Add a check on config classes docstring checkpoints (#17012)

* Add the check

* add missing ckpts

* add a list to ignore

* call the added check script

* better regex pattern
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

.circleci/config.yml

@@ -881,6 +881,7 @@ jobs:
             - run: python utils/check_dummies.py
             - run: python utils/check_repo.py
             - run: python utils/check_inits.py
+            - run: python utils/check_config_docstrings.py
             - run: make deps_table_check_updated
             - run: python utils/tests_fetcher.py --sanity_check
 

Makefile

@@ -39,6 +39,7 @@ repo-consistency:
 	python utils/check_dummies.py
 	python utils/check_repo.py
 	python utils/check_inits.py
+	python utils/check_config_docstrings.py
 	python utils/tests_fetcher.py --sanity_check
 
 # this target runs checks on all files

docs/source/en/pr_checks.mdx

@@ -108,6 +108,7 @@ This checks that:
 - All objects added to the init are documented (performed by `utils/check_repo.py`)
 - All `__init__.py` files have the same content in their two sections (performed by `utils/check_inits.py`)
 - All code identified as a copy from another module is consistent with the original (performed by `utils/check_copies.py`)
+- All configuration classes have at least one valid checkpoint mentioned in their docstrings (performed by `utils/check_config_docstrings.py`)
 - The translations of the READMEs and the index of the doc have the same model list as the main README (performed by `utils/check_copies.py`)
 - The auto-generated tables in the documentation are up to date (performed by `utils/check_table.py`)
 - The library has all objects available even if not all optional dependencies are installed (performed by `utils/check_dummies.py`)

src/transformers/models/convbert/configuration_convbert.py

@@ -37,9 +37,11 @@ class ConvBertConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`ConvBertModel`]. It is used to instantiate an
     ConvBERT model according to the specified arguments, defining the model architecture. Instantiating a configuration
     with the defaults will yield a similar configuration to that of the ConvBERT
-    [conv-bert-base](https://huggingface.co/YituTech/conv-bert-base) architecture. Configuration objects inherit from
-    [`PretrainedConfig`] and can be used to control the model outputs. Read the documentation from [`PretrainedConfig`]
-    for more information.
+    [YituTech/conv-bert-base](https://huggingface.co/YituTech/conv-bert-base) architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
 
     Args:
         vocab_size (`int`, *optional*, defaults to 30522):

src/transformers/models/imagegpt/configuration_imagegpt.py

@@ -32,7 +32,7 @@ class ImageGPTConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`ImageGPTModel`] or a [`TFImageGPTModel`]. It is
     used to instantiate a GPT-2 model according to the specified arguments, defining the model architecture.
     Instantiating a configuration with the defaults will yield a similar configuration to that of the ImageGPT
-    [small](https://huggingface.co/imagegpt) architecture.
+    [openai/imagegpt-small](https://huggingface.co/openai/imagegpt-small) architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
     documentation from [`PretrainedConfig`] for more information.

utils/check_config_docstrings.py

+# coding=utf-8
+# Copyright 2022 The HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import importlib
+import inspect
+import os
+import re
+
+
+# All paths are set with the intent you should run this script from the root of the repo with the command
+# python utils/check_config_docstrings.py
+PATH_TO_TRANSFORMERS = "src/transformers"
+
+
+# This is to make sure the transformers module imported is the one in the repo.
+spec = importlib.util.spec_from_file_location(
+    "transformers",
+    os.path.join(PATH_TO_TRANSFORMERS, "__init__.py"),
+    submodule_search_locations=[PATH_TO_TRANSFORMERS],
+)
+transformers = spec.loader.load_module()
+
+CONFIG_MAPPING = transformers.models.auto.configuration_auto.CONFIG_MAPPING
+
+# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
+# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
+_re_checkpoint = re.compile("\[(.+?)\]\((https://huggingface\.co/.+?)\)")
+
+
+CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK = {
+    "CLIPConfig",
+    "DecisionTransformerConfig",
+    "EncoderDecoderConfig",
+    "RagConfig",
+    "SpeechEncoderDecoderConfig",
+    "VisionEncoderDecoderConfig",
+    "VisionTextDualEncoderConfig",
+}
+
+
+def check_config_docstrings_have_checkpoints():
+    configs_without_checkpoint = []
+
+    for config_class in list(CONFIG_MAPPING.values()):
+        checkpoint_found = False
+
+        # source code of `config_class`
+        config_source = inspect.getsource(config_class)
+        checkpoints = _re_checkpoint.findall(config_source)
+
+        for checkpoint in checkpoints:
+            # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
+            # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
+            ckpt_name, ckpt_link = checkpoint
+
+            # verify the checkpoint name corresponds to the checkpoint link
+            ckpt_link_from_name = f"https://huggingface.co/{ckpt_name}"
+            if ckpt_link == ckpt_link_from_name:
+                checkpoint_found = True
+                break
+
+        name = config_class.__name__
+        if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
+            configs_without_checkpoint.append(name)
+
+    if len(configs_without_checkpoint) > 0:
+        message = "\n".join(sorted(configs_without_checkpoint))
+        raise ValueError(f"The following configurations don't contain any valid checkpoint:\n{message}")
+
+
+if __name__ == "__main__":
+    check_config_docstrings_have_checkpoints()