Make sure Diffusers works even if Hub is down (#3447)

* Make sure Diffusers works even if Hub is down

* Make sure hub down is well tested

src/diffusers/pipelines/pipeline_utils.py

@@ -30,6 +30,7 @@ import PIL
 import torch
 from huggingface_hub import hf_hub_download, model_info, snapshot_download
 from packaging import version
+from requests.exceptions import HTTPError
 from tqdm.auto import tqdm
 
 import diffusers
@@ -1228,6 +1229,17 @@ class DiffusionPipeline(ConfigMixin):
         allow_patterns = None
         ignore_patterns = None
 
+        if not local_files_only:
+            try:
+                info = model_info(
+                    pretrained_model_name,
+                    use_auth_token=use_auth_token,
+                    revision=revision,
+                )
+            except HTTPError as e:
+                logger.warn(f"Couldn't connect to the Hub: {e}.\nWill try to load from local cache.")
+                local_files_only = True
+
         if not local_files_only:
             config_file = hf_hub_download(
                 pretrained_model_name,
@@ -1239,11 +1251,6 @@ class DiffusionPipeline(ConfigMixin):
                 resume_download=resume_download,
                 use_auth_token=use_auth_token,
             )
-            info = model_info(
-                pretrained_model_name,
-                use_auth_token=use_auth_token,
-                revision=revision,
-            )
 
             config_dict = cls._dict_from_json_file(config_file)
 

tests/pipelines/test_pipelines.py

@@ -353,7 +353,7 @@ class DownloadTests(unittest.TestCase):
         with mock.patch("requests.request", return_value=response_mock):
             # Download this model to make sure it's in the cache.
             pipe = StableDiffusionPipeline.from_pretrained(
-                "hf-internal-testing/tiny-stable-diffusion-torch", safety_checker=None, local_files_only=True
+                "hf-internal-testing/tiny-stable-diffusion-torch", safety_checker=None
             )
             comps = {k: v for k, v in pipe.components.items() if hasattr(v, "parameters")}