fix http

Author: xadupre

_unittests/ut_torch_models/test_hghub_model.py

@@ -199,6 +199,7 @@ def _diff(c1, c2):
         for mid in load_models_testing():
             with self.subTest(mid=mid):
                 if mid in {
+                    "hf-internal-testing/tiny-random-BeitForImageClassification",
                     "hf-internal-testing/tiny-random-MaskFormerForInstanceSegmentation",
                     "hf-internal-testing/tiny-random-MoonshineForConditionalGeneration",
                     "fxmarty/pix2struct-tiny-random",

onnx_diagnostic/torch_models/hghub/hub_api.py

@@ -1,4 +1,5 @@
 import functools
+import os
 from typing import Any, Dict, List, Optional, Union
 import transformers
 from huggingface_hub import HfApi, model_info
@@ -33,25 +34,27 @@ def get_cached_configuration(name: str) -> Optional[transformers.PretrainedConfi
     assert cached, "no cached configuration, which is weird"
     if name in cached:
         return cached[name]()
+    if os.environ.get("NOHTTP", ""):
+        raise AssertionError(f"Unable to find {name!r} in {sorted(cached)}")
     return None
 
 
 def get_pretrained_config(
-    model_id: str, trust_remote_code: bool = True, use_cached: bool = True
+    model_id: str, trust_remote_code: bool = True, use_preinstalled: bool = True
 ) -> Any:
     """
     Returns the config for a model_id.
 
     :param model_id: model id
     :param trust_remote_code: trust_remote_code,
         see :meth:`transformers.AutoConfig.from_pretrained`
-    :param used_cached: if cached, uses this version to avoid
+    :param use_preinstalled: if use_preinstalled, uses this version to avoid
         accessing the network, if available, it is returned by
         :func:`get_cached_configuration`, the cached list is mostly for
         unit tests
     :return: a configuration
     """
-    if use_cached:
+    if use_preinstalled:
         conf = get_cached_configuration(model_id)
         if conf is not None:
             return conf

onnx_diagnostic/torch_models/hghub/hub_data_cached_configs.py

@@ -3259,8 +3259,8 @@ def _ccached_hf_m4_tiny_random_idefics():
     )
 
 
-def _ccached_openai_whisper_itny():
-    "openai/whipser-tiny"
+def _ccached_openai_whisper_tiny():
+    "openai/whisper-tiny"
     return transformers.WhisperConfig(
         **{
             "_name_or_path": "openai/whisper-tiny",

onnx_diagnostic/torch_models/hghub/model_inputs.py

@@ -326,6 +326,7 @@ def get_untrained_model_with_inputs(
     verbose: int = 0,
     dynamic_rope: Optional[bool] = None,
     same_as_pretrained: bool = False,
+    use_preinstalled: bool = True,
 ) -> Dict[str, Any]:
     """
     Gets a non initialized model similar to the original model
@@ -342,6 +343,7 @@ def get_untrained_model_with_inputs(
     :param dynamic_rope: use dynamic rope (see :class:`transformers.LlamaConfig`)
     :param same_as_pretrained: if True, do not change the default values
         to get a smaller model
+    :param use_preinstalled: use preinstalled configurations
     :return: dictionary with a model, inputs, dynamic shapes, and the configuration
 
     Example:
@@ -363,8 +365,10 @@ def get_untrained_model_with_inputs(
     """
     if verbose:
         print(f"[get_untrained_model_with_inputs] model_id={model_id!r}")
+        if use_preinstalled:
+            print(f"[get_untrained_model_with_inputs] use preinstalled {model_id!r}")
     if config is None:
-        config = get_pretrained_config(model_id)
+        config = get_pretrained_config(model_id, use_preinstalled=use_preinstalled)
     archs = config.architectures  # type: ignore
     assert archs is not None and len(archs) == 1, (
         f"Unable to determine the architecture for model {model_id!r}, "