ci: remove gh API requests (#11 monkeypatch) + anonymous links

Signed-off-by: Élie Goudout <[email protected]>

Author: eliegoudout

docs/src/conf.py

@@ -3,14 +3,14 @@
 #
 # For the full list of built-in configuration values, see the documentation:
 # https://www.sphinx-doc.org/en/master/usage/configuration.html
-
 import html
 import importlib
 import inspect
 import os
 import re
 from collections.abc import Mapping, Sequence
 from enum import EnumType
+from functools import partial
 from itertools import zip_longest
 from operator import itemgetter
 from os.path import dirname, relpath
@@ -19,6 +19,7 @@
 from types import MappingProxyType
 from typing import TYPE_CHECKING, Literal, cast
 
+import torch
 from paramclasses import IMPL, MISSING, isparamclass
 from sphinx.application import Sphinx
 from sphinx.util import logging
@@ -297,6 +298,9 @@ def linkcode_resolve(
 
 # -- Options for "sphinx_gallery.gen_gallery" --------------------------------
 os.environ.setdefault("HF_DATASETS_DISABLE_PROGRESS_BARS", "true")  # No download logs
+# Monkeypatch for github.com/ThalesGroup/scio/issues/11
+torch.hub.load = partial(torch.hub.load, skip_validation=True)
+
 tutorials_order = [
     "inferring_with_confidence.py",
     "visualizing_and_evaluating_ood_detection_algorithms.py",

docs/src/user_guide/installation_compatibility.rst

@@ -18,15 +18,15 @@ If you wish to install from source or wheels manually, you can download `release
 
 OS Compatibility
 ----------------
-The library is available and functional on **Ubuntu**, **Windows** and *MacOS* (minus ``faiss``-related features ─ feel free to show your interest `here <https://github.com/ThalesGroup/scio/issues/2>`_).
+The library is available and functional on **Ubuntu**, **Windows** and *MacOS* (minus ``faiss``-related features ─ feel free to show your interest `here <https://github.com/ThalesGroup/scio/issues/2>`__).
 
 Framework Compatiblity
 ----------------------
 Although confidence scores are not a particularity of Neural Networks, ``scio`` is precisely developed to handle such models. More precisely, only *PyTorch* models (inheriting from ``torch.nn.Module``) are currently supported.
 
 GPU Compatibility
 -----------------
-Our library is **fully compatible** and tested with CUDA devices for native use of GPU acceleration! Note however that features using ``faiss`` currently use CPU-bound indexes, introducing a potential GPU > CPU > GPU bottleneck. This may be improved in future versions ─ feel free to show your interest `here <https://github.com/ThalesGroup/scio/issues/18>`_.
+Our library is **fully compatible** and tested with CUDA devices for native use of GPU acceleration! Note however that features using ``faiss`` currently use CPU-bound indexes, introducing a potential GPU > CPU > GPU bottleneck. This may be improved in future versions ─ feel free to show your interest `here <https://github.com/ThalesGroup/scio/issues/18>`__.
 
 Supported Data Types
 --------------------