--- 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(