remap MODEL_FOR_QUESTION_ANSWERING_MAPPING classes to names auto-generated file (#10487)

* remap classes to strings

* missing new util

* style

* doc

* move the autogenerated file

* Trigger CI

utils/class_mapping_update.py

@@ -0,0 +1,60 @@
+# coding=utf-8
+# Copyright 2020 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.
+
+# this script remaps classes to class strings so that it's quick to load such maps and not require
+# loading all possible modeling files
+#
+# it can be extended to auto-generate other dicts that are needed at runtime
+
+
+import os
+import sys
+from os.path import abspath, dirname, join
+
+
+git_repo_path = abspath(join(dirname(dirname(__file__)), "src"))
+sys.path.insert(1, git_repo_path)
+
+src = "src/transformers/models/auto/modeling_auto.py"
+dst = "src/transformers/utils/modeling_auto_mapping.py"
+
+if os.path.exists(dst) and os.path.getmtime(src) < os.path.getmtime(dst):
+    # speed things up by only running this script if the src is newer than dst
+    sys.exit(0)
+
+# only load if needed
+from transformers.models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING  # noqa
+
+
+entries = "\n".join(
+    [f'        ("{k.__name__}", "{v.__name__}"),' for k, v in MODEL_FOR_QUESTION_ANSWERING_MAPPING.items()]
+)
+content = [
+    "# THIS FILE HAS BEEN AUTOGENERATED. To update:",
+    "# 1. modify: models/auto/modeling_auto.py",
+    "# 2. run: python utils/class_mapping_update.py",
+    "from collections import OrderedDict",
+    "",
+    "",
+    "MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict(",
+    "    [",
+    entries,
+    "    ]",
+    ")",
+    "",
+]
+print(f"updating {dst}")
+with open(dst, "w", encoding="utf-8", newline="\n") as f:
+    f.write("\n".join(content))