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--- a/tests/test_metric_common.py 2023-05-04 18:48:48.550861318 +0200
+++ b/tests/test_metric_common.py 2023-05-04 18:50:25.787364577 +0200
@@ -93,6 +93,7 @@
INTENSIVE_CALLS_PATCHER = {}
metric_name = None
+ @pytest.mark.skip(reason="disabling, depends on bert_score, bleurt, math_equivalence, coval, nltk, faiss, mauve, rouge_score, sacrebleu, sacremoses ...")
def test_load_metric(self, metric_name):
doctest.ELLIPSIS_MARKER = "[...]"
metric_module = importlib.import_module(
--- a/tests/test_hf_gcp.py 2023-05-04 19:33:31.150825303 +0200
+++ b/tests/test_hf_gcp.py 2023-05-04 19:40:08.401759538 +0200
@@ -69,6 +69,7 @@
self.assertTrue(os.path.exists(datset_info_path))
+@pytest.mark.skip(reason="require apache_beam")
@pytest.mark.integration
def test_wikipedia_frr(tmp_path_factory):
tmp_dir = tmp_path_factory.mktemp("test_hf_gcp") / "test_wikipedia_simple"
--- a/tests/test_distributed.py 2023-05-04 19:43:09.861275030 +0200
+++ b/tests/test_distributed.py 2023-05-04 19:44:17.608326722 +0200
@@ -55,6 +55,7 @@
assert len({tuple(x.values()) for ds in datasets_per_rank for x in ds}) == full_size
+@pytest.mark.skip(reason="require distributed torch")
@pytest.mark.parametrize("streaming", [False, True])
@require_torch
@pytest.mark.skipif(os.name == "nt", reason="execute_subprocess_async doesn't support windows")
@@ -76,6 +77,7 @@
execute_subprocess_async(cmd, env=os.environ.copy())
+@pytest.mark.skip(reason="require distributed torch")
@pytest.mark.parametrize(
"nproc_per_node, num_workers",
[
--- a/tests/utils.py 2023-05-06 08:43:16.251987543 +0200
+++ b/tests/utils.py 2023-05-06 08:44:24.467952870 +0200
@@ -54,8 +54,8 @@
# Audio
require_sndfile = pytest.mark.skipif(
# On Windows and OS X, soundfile installs sndfile
- find_spec("soundfile") is None or version.parse(importlib_metadata.version("soundfile")) < version.parse("0.12.0"),
- reason="test requires sndfile>=0.12.1: 'pip install \"soundfile>=0.12.1\"'; ",
+ True,
+ reason="test requires librosa",
)
# Beam
--- a/tests/features/test_audio.py 2023-05-06 09:03:58.680108142 +0200
+++ a/tests/features/test_audio.py 2023-05-06 09:05:50.463407967 +0200
@@ -57,6 +57,7 @@
assert features.arrow_schema == pa.schema({"sequence_of_audios": pa.list_(Audio().pa_type)})
+@pytest.mark.skip(reason="require librosa")
@pytest.mark.parametrize(
"build_example",
[
@@ -82,6 +82,7 @@
assert decoded_example.keys() == {"path", "array", "sampling_rate"}
+@pytest.mark.skip(reason="require librosa")
@pytest.mark.parametrize(
"build_example",
[
@@ -148,6 +149,7 @@
assert decoded_example["sampling_rate"] == 48000
+@pytest.mark.skip(reason="require librosa")
@pytest.mark.parametrize("sampling_rate", [16_000, 48_000])
def test_audio_decode_example_pcm(shared_datadir, sampling_rate):
audio_path = str(shared_datadir / "test_audio_16000.pcm")
@@ -416,6 +417,7 @@
assert column[0]["sampling_rate"] == 16000
+@pytest.mark.skip(reason="require librosa")
@pytest.mark.parametrize(
"build_data",
[
@@ -440,6 +442,7 @@
assert item["audio"].keys() == {"path", "array", "sampling_rate"}
+@pytest.mark.skip(reason="require librosa")
def test_dataset_concatenate_audio_features(shared_datadir):
# we use a different data structure between 1 and 2 to make sure they are compatible with each other
audio_path = str(shared_datadir / "test_audio_44100.wav")
@@ -453,6 +456,7 @@
assert concatenated_dataset[1]["audio"]["array"].shape == dset2[0]["audio"]["array"].shape
+@pytest.mark.skip(reason="require librosa")
def test_dataset_concatenate_nested_audio_features(shared_datadir):
# we use a different data structure between 1 and 2 to make sure they are compatible with each other
audio_path = str(shared_datadir / "test_audio_44100.wav")
@@ -616,6 +616,7 @@
assert isinstance(ds, Dataset)
+@require_sndfile
def test_dataset_with_audio_feature_undecoded(shared_datadir):
audio_path = str(shared_datadir / "test_audio_44100.wav")
data = {"audio": [audio_path]}
@@ -633,6 +634,7 @@
assert column[0] == {"path": audio_path, "bytes": None}
+@require_sndfile
def test_formatted_dataset_with_audio_feature_undecoded(shared_datadir):
audio_path = str(shared_datadir / "test_audio_44100.wav")
data = {"audio": [audio_path]}
@@ -664,6 +666,7 @@
assert column[0] == {"path": audio_path, "bytes": None}
+@require_sndfile
def test_dataset_with_audio_feature_map_undecoded(shared_datadir):
audio_path = str(shared_datadir / "test_audio_44100.wav")
data = {"audio": [audio_path]}
--- a/tests/test_metric_common.py 2023-05-06 13:20:24.496197629 +0200
+++ b/tests/test_metric_common.py 2023-05-06 13:21:09.916732417 +0200
@@ -210,6 +210,7 @@
yield
+@pytest.mark.skip(reason="require seqeval")
def test_seqeval_raises_when_incorrect_scheme():
metric = load_metric(os.path.join("metrics", "seqeval"))
wrong_scheme = "ERROR"
--- a/tests/packaged_modules/test_audiofolder.py 2023-05-06 14:00:39.560876163 +0200
+++ b/tests/packaged_modules/test_audiofolder.py 2023-05-06 14:01:26.005212423 +0200
@@ -4,7 +4,6 @@
import librosa
import numpy as np
import pytest
-import soundfile as sf
from datasets import Audio, ClassLabel, Features, Value
from datasets.data_files import DataFilesDict, get_data_patterns_locally
@@ -191,9 +190,11 @@
assert len(data_files_with_two_splits_and_metadata["test"]) == 2
return data_files_with_two_splits_and_metadata
-
+@pytest.mark.skip(reason="require soundfile")
@pytest.fixture
def data_files_with_zip_archives(tmp_path, audio_file):
+ import soundfile as sf
+
data_dir = tmp_path / "audiofolder_data_dir_with_zip_archives"
data_dir.mkdir(parents=True, exist_ok=True)
archive_dir = data_dir / "archive"
--- a/tests/test_arrow_dataset.py 2023-05-06 15:36:11.080459079 +0200
+++ b/tests/test_arrow_dataset.py 2023-05-06 15:38:07.452828528 +0200
@@ -3928,6 +3928,7 @@
)
self.assertDictEqual(features_after_cast, dset.features)
+ @pytest.mark.skip(reason="require soundfile")
def test_task_automatic_speech_recognition(self):
# Include a dummy extra column `dummy` to test we drop it correctly
features_before_cast = Features(
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