mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-03 21:00:08 +06:00
0041be5b3d
* LLaMA * sharding and docs * tweak * black * inits * ruff * LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP * init * no checkpoint * docs * ruff * type_vocab_size * tokenizer fixes * tokenizer fixes * Update tokenization_llama.py * Update tokenization_llama.py * Update configuration_llama.py * Update modeling_llama.py * tokenizer add_bos by default * licenses * remove decoder * norms and mlp * rope overhaul * tweaks * black * mention OPT implementation * off-by-one naming * typo * fix * tokenization fix and slicing bug * padding config * cleanup * black * update tests * undo typo * fix vocab caching logic * ruff * docbuilder * attn fix from BlackSamorez * initial feedback * typo * docs * llama case * llama case * load checkpoint docs * comment about tokenizer * tokenizer defaults * clear past_key_values if use_cache=False * last tweaks * last tweaks * last tweaks * last tweaks --------- Co-authored-by: Stella Biderman <stellabiderman@gmail.com>
88 lines
3.0 KiB
Python
88 lines
3.0 KiB
Python
# 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 inspect
|
|
import re
|
|
|
|
from transformers.utils import direct_transformers_import
|
|
|
|
|
|
# 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.
|
|
transformers = direct_transformers_import(PATH_TO_TRANSFORMERS)
|
|
|
|
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 = {
|
|
"DecisionTransformerConfig",
|
|
"EncoderDecoderConfig",
|
|
"RagConfig",
|
|
"SpeechEncoderDecoderConfig",
|
|
"VisionEncoderDecoderConfig",
|
|
"VisionTextDualEncoderConfig",
|
|
"LlamaConfig",
|
|
}
|
|
|
|
|
|
def get_checkpoint_from_config_class(config_class):
|
|
checkpoint = None
|
|
|
|
# source code of `config_class`
|
|
config_source = inspect.getsource(config_class)
|
|
checkpoints = _re_checkpoint.findall(config_source)
|
|
|
|
# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
|
|
# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
|
|
for ckpt_name, ckpt_link in checkpoints:
|
|
# allow the link to end with `/`
|
|
if ckpt_link.endswith("/"):
|
|
ckpt_link = ckpt_link[:-1]
|
|
|
|
# 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 = ckpt_name
|
|
break
|
|
|
|
return checkpoint
|
|
|
|
|
|
def check_config_docstrings_have_checkpoints():
|
|
configs_without_checkpoint = []
|
|
|
|
for config_class in list(CONFIG_MAPPING.values()):
|
|
checkpoint = get_checkpoint_from_config_class(config_class)
|
|
|
|
name = config_class.__name__
|
|
if checkpoint is None 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()
|