Support hfh 0.10 implicit auth (#5031)

* support hfh 0.10 implicit auth

* update tests

* Bump minimum hfh to 0.2.0 and test minimum version

* style

* fix test

* fix tests

* again

* lucain's comment

* fix ci

.github/workflows/ci.yml

@@ -38,7 +38,7 @@ jobs:
       matrix:
         test: ['unit', 'integration']
         os: [ubuntu-latest, windows-latest]
-        pyarrow_version: [latest, 6.0.1]
+        deps_versions: [latest, minimum]
     continue-on-error: ${{ matrix.test == 'integration' }}
     runs-on: ${{ matrix.os }}
     steps:
@@ -63,12 +63,12 @@ jobs:
         run: |
           pip install .[tests]
           pip install -r additional-tests-requirements.txt --no-deps
-      - name: Install latest PyArrow
-        if: ${{ matrix.pyarrow_version == 'latest' }}
-        run: pip install pyarrow --upgrade
-      - name: Install PyArrow ${{ matrix.pyarrow_version }}
-        if: ${{ matrix.pyarrow_version != 'latest' }}
-        run: pip install pyarrow==${{ matrix.pyarrow_version }}
+      - name: Install dependencies (latest versions)
+        if: ${{ matrix.deps_versions == 'latest' }}
+        run: pip install --upgrade pyarrow huggingface-hub
+      - name: Install depencencies (minimum versions)
+        if: ${{ matrix.deps_versions != 'latest' }}
+        run: pip install pyarrow==6.0.1 huggingface-hub==0.2.0 transformers
       - name: Test with pytest
         run: |
           python -m pytest -rfExX -m ${{ matrix.test }} -n 2 --dist loadfile -sv ./tests/

setup.py

@@ -85,7 +85,8 @@
     # for data streaming via http
     "aiohttp",
     # To get datasets from the Datasets Hub on huggingface.co
-    "huggingface-hub>=0.1.0,<1.0.0",
+    # minimum 0.2.0 for set_access_token
+    "huggingface-hub>=0.2.0,<1.0.0",
     # Utilities from PyPA to e.g., compare versions
     "packaging",
     "responses<0.19",

src/datasets/arrow_dataset.py

@@ -102,6 +102,7 @@
 from .tasks import TaskTemplate
 from .utils import logging
 from .utils._hf_hub_fixes import create_repo
+from .utils._hf_hub_fixes import list_repo_files as hf_api_list_repo_files
 from .utils.file_utils import _retry, cached_path, estimate_dataset_size, hf_hub_url
 from .utils.info_utils import is_small_dataset
 from .utils.py_utils import asdict, convert_file_size_to_int, unique_values
@@ -4245,7 +4246,7 @@ def shards_with_embedded_external_files(shards):
 
             shards = shards_with_embedded_external_files(shards)
 
-        files = api.list_repo_files(repo_id, repo_type="dataset", revision=branch, token=token)
+        files = hf_api_list_repo_files(api, repo_id, repo_type="dataset", revision=branch, token=token)
         data_files = [file for file in files if file.startswith("data/")]
 
         def path_in_repo(_index, shard):

src/datasets/load.py

@@ -29,7 +29,7 @@
 
 import fsspec
 import requests
-from huggingface_hub import HfApi, HfFolder
+from huggingface_hub import HfApi
 
 from . import config
 from .arrow_dataset import Dataset
@@ -62,6 +62,7 @@
 )
 from .splits import Split
 from .tasks import TaskTemplate
+from .utils._hf_hub_fixes import dataset_info as hf_api_dataset_info
 from .utils.deprecation_utils import deprecated
 from .utils.file_utils import (
     OfflineModeIsEnabled,
@@ -744,14 +745,11 @@ def __init__(
         increase_load_count(name, resource_type="dataset")
 
     def get_module(self) -> DatasetModule:
-        if isinstance(self.download_config.use_auth_token, bool):
-            token = HfFolder.get_token() if self.download_config.use_auth_token else None
-        else:
-            token = self.download_config.use_auth_token
-        hfh_dataset_info = HfApi(config.HF_ENDPOINT).dataset_info(
+        hfh_dataset_info = hf_api_dataset_info(
+            HfApi(config.HF_ENDPOINT),
             self.name,
             revision=self.revision,
-            token=token if token else "no-token",
+            use_auth_token=self.download_config.use_auth_token,
             timeout=100.0,
         )
         patterns = (
@@ -1112,14 +1110,11 @@ def dataset_module_factory(
             _raise_if_offline_mode_is_enabled()
             hf_api = HfApi(config.HF_ENDPOINT)
             try:
-                if isinstance(download_config.use_auth_token, bool):
-                    token = HfFolder.get_token() if download_config.use_auth_token else None
-                else:
-                    token = download_config.use_auth_token
-                dataset_info = hf_api.dataset_info(
+                dataset_info = hf_api_dataset_info(
+                    hf_api,
                     repo_id=path,
                     revision=revision,
-                    token=token if token else "no-token",
+                    use_auth_token=download_config.use_auth_token,
                     timeout=100.0,
                 )
             except Exception as e:  # noqa: catch any exception of hf_hub and consider that the dataset doesn't exist

src/datasets/utils/_hf_hub_fixes.py

@@ -1,7 +1,8 @@
-from typing import Optional
+from typing import List, Optional, Union
 
 import huggingface_hub
-from huggingface_hub import HfApi
+from huggingface_hub import HfApi, HfFolder
+from huggingface_hub.hf_api import DatasetInfo
 from packaging import version
 
 
@@ -99,3 +100,77 @@ def delete_repo(
             token=token,
             repo_type=repo_type,
         )
+
+
+def dataset_info(
+    hf_api: HfApi,
+    repo_id: str,
+    *,
+    revision: Optional[str] = None,
+    timeout: Optional[float] = None,
+    use_auth_token: Optional[Union[bool, str]] = None,
+) -> DatasetInfo:
+    """
+    The huggingface_hub.HfApi.dataset_info parameters changed in 0.10.0 and some of them were deprecated.
+    This function checks the huggingface_hub version to call the right parameters.
+
+    Args:
+        hf_api (`huggingface_hub.HfApi`): Hub client
+        repo_id (`str`):
+            A namespace (user or an organization) and a repo name separated
+            by a `/`.
+        revision (`str`, *optional*):
+            The revision of the dataset repository from which to get the
+            information.
+        timeout (`float`, *optional*):
+            Whether to set a timeout for the request to the Hub.
+        use_auth_token (`bool` or `str`, *optional*):
+            Whether to use the `auth_token` provided from the
+            `huggingface_hub` cli. If not logged in, a valid `auth_token`
+            can be passed in as a string.
+    Returns:
+        [`hf_api.DatasetInfo`]: The dataset repository information.
+    <Tip>
+    Raises the following errors:
+        - [`~utils.RepositoryNotFoundError`]
+            If the repository to download from cannot be found. This may be because it doesn't exist,
+            or because it is set to `private` and you do not have access.
+        - [`~utils.RevisionNotFoundError`]
+            If the revision to download from cannot be found.
+    </Tip>
+    """
+    if version.parse(huggingface_hub.__version__) < version.parse("0.10.0"):
+        if use_auth_token is False:
+            token = "no-token"
+        elif isinstance(use_auth_token, str):
+            token = use_auth_token
+        else:
+            token = HfFolder.get_token() or "no-token"
+        return hf_api.dataset_info(
+            repo_id,
+            revision=revision,
+            token=token,
+            timeout=timeout,
+        )
+    else:  # the `token` parameter is deprecated in huggingface_hub>=0.10.0
+        return hf_api.dataset_info(repo_id, revision=revision, timeout=timeout, use_auth_token=use_auth_token)
+
+
+def list_repo_files(
+    hf_api: HfApi,
+    repo_id: str,
+    revision: Optional[str] = None,
+    repo_type: Optional[str] = None,
+    token: Optional[str] = None,
+    timeout: Optional[float] = None,
+) -> List[str]:
+    """
+    The huggingface_hub.HfApi.list_repo_files parameters changed in 0.10.0 and some of them were deprecated.
+    This function checks the huggingface_hub version to call the right parameters.
+    """
+    if version.parse(huggingface_hub.__version__) < version.parse("0.10.0"):
+        return hf_api.list_repo_files(repo_id, revision=revision, repo_type=repo_type, token=token, timeout=timeout)
+    else:  # the `token` parameter is deprecated in huggingface_hub>=0.10.0
+        return hf_api.list_repo_files(
+            repo_id, revision=revision, repo_type=repo_type, use_auth_token=token, timeout=timeout
+        )

src/datasets/utils/file_utils.py

@@ -22,7 +22,9 @@
 from typing import List, Optional, Type, TypeVar, Union
 from urllib.parse import urljoin, urlparse
 
+import huggingface_hub
 import requests
+from huggingface_hub import HfFolder
 
 from .. import __version__, config
 from ..download.download_config import DownloadConfig
@@ -218,7 +220,9 @@ def cached_path(
 
 
 def get_datasets_user_agent(user_agent: Optional[Union[str, dict]] = None) -> str:
-    ua = f"datasets/{__version__}; python/{config.PY_VERSION}"
+    ua = f"datasets/{__version__}"
+    ua += f"; python/{config.PY_VERSION}"
+    ua += f"; huggingface_hub/{huggingface_hub.__version__}"
     ua += f"; pyarrow/{config.PYARROW_VERSION}"
     if config.TORCH_AVAILABLE:
         ua += f"; torch/{config.TORCH_VERSION}"
@@ -239,13 +243,13 @@ def get_authentication_headers_for_url(url: str, use_auth_token: Optional[Union[
     """Handle the HF authentication"""
     headers = {}
     if url.startswith(config.HF_ENDPOINT):
-        token = None
-        if isinstance(use_auth_token, str):
+        if use_auth_token is False:
+            token = None
+        elif isinstance(use_auth_token, str):
             token = use_auth_token
-        elif bool(use_auth_token):
-            from huggingface_hub import hf_api
+        else:
+            token = HfFolder.get_token()
 
-            token = hf_api.HfFolder.get_token()
         if token:
             headers["authorization"] = f"Bearer {token}"
     return headers

tests/test_filesystem.py

@@ -12,6 +12,7 @@
     extract_path_from_uri,
     is_remote_filesystem,
 )
+from datasets.utils._hf_hub_fixes import dataset_info as hf_api_dataset_info
 
 from .utils import require_lz4, require_zstandard
 
@@ -93,7 +94,7 @@ def test_fs_isfile(protocol, zip_jsonl_path, jsonl_gz_path):
 
 @pytest.mark.integration
 def test_hf_filesystem(hf_token, hf_api, hf_private_dataset_repo_txt_data, text_file):
-    repo_info = hf_api.dataset_info(hf_private_dataset_repo_txt_data, token=hf_token)
+    repo_info = hf_api_dataset_info(hf_api, hf_private_dataset_repo_txt_data, use_auth_token=hf_token)
     hffs = HfFileSystem(repo_info=repo_info, token=hf_token)
     assert sorted(hffs.glob("*")) == [".gitattributes", "data"]
     assert hffs.isdir("data")

tests/test_load.py

@@ -756,18 +756,6 @@ def test_load_dataset_streaming_csv(path_extension, streaming, csv_path, bz2_csv
     assert ds_item == {"col_1": "0", "col_2": 0, "col_3": 0.0}
 
 
-@require_pil
-@pytest.mark.integration
-@pytest.mark.parametrize("streaming", [False, True])
-def test_load_dataset_private_zipped_images(hf_private_dataset_repo_zipped_img_data, hf_token, streaming):
-    ds = load_dataset(
-        hf_private_dataset_repo_zipped_img_data, split="train", streaming=streaming, use_auth_token=hf_token
-    )
-    assert isinstance(ds, IterableDataset if streaming else Dataset)
-    ds_items = list(ds)
-    assert len(ds_items) == 2
-
-
 @pytest.mark.parametrize("streaming", [False, True])
 @pytest.mark.parametrize("data_file", ["zip_csv_path", "zip_csv_with_dir_path", "csv_path"])
 def test_load_dataset_zip_csv(data_file, streaming, zip_csv_path, zip_csv_with_dir_path, csv_path):
@@ -876,20 +864,32 @@ def assert_auth(url, *args, headers, **kwargs):
 
 @pytest.mark.integration
 def test_load_streaming_private_dataset(hf_token, hf_private_dataset_repo_txt_data):
-    with pytest.raises(FileNotFoundError):
-        load_dataset(hf_private_dataset_repo_txt_data, streaming=True)
-    ds = load_dataset(hf_private_dataset_repo_txt_data, streaming=True, use_auth_token=hf_token)
+    ds = load_dataset(hf_private_dataset_repo_txt_data, streaming=True)
     assert next(iter(ds)) is not None
 
 
 @pytest.mark.integration
 def test_load_streaming_private_dataset_with_zipped_data(hf_token, hf_private_dataset_repo_zipped_txt_data):
-    with pytest.raises(FileNotFoundError):
-        load_dataset(hf_private_dataset_repo_zipped_txt_data, streaming=True)
-    ds = load_dataset(hf_private_dataset_repo_zipped_txt_data, streaming=True, use_auth_token=hf_token)
+    ds = load_dataset(hf_private_dataset_repo_zipped_txt_data, streaming=True)
     assert next(iter(ds)) is not None
 
 
+@require_pil
+@pytest.mark.integration
+@pytest.mark.parametrize("implicit_token", [False, True])
+@pytest.mark.parametrize("streaming", [False, True])
+def test_load_dataset_private_zipped_images(
+    hf_private_dataset_repo_zipped_img_data, hf_token, streaming, implicit_token
+):
+    use_auth_token = None if implicit_token else hf_token
+    ds = load_dataset(
+        hf_private_dataset_repo_zipped_img_data, split="train", streaming=streaming, use_auth_token=use_auth_token
+    )
+    assert isinstance(ds, IterableDataset if streaming else Dataset)
+    ds_items = list(ds)
+    assert len(ds_items) == 2
+
+
 def test_load_dataset_then_move_then_reload(dataset_loading_script_dir, data_dir, tmp_path, caplog):
     cache_dir1 = tmp_path / "cache1"
     cache_dir2 = tmp_path / "cache2"

tests/test_metric_common.py

@@ -38,6 +38,9 @@
 UNSUPPORTED_ON_WINDOWS = {"code_eval"}
 _on_windows = os.name == "nt"
 
+REQUIRE_TRANSFORMERS = {"bertscore", "frugalscore", "perplexity"}
+_has_transformers = importlib.util.find_spec("transformers") is not None
+
 
 def skip_if_metric_requires_fairseq(test_case):
     @wraps(test_case)
@@ -50,6 +53,17 @@ def wrapper(self, metric_name):
     return wrapper
 
 
+def skip_if_metric_requires_transformers(test_case):
+    @wraps(test_case)
+    def wrapper(self, metric_name):
+        if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
+            self.skipTest('"test requires transformers"')
+        else:
+            test_case(self, metric_name)
+
+    return wrapper
+
+
 def skip_on_windows_if_not_windows_compatible(test_case):
     @wraps(test_case)
     def wrapper(self, metric_name):
@@ -67,7 +81,9 @@ def get_local_metric_names():
 
 
 @parameterized.named_parameters(get_local_metric_names())
-@for_all_test_methods(skip_if_metric_requires_fairseq, skip_on_windows_if_not_windows_compatible)
+@for_all_test_methods(
+    skip_if_metric_requires_fairseq, skip_if_metric_requires_transformers, skip_on_windows_if_not_windows_compatible
+)
 @local
 @pytest.mark.integration
 class LocalMetricTest(parameterized.TestCase):