 5 | from spacy.util import load_model_from_config, registry, resolve_dot_names
|
6 | 6 | from spacy.schemas import ConfigSchemaTraining
|
@@ -64,8 +64,8 @@ def reader(nlp: Language):
|
64 | 64 | @pytest.mark.parametrize(
|
65 | 65 | "reader,additional_config",
|
66 | 66 | [
|
67 |
| - ("ml_datasets.imdb_sentiment.v1", {"train_limit": 10, "dev_limit": 2}), |
68 |
| - ("ml_datasets.dbpedia.v1", {"train_limit": 10, "dev_limit": 2}), |
| 67 | + ("ml_datasets.imdb_sentiment.v1", {"train_limit": 10, "dev_limit": 10}), |
| 68 | + ("ml_datasets.dbpedia.v1", {"train_limit": 10, "dev_limit": 10}), |
69 | 69 | ("ml_datasets.cmu_movies.v1", {"limit": 10, "freq_cutoff": 200, "split": 0.8}),
|
70 | 70 | ],
|
71 | 71 | )
|
@@ -93,6 +93,7 @@ def test_cat_readers(reader, additional_config):
|
93 | 93 | factory = "textcat"
|
94 | 94 | """
|
95 | 95 | config = Config().from_str(nlp_config_string)
|
| 96 | + fix_random_seed(config["training"]["seed"]) |
96 | 97 | config["corpora"]["@readers"] = reader
|
97 | 98 | config["corpora"].update(additional_config)
|
98 | 99 | nlp = load_model_from_config(config, auto_fill=True)
|
|
0 commit comments