spaCy/spacy/tests/test_cli_app.py
Paul O'Leary McCann a060ed21e8 Add output arg for assemble and pretrain
Assemble and pretrain require an output argument. This commit adds
assemble testing, but not pretrain, as that requires an actual trainable
component, which is not currently in the test config.
2023-01-25 19:59:38 +09:00

230 lines
4.8 KiB
Python

import os
from pathlib import Path
import pytest
import subprocess
from typer.testing import CliRunner
import spacy
from spacy.cli._util import app
from spacy.language import Language
from spacy.tokens import DocBin
from .util import make_tempdir
def test_convert_auto():
with make_tempdir() as d_in, make_tempdir() as d_out:
for f in ["data1.iob", "data2.iob", "data3.iob"]:
Path(d_in / f).touch()
# ensure that "automatic" suffix detection works
result = CliRunner().invoke(app, ["convert", str(d_in), str(d_out)])
assert "Generated output file" in result.stdout
out_files = os.listdir(d_out)
assert len(out_files) == 3
assert "data1.spacy" in out_files
assert "data2.spacy" in out_files
assert "data3.spacy" in out_files
def test_convert_auto_conflict():
with make_tempdir() as d_in, make_tempdir() as d_out:
for f in ["data1.iob", "data2.iob", "data3.json"]:
Path(d_in / f).touch()
# ensure that "automatic" suffix detection warns when there are different file types
result = CliRunner().invoke(app, ["convert", str(d_in), str(d_out)])
assert "All input files must be same type" in result.stdout
out_files = os.listdir(d_out)
assert len(out_files) == 0
NOOP_CONFIG = """
[paths]
train = null
dev = null
vectors = null
init_tok2vec = null
[system]
seed = 0
gpu_allocator = null
[nlp]
lang = "xx"
pipeline = ["noop", "noop2"]
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
batch_size = 1000
tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
[components]
[components.noop]
factory = "noop"
[components.noop2]
factory = "noop2"
[corpora]
[corpora.dev]
@readers = "spacy.Corpus.v1"
path = ${paths.dev}
gold_preproc = false
max_length = 0
limit = 0
augmenter = null
[corpora.train]
@readers = "spacy.Corpus.v1"
path = ${paths.train}
gold_preproc = false
max_length = 0
limit = 0
augmenter = null
[training]
seed = ${system.seed}
gpu_allocator = ${system.gpu_allocator}
dropout = 0.1
accumulate_gradient = 1
patience = 1600
max_epochs = 0
max_steps = 100
eval_frequency = 200
frozen_components = []
annotating_components = []
dev_corpus = "corpora.dev"
train_corpus = "corpora.train"
before_to_disk = null
before_update = null
[training.batcher]
@batchers = "spacy.batch_by_words.v1"
discard_oversize = false
tolerance = 0.2
get_length = null
[training.batcher.size]
@schedules = "compounding.v1"
start = 100
stop = 1000
compound = 1.001
t = 0.0
[training.logger]
@loggers = "spacy.ConsoleLogger.v1"
progress_bar = false
[training.optimizer]
@optimizers = "Adam.v1"
beta1 = 0.9
beta2 = 0.999
L2_is_weight_decay = true
L2 = 0.01
grad_clip = 1.0
use_averages = false
eps = 0.00000001
learn_rate = 0.001
[training.score_weights]
[pretraining]
[initialize]
vectors = ${paths.vectors}
init_tok2vec = ${paths.init_tok2vec}
vocab_data = null
lookups = null
before_init = null
after_init = null
[initialize.components]
[initialize.tokenizer]
"""
@pytest.fixture
def data_paths():
nlp = spacy.blank("xx")
doc = nlp("ok")
with make_tempdir() as tdir:
db = DocBin()
# debug data will *fail* if there aren't enough docs
for ii in range(100):
db.add(doc)
fpath = tdir / "data.spacy"
db.to_disk(fpath)
args = [
"--paths.train",
str(fpath),
"--paths.dev",
str(fpath),
]
yield args
@pytest.fixture
def code_paths():
noop_base = """
from spacy.language import Language
@Language.component("{}")
def noop(doc):
return doc
"""
with make_tempdir() as temp_d:
# write code files to load
paths = []
for ff in ["noop", "noop2"]:
pyfile = temp_d / f"{ff}.py"
pyfile.write_text(noop_base.format(ff))
paths.append(pyfile)
args = ["--code", ",".join([str(pp) for pp in paths])]
yield args
@pytest.fixture
def noop_config():
with make_tempdir() as temp_d:
cfg = temp_d / "config.cfg"
cfg.write_text(NOOP_CONFIG)
yield cfg
@pytest.mark.parametrize(
"cmd",
[
["debug", "config"],
["debug", "data"],
["train"],
["assemble"],
],
)
def test_multi_code(cmd, code_paths, data_paths, noop_config):
# check that it fails without the code arg
output = ["."] if cmd[0] in ("pretrain", "assemble") else []
cmd = ["python", "-m", "spacy"] + cmd
result = subprocess.run([*cmd, str(noop_config), *output, *data_paths])
assert result.returncode == 1
# check that it succeeds with the code arg
result = subprocess.run(
[
*cmd,
str(noop_config),
*output,
*data_paths,
*code_paths,
]
)
assert result.returncode == 0