gentoo auto-resync : 07:05:2023 - 23:37:50

1 files changed, 168 insertions, 0 deletions

diff --git a/sci-libs/datasets/files/datasets-2.11.0-tests.patch b/sci-libs/datasets/files/datasets-2.11.0-tests.patch
new file mode 100644
index 000000000000..01e5d9c70e7b
--- /dev/null
+++ b/sci-libs/datasets/files/datasets-2.11.0-tests.patch
@@ -0,0 +1,168 @@
+--- 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(