Limit to pydantic<2.x on python3.8 (#1828)

* limit pydantic version on python3.8 to 1.x

* fix

* fix comma

* light fix/refacto for keras tests

Author: Wauplin

.github/workflows/python-tests.yml

@@ -73,7 +73,6 @@ jobs:
               sudo apt update
               sudo apt install -y graphviz
               pip install .[tensorflow]
-              pip install typing_extensions>=4.8.0
               ;;
 
           esac

setup.py

@@ -30,7 +30,11 @@ def get_version() -> str:
 
 extras["inference"] = [
     "aiohttp",  # for AsyncInferenceClient
-    "pydantic>1.1,<3.0",  # match text-generation-inference v1.1.0
+    # On Python 3.8, Pydantic 2.x and tensorflow don't play well together
+    # Let's limit pydantic to 1.x for now. Since Tensorflow 2.14, Python3.8 is not supported anyway so impact should be
+    # limited. We still trigger some CIs on Python 3.8 so we need this workaround.
+    "pydantic>1.1,<3.0; python_version>'3.8'",
+    "pydantic>1.1,<2.0; python_version=='3.8'",
 ]
 
 extras["torch"] = [
@@ -76,7 +80,6 @@ def get_version() -> str:
     "types-toml",
     "types-tqdm",
     "types-urllib3",
-    "pydantic>1.1,<3.0",  # for text-generation-interface dataclasses
 ]
 
 extras["quality"] = [

src/huggingface_hub/keras_mixin.py

@@ -92,13 +92,18 @@ def _create_model_card(
 ):
     """
     Creates a model card for the repository.
+
+    Do not overwrite an existing README.md file.
     """
+    readme_path = repo_dir / "README.md"
+    if readme_path.exists():
+        return
+
     hyperparameters = _create_hyperparameter_table(model)
     if plot_model and is_graphviz_available() and is_pydot_available():
         _plot_network(model, repo_dir)
     if metadata is None:
         metadata = {}
-    readme_path = f"{repo_dir}/README.md"
     metadata["library_name"] = "keras"
     model_card: str = "---\n"
     model_card += yaml_dump(metadata, default_flow_style=False)
@@ -120,13 +125,7 @@ def _create_model_card(
         model_card += f"\n![Model Image]({path_to_plot})\n"
         model_card += "\n</details>"
 
-    if os.path.exists(readme_path):
-        with open(readme_path, "r", encoding="utf8") as f:
-            readme = f.read()
-    else:
-        readme = model_card
-    with open(readme_path, "w", encoding="utf-8") as f:
-        f.write(readme)
+    readme_path.write_text(model_card)
 
 
 def save_pretrained_keras(

tests/test_keras_integration.py

@@ -1,6 +1,5 @@
 import json
 import os
-import re
 import unittest
 from pathlib import Path
 
@@ -13,25 +12,14 @@
     push_to_hub_keras,
     save_pretrained_keras,
 )
-from huggingface_hub.utils import (
-    is_graphviz_available,
-    is_pydot_available,
-    is_tf_available,
-    logging,
-)
+from huggingface_hub.utils import is_graphviz_available, is_pydot_available, is_tf_available, logging
 
 from .testing_constants import ENDPOINT_STAGING, TOKEN, USER
-from .testing_utils import (
-    repo_name,
-)
+from .testing_utils import repo_name
 
 
 logger = logging.get_logger(__name__)
 
-WORKING_REPO_SUBDIR = f"fixtures/working_repo_{__name__.split('.')[-1]}"
-WORKING_REPO_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), WORKING_REPO_SUBDIR)
-
-PUSH_TO_HUB_KERAS_WARNING_REGEX = re.escape("Deprecated argument(s) used in 'push_to_hub_keras':")
 
 if is_tf_available():
     import tensorflow as tf
@@ -259,8 +247,9 @@ def test_push_to_hub_keras_sequential_via_http_basic(self):
         push_to_hub_keras(model, repo_id=repo_id, token=TOKEN, api_endpoint=ENDPOINT_STAGING)
         model_info = self._api.model_info(repo_id)
         self.assertEqual(model_info.modelId, repo_id)
-        self.assertTrue("README.md" in [f.rfilename for f in model_info.siblings])
-        self.assertTrue("model.png" in [f.rfilename for f in model_info.siblings])
+        repo_files = self._api.list_repo_files(repo_id)
+        self.assertIn("README.md", repo_files)
+        self.assertIn("model.png", repo_files)
         self._api.delete_repo(repo_id=repo_id)
 
     def test_push_to_hub_keras_sequential_via_http_plot_false(self):
@@ -269,8 +258,8 @@ def test_push_to_hub_keras_sequential_via_http_plot_false(self):
         model = self.model_fit(model)
 
         push_to_hub_keras(model, repo_id=repo_id, token=TOKEN, api_endpoint=ENDPOINT_STAGING, plot_model=False)
-        model_info = self._api.model_info(repo_id)
-        self.assertFalse("model.png" in [f.rfilename for f in model_info.siblings])
+        repo_files = self._api.list_repo_files(repo_id)
+        self.assertNotIn("model.png", repo_files)
         self._api.delete_repo(repo_id=repo_id)
 
     def test_push_to_hub_keras_via_http_override_tensorboard(self):