transformers/utils/class_mapping_update.py
Stas Bekman 188574ac50
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
2021-03-03 08:54:00 -08:00

61 lines
1.9 KiB
Python

# 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))