741 lines
30 KiB
Python
741 lines
30 KiB
Python
# coding=utf-8
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# Copyright 2020 The HuggingFace Inc. team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Utility that checks whether the copies defined in the library match the original or not. This includes:
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- All code commented with `# Copied from` comments,
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- The list of models in the main README.md matches the ones in the localized READMEs,
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- Files that are registered as full copies of one another in the `FULL_COPIES` constant of this script.
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This also checks the list of models in the README is complete (has all models) and add a line to complete if there is
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a model missing.
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Use from the root of the repo with:
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```bash
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python utils/check_copies.py
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```
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for a check that will error in case of inconsistencies (used by `make repo-consistency`) or
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```bash
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python utils/check_copies.py --fix_and_overwrite
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```
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for a check that will fix all inconsistencies automatically (used by `make fix-copies`).
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"""
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import argparse
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import glob
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import os
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import re
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import subprocess
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from typing import List, Optional, Tuple
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from transformers.utils import direct_transformers_import
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# All paths are set with the intent you should run this script from the root of the repo with the command
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# python utils/check_copies.py
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TRANSFORMERS_PATH = "src/transformers"
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MODEL_TEST_PATH = "tests/models"
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PATH_TO_DOCS = "docs/source/en"
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REPO_PATH = "."
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# Mapping for files that are full copies of others (keys are copies, values the file to keep them up to data with)
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FULL_COPIES = {
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"examples/tensorflow/question-answering/utils_qa.py": "examples/pytorch/question-answering/utils_qa.py",
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"examples/flax/question-answering/utils_qa.py": "examples/pytorch/question-answering/utils_qa.py",
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}
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LOCALIZED_READMES = {
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# If the introduction or the conclusion of the list change, the prompts may need to be updated.
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"README.md": {
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"start_prompt": "🤗 Transformers currently provides the following architectures",
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"end_prompt": "1. Want to contribute a new model?",
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"format_model_list": (
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"**[{title}]({model_link})** (from {paper_affiliations}) released with the paper {paper_title_link} by"
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" {paper_authors}.{supplements}"
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),
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},
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"README_zh-hans.md": {
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"start_prompt": "🤗 Transformers 目前支持如下的架构",
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"end_prompt": "1. 想要贡献新的模型?",
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"format_model_list": (
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"**[{title}]({model_link})** (来自 {paper_affiliations}) 伴随论文 {paper_title_link} 由 {paper_authors}"
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" 发布。{supplements}"
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),
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},
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"README_zh-hant.md": {
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"start_prompt": "🤗 Transformers 目前支援以下的架構",
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"end_prompt": "1. 想要貢獻新的模型?",
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"format_model_list": (
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"**[{title}]({model_link})** (from {paper_affiliations}) released with the paper {paper_title_link} by"
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" {paper_authors}.{supplements}"
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),
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},
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"README_ko.md": {
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"start_prompt": "🤗 Transformers는 다음 모델들을 제공합니다",
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"end_prompt": "1. 새로운 모델을 올리고 싶나요?",
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"format_model_list": (
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"**[{title}]({model_link})** ({paper_affiliations} 에서 제공)은 {paper_authors}.{supplements}의"
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" {paper_title_link}논문과 함께 발표했습니다."
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),
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},
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"README_es.md": {
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"start_prompt": "🤗 Transformers actualmente proporciona las siguientes arquitecturas",
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"end_prompt": "1. ¿Quieres aportar un nuevo modelo?",
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"format_model_list": (
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"**[{title}]({model_link})** (from {paper_affiliations}) released with the paper {paper_title_link} by"
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" {paper_authors}.{supplements}"
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),
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},
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"README_ja.md": {
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"start_prompt": "🤗Transformersは現在、以下のアーキテクチャを提供しています",
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"end_prompt": "1. 新しいモデルを投稿したいですか?",
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"format_model_list": (
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"**[{title}]({model_link})** ({paper_affiliations} から) {paper_authors}.{supplements} から公開された研究論文"
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" {paper_title_link}"
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),
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},
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"README_hd.md": {
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"start_prompt": "🤗 ट्रांसफॉर्मर वर्तमान में निम्नलिखित आर्किटेक्चर का समर्थन करते हैं",
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"end_prompt": "1. एक नए मॉडल में योगदान देना चाहते हैं?",
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"format_model_list": (
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"**[{title}]({model_link})** ({paper_affiliations} से) {paper_authors}.{supplements} द्वारा"
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"अनुसंधान पत्र {paper_title_link} के साथ जारी किया गया"
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),
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},
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}
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# This is to make sure the transformers module imported is the one in the repo.
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transformers_module = direct_transformers_import(TRANSFORMERS_PATH)
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def _should_continue(line: str, indent: str) -> bool:
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# Helper function. Returns `True` if `line` is empty, starts with the `indent` or is the end parenthesis of a
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# function definition
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return line.startswith(indent) or len(line.strip()) == 0 or re.search(r"^\s*\)(\s*->.*:|:)\s*$", line) is not None
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def find_code_in_transformers(object_name: str, base_path: str = None) -> str:
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"""
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Find and return the source code of an object.
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Args:
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object_name (`str`):
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The name of the object we want the source code of.
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base_path (`str`, *optional*):
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The path to the base folder where files are checked. If not set, it will be set to `TRANSFORMERS_PATH`.
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Returns:
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`str`: The source code of the object.
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"""
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parts = object_name.split(".")
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i = 0
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# We can't set this as the default value in the argument, otherwise `CopyCheckTester` will fail, as it uses a
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# patched temp directory.
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if base_path is None:
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base_path = TRANSFORMERS_PATH
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# Detail: the `Copied from` statement is originally designed to work with the last part of `TRANSFORMERS_PATH`,
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# (which is `transformers`). The same should be applied for `MODEL_TEST_PATH`. However, its last part is `models`
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# (to only check and search in it) which is a bit confusing. So we keep the copied statement staring with
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# `tests.models.` and change it to `tests` here.
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if base_path == MODEL_TEST_PATH:
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base_path = "tests"
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# First let's find the module where our object lives.
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module = parts[i]
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while i < len(parts) and not os.path.isfile(os.path.join(base_path, f"{module}.py")):
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i += 1
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if i < len(parts):
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module = os.path.join(module, parts[i])
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if i >= len(parts):
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raise ValueError(
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f"`object_name` should begin with the name of a module of transformers but got {object_name}."
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)
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with open(os.path.join(base_path, f"{module}.py"), "r", encoding="utf-8", newline="\n") as f:
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lines = f.readlines()
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# Now let's find the class / func in the code!
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indent = ""
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line_index = 0
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for name in parts[i + 1 :]:
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while (
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line_index < len(lines) and re.search(rf"^{indent}(class|def)\s+{name}(\(|\:)", lines[line_index]) is None
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):
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line_index += 1
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indent += " "
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line_index += 1
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if line_index >= len(lines):
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raise ValueError(f" {object_name} does not match any function or class in {module}.")
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# We found the beginning of the class / func, now let's find the end (when the indent diminishes).
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start_index = line_index - 1
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while line_index < len(lines) and _should_continue(lines[line_index], indent):
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line_index += 1
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# Clean up empty lines at the end (if any).
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while len(lines[line_index - 1]) <= 1:
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line_index -= 1
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code_lines = lines[start_index:line_index]
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return "".join(code_lines)
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_re_copy_warning = re.compile(r"^(\s*)#\s*Copied from\s+transformers\.(\S+\.\S+)\s*($|\S.*$)")
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_re_copy_warning_for_test_file = re.compile(r"^(\s*)#\s*Copied from\s+tests\.(\S+\.\S+)\s*($|\S.*$)")
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_re_replace_pattern = re.compile(r"^\s*(\S+)->(\S+)(\s+.*|$)")
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_re_fill_pattern = re.compile(r"<FILL\s+[^>]*>")
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def get_indent(code: str) -> str:
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"""
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Find the indent in the first non empty line in a code sample.
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Args:
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code (`str`): The code to inspect.
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Returns:
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`str`: The indent looked at (as string).
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"""
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lines = code.split("\n")
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idx = 0
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while idx < len(lines) and len(lines[idx]) == 0:
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idx += 1
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if idx < len(lines):
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return re.search(r"^(\s*)\S", lines[idx]).groups()[0]
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return ""
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def run_ruff(code):
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command = ["ruff", "format", "-", "--config", "pyproject.toml", "--silent"]
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process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE)
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stdout, _ = process.communicate(input=code.encode())
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return stdout.decode()
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def stylify(code: str) -> str:
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"""
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Applies the ruff part of our `make style` command to some code. This formats the code using `ruff format`.
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As `ruff` does not provide a python api this cannot be done on the fly.
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Args:
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code (`str`): The code to format.
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Returns:
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`str`: The formatted code.
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"""
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has_indent = len(get_indent(code)) > 0
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if has_indent:
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code = f"class Bla:\n{code}"
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formatted_code = run_ruff(code)
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return formatted_code[len("class Bla:\n") :] if has_indent else formatted_code
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def check_codes_match(observed_code: str, theoretical_code: str) -> Optional[int]:
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"""
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Checks if two version of a code match with the exception of the class/function name.
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Args:
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observed_code (`str`): The code found.
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theoretical_code (`str`): The code to match.
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Returns:
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`Optional[int]`: The index of the first line where there is a difference (if any) and `None` if the codes
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match.
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"""
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observed_code_header = observed_code.split("\n")[0]
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theoretical_code_header = theoretical_code.split("\n")[0]
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# Catch the function/class name: it is expected that those do not match.
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_re_class_match = re.compile(r"class\s+([^\(:]+)(?:\(|:)")
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_re_func_match = re.compile(r"def\s+([^\(]+)\(")
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for re_pattern in [_re_class_match, _re_func_match]:
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if re_pattern.match(observed_code_header) is not None:
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observed_obj_name = re_pattern.search(observed_code_header).groups()[0]
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theoretical_name = re_pattern.search(theoretical_code_header).groups()[0]
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theoretical_code_header = theoretical_code_header.replace(theoretical_name, observed_obj_name)
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# Find the first diff. Line 0 is special since we need to compare with the function/class names ignored.
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diff_index = 0
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if theoretical_code_header != observed_code_header:
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return 0
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diff_index = 1
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for observed_line, theoretical_line in zip(observed_code.split("\n")[1:], theoretical_code.split("\n")[1:]):
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if observed_line != theoretical_line:
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return diff_index
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diff_index += 1
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def is_copy_consistent(filename: str, overwrite: bool = False) -> Optional[List[Tuple[str, int]]]:
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"""
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Check if the code commented as a copy in a file matches the original.
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Args:
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filename (`str`):
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The name of the file to check.
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overwrite (`bool`, *optional*, defaults to `False`):
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Whether or not to overwrite the copies when they don't match.
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Returns:
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`Optional[List[Tuple[str, int]]]`: If `overwrite=False`, returns the list of differences as tuples `(str, int)`
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with the name of the object having a diff and the line number where theere is the first diff.
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"""
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with open(filename, "r", encoding="utf-8", newline="\n") as f:
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lines = f.readlines()
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diffs = []
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line_index = 0
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# Not a for loop cause `lines` is going to change (if `overwrite=True`).
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while line_index < len(lines):
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search_re = _re_copy_warning
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if filename.startswith("tests"):
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search_re = _re_copy_warning_for_test_file
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search = search_re.search(lines[line_index])
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if search is None:
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line_index += 1
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continue
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# There is some copied code here, let's retrieve the original.
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indent, object_name, replace_pattern = search.groups()
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base_path = TRANSFORMERS_PATH if not filename.startswith("tests") else MODEL_TEST_PATH
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theoretical_code = find_code_in_transformers(object_name, base_path=base_path)
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theoretical_indent = get_indent(theoretical_code)
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start_index = line_index + 1 if indent == theoretical_indent else line_index
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line_index = start_index + 1
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subcode = "\n".join(theoretical_code.split("\n")[1:])
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indent = get_indent(subcode)
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# Loop to check the observed code, stop when indentation diminishes or if we see a End copy comment.
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should_continue = True
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while line_index < len(lines) and should_continue:
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line_index += 1
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if line_index >= len(lines):
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break
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line = lines[line_index]
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# There is a special pattern `# End copy` to stop early. It's not documented cause it shouldn't really be
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# used.
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should_continue = _should_continue(line, indent) and re.search(f"^{indent}# End copy", line) is None
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# Clean up empty lines at the end (if any).
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while len(lines[line_index - 1]) <= 1:
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line_index -= 1
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observed_code_lines = lines[start_index:line_index]
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observed_code = "".join(observed_code_lines)
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# Before comparing, use the `replace_pattern` on the original code.
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if len(replace_pattern) > 0:
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patterns = replace_pattern.replace("with", "").split(",")
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patterns = [_re_replace_pattern.search(p) for p in patterns]
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for pattern in patterns:
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if pattern is None:
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continue
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obj1, obj2, option = pattern.groups()
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theoretical_code = re.sub(obj1, obj2, theoretical_code)
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if option.strip() == "all-casing":
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theoretical_code = re.sub(obj1.lower(), obj2.lower(), theoretical_code)
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theoretical_code = re.sub(obj1.upper(), obj2.upper(), theoretical_code)
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theoretical_code = stylify(theoretical_code)
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# Test for a diff and act accordingly.
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diff_index = check_codes_match(observed_code, theoretical_code)
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if diff_index is not None:
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diffs.append([object_name, diff_index + start_index + 1])
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if overwrite:
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lines = lines[:start_index] + [theoretical_code] + lines[line_index:]
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line_index = start_index + 1
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if overwrite and len(diffs) > 0:
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# Warn the user a file has been modified.
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print(f"Detected changes, rewriting {filename}.")
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with open(filename, "w", encoding="utf-8", newline="\n") as f:
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f.writelines(lines)
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return diffs
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def check_copies(overwrite: bool = False):
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"""
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Check every file is copy-consistent with the original. Also check the model list in the main README and other
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READMEs are consistent.
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Args:
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overwrite (`bool`, *optional*, defaults to `False`):
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Whether or not to overwrite the copies when they don't match.
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"""
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all_files = glob.glob(os.path.join(TRANSFORMERS_PATH, "**/*.py"), recursive=True)
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all_test_files = glob.glob(os.path.join(MODEL_TEST_PATH, "**/*.py"), recursive=True)
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all_files = list(all_files) + list(all_test_files)
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diffs = []
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for filename in all_files:
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new_diffs = is_copy_consistent(filename, overwrite)
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diffs += [f"- {filename}: copy does not match {d[0]} at line {d[1]}" for d in new_diffs]
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if not overwrite and len(diffs) > 0:
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diff = "\n".join(diffs)
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raise Exception(
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"Found the following copy inconsistencies:\n"
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+ diff
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+ "\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them."
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)
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check_model_list_copy(overwrite=overwrite)
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def check_full_copies(overwrite: bool = False):
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"""
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Check the files that are full copies of others (as indicated in `FULL_COPIES`) are copy-consistent.
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Args:
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overwrite (`bool`, *optional*, defaults to `False`):
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Whether or not to overwrite the copies when they don't match.
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"""
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diffs = []
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for target, source in FULL_COPIES.items():
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with open(source, "r", encoding="utf-8") as f:
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source_code = f.read()
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with open(target, "r", encoding="utf-8") as f:
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target_code = f.read()
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if source_code != target_code:
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if overwrite:
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with open(target, "w", encoding="utf-8") as f:
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print(f"Replacing the content of {target} by the one of {source}.")
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f.write(source_code)
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else:
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diffs.append(f"- {target}: copy does not match {source}.")
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if not overwrite and len(diffs) > 0:
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diff = "\n".join(diffs)
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raise Exception(
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"Found the following copy inconsistencies:\n"
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+ diff
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+ "\nRun `make fix-copies` or `python utils/check_copies.py --fix_and_overwrite` to fix them."
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)
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def get_model_list(filename: str, start_prompt: str, end_prompt: str) -> str:
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"""
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|
Extracts the model list from a README.
|
|
|
|
Args:
|
|
filename (`str`): The name of the README file to check.
|
|
start_prompt (`str`): The string to look for that introduces the model list.
|
|
end_prompt (`str`): The string to look for that ends the model list.
|
|
|
|
Returns:
|
|
`str`: The model list.
|
|
"""
|
|
with open(os.path.join(REPO_PATH, filename), "r", encoding="utf-8", newline="\n") as f:
|
|
lines = f.readlines()
|
|
# Find the start of the list.
|
|
start_index = 0
|
|
while not lines[start_index].startswith(start_prompt):
|
|
start_index += 1
|
|
start_index += 1
|
|
|
|
result = []
|
|
current_line = ""
|
|
end_index = start_index
|
|
|
|
# Keep going until the end of the list.
|
|
while not lines[end_index].startswith(end_prompt):
|
|
if lines[end_index].startswith("1."):
|
|
if len(current_line) > 1:
|
|
result.append(current_line)
|
|
current_line = lines[end_index]
|
|
elif len(lines[end_index]) > 1:
|
|
current_line = f"{current_line[:-1]} {lines[end_index].lstrip()}"
|
|
end_index += 1
|
|
if len(current_line) > 1:
|
|
result.append(current_line)
|
|
|
|
return "".join(result)
|
|
|
|
|
|
def convert_to_localized_md(model_list: str, localized_model_list: str, format_str: str) -> Tuple[bool, str]:
|
|
"""
|
|
Compare the model list from the main README to the one in a localized README.
|
|
|
|
Args:
|
|
model_list (`str`): The model list in the main README.
|
|
localized_model_list (`str`): The model list in one of the localized README.
|
|
format_str (`str`):
|
|
The template for a model entry in the localized README (look at the `format_model_list` in the entries of
|
|
`LOCALIZED_READMES` for examples).
|
|
|
|
Returns:
|
|
`Tuple[bool, str]`: A tuple where the first value indicates if the READMEs match or not, and the second value
|
|
is the correct localized README.
|
|
"""
|
|
|
|
def _rep(match):
|
|
title, model_link, paper_affiliations, paper_title_link, paper_authors, supplements = match.groups()
|
|
return format_str.format(
|
|
title=title,
|
|
model_link=model_link,
|
|
paper_affiliations=paper_affiliations,
|
|
paper_title_link=paper_title_link,
|
|
paper_authors=paper_authors,
|
|
supplements=" " + supplements.strip() if len(supplements) != 0 else "",
|
|
)
|
|
|
|
# This regex captures metadata from an English model description, including model title, model link,
|
|
# affiliations of the paper, title of the paper, authors of the paper, and supplemental data (see DistilBERT for
|
|
# example).
|
|
_re_capture_meta = re.compile(
|
|
r"\*\*\[([^\]]*)\]\(([^\)]*)\)\*\* \(from ([^)]*)\)[^\[]*([^\)]*\)).*?by (.*?[A-Za-z\*]{2,}?)\. (.*)$"
|
|
)
|
|
# This regex is used to synchronize link.
|
|
_re_capture_title_link = re.compile(r"\*\*\[([^\]]*)\]\(([^\)]*)\)\*\*")
|
|
|
|
if len(localized_model_list) == 0:
|
|
localized_model_index = {}
|
|
else:
|
|
try:
|
|
localized_model_index = {
|
|
re.search(r"\*\*\[([^\]]*)", line).groups()[0]: line
|
|
for line in localized_model_list.strip().split("\n")
|
|
}
|
|
except AttributeError:
|
|
raise AttributeError("A model name in localized READMEs cannot be recognized.")
|
|
|
|
model_keys = [re.search(r"\*\*\[([^\]]*)", line).groups()[0] for line in model_list.strip().split("\n")]
|
|
|
|
# We exclude keys in localized README not in the main one.
|
|
readmes_match = not any(k not in model_keys for k in localized_model_index)
|
|
localized_model_index = {k: v for k, v in localized_model_index.items() if k in model_keys}
|
|
|
|
for model in model_list.strip().split("\n"):
|
|
title, model_link = _re_capture_title_link.search(model).groups()
|
|
if title not in localized_model_index:
|
|
readmes_match = False
|
|
# Add an anchor white space behind a model description string for regex.
|
|
# If metadata cannot be captured, the English version will be directly copied.
|
|
localized_model_index[title] = _re_capture_meta.sub(_rep, model + " ")
|
|
elif _re_fill_pattern.search(localized_model_index[title]) is not None:
|
|
update = _re_capture_meta.sub(_rep, model + " ")
|
|
if update != localized_model_index[title]:
|
|
readmes_match = False
|
|
localized_model_index[title] = update
|
|
else:
|
|
# Synchronize link
|
|
localized_model_index[title] = _re_capture_title_link.sub(
|
|
f"**[{title}]({model_link})**", localized_model_index[title], count=1
|
|
)
|
|
|
|
sorted_index = sorted(localized_model_index.items(), key=lambda x: x[0].lower())
|
|
|
|
return readmes_match, "\n".join((x[1] for x in sorted_index)) + "\n"
|
|
|
|
|
|
def _find_text_in_file(filename: str, start_prompt: str, end_prompt: str) -> Tuple[str, int, int, List[str]]:
|
|
"""
|
|
Find the text in a file between two prompts.
|
|
|
|
Args:
|
|
filename (`str`): The name of the file to look into.
|
|
start_prompt (`str`): The string to look for that introduces the content looked for.
|
|
end_prompt (`str`): The string to look for that ends the content looked for.
|
|
|
|
Returns:
|
|
Tuple[str, int, int, List[str]]: The content between the two prompts, the index of the start line in the
|
|
original file, the index of the end line in the original file and the list of lines of that file.
|
|
"""
|
|
with open(filename, "r", encoding="utf-8", newline="\n") as f:
|
|
lines = f.readlines()
|
|
# Find the start prompt.
|
|
start_index = 0
|
|
while not lines[start_index].startswith(start_prompt):
|
|
start_index += 1
|
|
start_index += 1
|
|
|
|
end_index = start_index
|
|
while not lines[end_index].startswith(end_prompt):
|
|
end_index += 1
|
|
end_index -= 1
|
|
|
|
while len(lines[start_index]) <= 1:
|
|
start_index += 1
|
|
while len(lines[end_index]) <= 1:
|
|
end_index -= 1
|
|
end_index += 1
|
|
return "".join(lines[start_index:end_index]), start_index, end_index, lines
|
|
|
|
|
|
def check_model_list_copy(overwrite: bool = False):
|
|
"""
|
|
Check the model lists in the README is consistent with the ones in the other READMES and also with `index.nmd`.
|
|
|
|
Args:
|
|
overwrite (`bool`, *optional*, defaults to `False`):
|
|
Whether or not to overwrite the copies when they don't match.
|
|
"""
|
|
# Fix potential doc links in the README
|
|
with open(os.path.join(REPO_PATH, "README.md"), "r", encoding="utf-8", newline="\n") as f:
|
|
readme = f.read()
|
|
new_readme = readme.replace("https://huggingface.co/transformers", "https://huggingface.co/docs/transformers")
|
|
new_readme = new_readme.replace(
|
|
"https://huggingface.co/docs/main/transformers", "https://huggingface.co/docs/transformers/main"
|
|
)
|
|
if new_readme != readme:
|
|
if overwrite:
|
|
with open(os.path.join(REPO_PATH, "README.md"), "w", encoding="utf-8", newline="\n") as f:
|
|
f.write(new_readme)
|
|
else:
|
|
raise ValueError(
|
|
"The main README contains wrong links to the documentation of Transformers. Run `make fix-copies` to "
|
|
"automatically fix them."
|
|
)
|
|
|
|
md_list = get_model_list(
|
|
filename="README.md",
|
|
start_prompt=LOCALIZED_READMES["README.md"]["start_prompt"],
|
|
end_prompt=LOCALIZED_READMES["README.md"]["end_prompt"],
|
|
)
|
|
|
|
# Build the converted Markdown.
|
|
converted_md_lists = []
|
|
for filename, value in LOCALIZED_READMES.items():
|
|
_start_prompt = value["start_prompt"]
|
|
_end_prompt = value["end_prompt"]
|
|
_format_model_list = value["format_model_list"]
|
|
|
|
localized_md_list = get_model_list(filename, _start_prompt, _end_prompt)
|
|
readmes_match, converted_md_list = convert_to_localized_md(md_list, localized_md_list, _format_model_list)
|
|
|
|
converted_md_lists.append((filename, readmes_match, converted_md_list, _start_prompt, _end_prompt))
|
|
|
|
# Compare the converted Markdowns
|
|
for converted_md_list in converted_md_lists:
|
|
filename, readmes_match, converted_md, _start_prompt, _end_prompt = converted_md_list
|
|
|
|
if filename == "README.md":
|
|
continue
|
|
if overwrite:
|
|
_, start_index, end_index, lines = _find_text_in_file(
|
|
filename=os.path.join(REPO_PATH, filename), start_prompt=_start_prompt, end_prompt=_end_prompt
|
|
)
|
|
with open(os.path.join(REPO_PATH, filename), "w", encoding="utf-8", newline="\n") as f:
|
|
f.writelines(lines[:start_index] + [converted_md] + lines[end_index:])
|
|
elif not readmes_match:
|
|
raise ValueError(
|
|
f"The model list in the README changed and the list in `{filename}` has not been updated. Run "
|
|
"`make fix-copies` to fix this."
|
|
)
|
|
|
|
|
|
# Map a model name with the name it has in the README for the check_readme check
|
|
SPECIAL_MODEL_NAMES = {
|
|
"Bert Generation": "BERT For Sequence Generation",
|
|
"BigBird": "BigBird-RoBERTa",
|
|
"Data2VecAudio": "Data2Vec",
|
|
"Data2VecText": "Data2Vec",
|
|
"Data2VecVision": "Data2Vec",
|
|
"DonutSwin": "Swin Transformer",
|
|
"Marian": "MarianMT",
|
|
"MaskFormerSwin": "Swin Transformer",
|
|
"OpenAI GPT-2": "GPT-2",
|
|
"OpenAI GPT": "GPT",
|
|
"Perceiver": "Perceiver IO",
|
|
"SAM": "Segment Anything",
|
|
"ViT": "Vision Transformer (ViT)",
|
|
}
|
|
|
|
# Update this list with the models that shouldn't be in the README. This only concerns modular models or those who do
|
|
# not have an associated paper.
|
|
MODELS_NOT_IN_README = [
|
|
"BertJapanese",
|
|
"Encoder decoder",
|
|
"FairSeq Machine-Translation",
|
|
"HerBERT",
|
|
"RetriBERT",
|
|
"Speech Encoder decoder",
|
|
"Speech2Text",
|
|
"Speech2Text2",
|
|
"TimmBackbone",
|
|
"Vision Encoder decoder",
|
|
"VisionTextDualEncoder",
|
|
]
|
|
|
|
# Template for new entries to add in the main README when we have missing models.
|
|
README_TEMPLATE = (
|
|
"1. **[{model_name}](https://huggingface.co/docs/main/transformers/model_doc/{model_type})** (from "
|
|
"<FILL INSTITUTION>) released with the paper [<FILL PAPER TITLE>](<FILL ARKIV LINK>) by <FILL AUTHORS>."
|
|
)
|
|
|
|
|
|
def check_readme(overwrite: bool = False):
|
|
"""
|
|
Check if the main README contains all the models in the library or not.
|
|
|
|
Args:
|
|
overwrite (`bool`, *optional*, defaults to `False`):
|
|
Whether or not to add an entry for the missing models using `README_TEMPLATE`.
|
|
"""
|
|
info = LOCALIZED_READMES["README.md"]
|
|
models, start_index, end_index, lines = _find_text_in_file(
|
|
os.path.join(REPO_PATH, "README.md"),
|
|
info["start_prompt"],
|
|
info["end_prompt"],
|
|
)
|
|
models_in_readme = [re.search(r"\*\*\[([^\]]*)", line).groups()[0] for line in models.strip().split("\n")]
|
|
|
|
model_names_mapping = transformers_module.models.auto.configuration_auto.MODEL_NAMES_MAPPING
|
|
absents = [
|
|
(key, name)
|
|
for key, name in model_names_mapping.items()
|
|
if SPECIAL_MODEL_NAMES.get(name, name) not in models_in_readme
|
|
]
|
|
# Remove exceptions
|
|
absents = [(key, name) for key, name in absents if name not in MODELS_NOT_IN_README]
|
|
if len(absents) > 0 and not overwrite:
|
|
print(absents)
|
|
raise ValueError(
|
|
"The main README doesn't contain all models, run `make fix-copies` to fill it with the missing model(s)"
|
|
" then complete the generated entries.\nIf the model is not supposed to be in the main README, add it to"
|
|
" the list `MODELS_NOT_IN_README` in utils/check_copies.py.\nIf it has a different name in the repo than"
|
|
" in the README, map the correspondence in `SPECIAL_MODEL_NAMES` in utils/check_copies.py."
|
|
)
|
|
|
|
new_models = [README_TEMPLATE.format(model_name=name, model_type=key) for key, name in absents]
|
|
|
|
all_models = models.strip().split("\n") + new_models
|
|
all_models = sorted(all_models, key=lambda x: re.search(r"\*\*\[([^\]]*)", x).groups()[0].lower())
|
|
all_models = "\n".join(all_models) + "\n"
|
|
|
|
if all_models != models:
|
|
if overwrite:
|
|
print("Fixing the main README.")
|
|
with open(os.path.join(REPO_PATH, "README.md"), "w", encoding="utf-8", newline="\n") as f:
|
|
f.writelines(lines[:start_index] + [all_models] + lines[end_index:])
|
|
else:
|
|
raise ValueError("The main README model list is not properly sorted. Run `make fix-copies` to fix this.")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
parser = argparse.ArgumentParser()
|
|
parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
|
|
args = parser.parse_args()
|
|
|
|
check_readme(args.fix_and_overwrite)
|
|
check_copies(args.fix_and_overwrite)
|
|
check_full_copies(args.fix_and_overwrite)
|