Avoid failure in check_repo.py due to missing backends (#21930)

* Update utils/check_repo.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update utils/check_repo.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

utils/check_repo.py

@@ -323,6 +323,30 @@
 transformers = direct_transformers_import(PATH_TO_TRANSFORMERS)
 
 
+def check_missing_backends():
+    missing_backends = []
+    if not is_torch_available():
+        missing_backends.append("PyTorch")
+    if not is_tf_available():
+        missing_backends.append("TensorFlow")
+    if not is_flax_available():
+        missing_backends.append("Flax")
+    if len(missing_backends) > 0:
+        missing = ", ".join(missing_backends)
+        if os.getenv("TRANSFORMERS_IS_CI", "").upper() in ENV_VARS_TRUE_VALUES:
+            raise Exception(
+                "Full repo consistency checks require all backends to be installed (with `pip install -e .[dev]` in the "
+                f"Transformers repo, the following are missing: {missing}."
+            )
+        else:
+            warnings.warn(
+                "Full repo consistency checks require all backends to be installed (with `pip install -e .[dev]` in the "
+                f"Transformers repo, the following are missing: {missing}. While it's probably fine as long as you "
+                "didn't make any change in one of those backends modeling files, you should probably execute the "
+                "command above to be on the safe side."
+            )
+
+
 def check_model_list():
     """Check the model list inside the transformers library."""
     # Get the models from the directory structure of `src/transformers/models/`
@@ -578,27 +602,7 @@ def check_models_are_auto_configured(module, all_auto_models):
 
 def check_all_models_are_auto_configured():
     """Check all models are each in an auto class."""
-    missing_backends = []
-    if not is_torch_available():
-        missing_backends.append("PyTorch")
-    if not is_tf_available():
-        missing_backends.append("TensorFlow")
-    if not is_flax_available():
-        missing_backends.append("Flax")
-    if len(missing_backends) > 0:
-        missing = ", ".join(missing_backends)
-        if os.getenv("TRANSFORMERS_IS_CI", "").upper() in ENV_VARS_TRUE_VALUES:
-            raise Exception(
-                "Full quality checks require all backends to be installed (with `pip install -e .[dev]` in the "
-                f"Transformers repo, the following are missing: {missing}."
-            )
-        else:
-            warnings.warn(
-                "Full quality checks require all backends to be installed (with `pip install -e .[dev]` in the "
-                f"Transformers repo, the following are missing: {missing}. While it's probably fine as long as you "
-                "didn't make any change in one of those backends modeling files, you should probably execute the "
-                "command above to be on the safe side."
-            )
+    check_missing_backends()
     modules = get_model_modules()
     all_auto_models = get_all_auto_configured_models()
     failures = []
@@ -612,8 +616,9 @@ def check_all_models_are_auto_configured():
 
 def check_all_auto_object_names_being_defined():
     """Check all names defined in auto (name) mappings exist in the library."""
-    failures = []
+    check_missing_backends()
 
+    failures = []
     mappings_to_check = {
         "TOKENIZER_MAPPING_NAMES": TOKENIZER_MAPPING_NAMES,
         "IMAGE_PROCESSOR_MAPPING_NAMES": IMAGE_PROCESSOR_MAPPING_NAMES,
@@ -623,7 +628,9 @@ def check_all_auto_object_names_being_defined():
 
     # Each auto modeling files contains multiple mappings. Let's get them in a dynamic way.
     for module_name in ["modeling_auto", "modeling_tf_auto", "modeling_flax_auto"]:
-        module = getattr(transformers.models.auto, module_name)
+        module = getattr(transformers.models.auto, module_name, None)
+        if module is None:
+            continue
         # all mappings in a single auto modeling file
         mapping_names = [x for x in dir(module) if x.endswith("_MAPPING_NAMES")]
         mappings_to_check.update({name: getattr(module, name) for name in mapping_names})
@@ -650,8 +657,9 @@ def check_all_auto_object_names_being_defined():
 
 def check_all_auto_mapping_names_in_config_mapping_names():
     """Check all keys defined in auto mappings (mappings of names) appear in `CONFIG_MAPPING_NAMES`."""
-    failures = []
+    check_missing_backends()
 
+    failures = []
     # `TOKENIZER_PROCESSOR_MAPPING_NAMES` and `AutoTokenizer` is special, and don't need to follow the rule.
     mappings_to_check = {
         "IMAGE_PROCESSOR_MAPPING_NAMES": IMAGE_PROCESSOR_MAPPING_NAMES,
@@ -661,7 +669,9 @@ def check_all_auto_mapping_names_in_config_mapping_names():
 
     # Each auto modeling files contains multiple mappings. Let's get them in a dynamic way.
     for module_name in ["modeling_auto", "modeling_tf_auto", "modeling_flax_auto"]:
-        module = getattr(transformers.models.auto, module_name)
+        module = getattr(transformers.models.auto, module_name, None)
+        if module is None:
+            continue
         # all mappings in a single auto modeling file
         mapping_names = [x for x in dir(module) if x.endswith("_MAPPING_NAMES")]
         mappings_to_check.update({name: getattr(module, name) for name in mapping_names})