From 8609449b6364490fbdde0cbf98a7d002c92e37b3 Mon Sep 17 00:00:00 2001 From: Isotr0py <41363108+Isotr0py@users.noreply.github.com> Date: Sat, 4 Nov 2023 04:06:10 +0800 Subject: [PATCH] Auto download missing model for `bert_gen.py` (#146) * auto download missing model * support openi * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix wrong delete * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * pass pre-commit * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix repeat login --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> --- bert/bert_models.json | 14 ++++++++++++++ bert_gen.py | 3 ++- config.py | 3 +++ default_config.yml | 3 ++- text/__init__.py | 20 ++++++++++++++++++++ text/bert_utils.py | 23 +++++++++++++++++++++++ text/chinese_bert.py | 16 ++++++++-------- text/english_bert_mock.py | 17 ++++++++++------- text/japanese_bert.py | 18 ++++++++++-------- 9 files changed, 92 insertions(+), 25 deletions(-) create mode 100644 bert/bert_models.json create mode 100644 text/bert_utils.py diff --git a/bert/bert_models.json b/bert/bert_models.json new file mode 100644 index 0000000..61d4e6a --- /dev/null +++ b/bert/bert_models.json @@ -0,0 +1,14 @@ +{ + "deberta-v2-large-japanese": { + "repo_id": "ku-nlp/deberta-v2-large-japanese", + "files": ["spm.model", "pytorch_model.bin"] + }, + "chinese-roberta-wwm-ext-large": { + "repo_id": "hfl/chinese-roberta-wwm-ext-large", + "files": ["pytorch_model.bin"] + }, + "deberta-v3-large": { + "repo_id": "microsoft/deberta-v3-large", + "files": ["spm.model", "pytorch_model.bin"] + } +} diff --git a/bert_gen.py b/bert_gen.py index f067054..20e2cac 100644 --- a/bert_gen.py +++ b/bert_gen.py @@ -3,7 +3,7 @@ from multiprocessing import Pool import commons import utils from tqdm import tqdm -from text import cleaned_text_to_sequence, get_bert +from text import check_bert_models, cleaned_text_to_sequence, get_bert import argparse import torch.multiprocessing as mp from config import config @@ -57,6 +57,7 @@ if __name__ == "__main__": args, _ = parser.parse_known_args() config_path = args.config hps = utils.get_hparams_from_file(config_path) + check_bert_models() lines = [] with open(hps.data.training_files, encoding="utf-8") as f: lines.extend(f.readlines()) diff --git a/config.py b/config.py index 4859a69..9484fa3 100644 --- a/config.py +++ b/config.py @@ -195,7 +195,10 @@ class Config: with open(file=config_path, mode="r", encoding="utf-8") as file: yaml_config: Dict[str, any] = yaml.safe_load(file.read()) dataset_path: str = yaml_config["dataset_path"] + openi_token: str = yaml_config["openi_token"] self.dataset_path: str = dataset_path + self.mirror: str = yaml_config["mirror"] + self.openi_token: str = openi_token self.resample_config: Resample_config = Resample_config.from_dict( dataset_path, yaml_config["resample"] ) diff --git a/default_config.yml b/default_config.yml index b61a122..68511ae 100644 --- a/default_config.yml +++ b/default_config.yml @@ -5,7 +5,8 @@ # 每个数据集与其对应的模型存放至统一路径下，后续所有的路径配置均为相对于datasetPath的路径 # 不填或者填空则路径为相对于项目根目录的路径 dataset_path: "Data/你的数据集" - +mirror: "openi" # 模型镜像源 +openi_token: "1145141919810" # openi token # resample 音频重采样配置 # 注意， “:” 后需要加空格 diff --git a/text/__init__.py b/text/__init__.py index a45b650..54cbef1 100644 --- a/text/__init__.py +++ b/text/__init__.py @@ -26,3 +26,23 @@ def get_bert(norm_text, word2ph, language, device): lang_bert_func_map = {"ZH": zh_bert, "EN": en_bert, "JP": jp_bert} bert = lang_bert_func_map[language](norm_text, word2ph, device) return bert + + +def check_bert_models(): + import json + from pathlib import Path + + from config import config + from .bert_utils import _check_bert + + if config.mirror.lower() == "openi": + import openi + + kwargs = {"token": config.openi_token} if config.openi_token else {} + openi.login(**kwargs) + + with open("./bert/bert_models.json", "r") as fp: + models = json.load(fp) + for k, v in models.items(): + local_path = Path("./bert").joinpath(k) + _check_bert(v["repo_id"], v["files"], local_path) diff --git a/text/bert_utils.py b/text/bert_utils.py new file mode 100644 index 0000000..7e0c4a9 --- /dev/null +++ b/text/bert_utils.py @@ -0,0 +1,23 @@ +from pathlib import Path + +from huggingface_hub import hf_hub_download + +from config import config + + +MIRROR: str = config.mirror + + +def _check_bert(repo_id, files, local_path): + for file in files: + if not Path(local_path).joinpath(file).exists(): + if MIRROR.lower() == "openi": + import openi + + openi.model.download_model( + "Stardust_minus/Bert-VITS2", repo_id.split("/")[-1], "./bert" + ) + else: + hf_hub_download( + repo_id, file, local_dir=local_path, local_dir_use_symlinks=False + ) diff --git a/text/chinese_bert.py b/text/chinese_bert.py index 6a65e8d..36f1e2a 100644 --- a/text/chinese_bert.py +++ b/text/chinese_bert.py @@ -1,9 +1,13 @@ -import torch import sys -from transformers import AutoTokenizer, AutoModelForMaskedLM + +import torch +from transformers import AutoModelForMaskedLM, AutoTokenizer + from config import config -tokenizer = AutoTokenizer.from_pretrained("./bert/chinese-roberta-wwm-ext-large") +LOCAL_PATH = "./bert/chinese-roberta-wwm-ext-large" + +tokenizer = AutoTokenizer.from_pretrained(LOCAL_PATH) models = dict() @@ -18,9 +22,7 @@ def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): if not device: device = "cuda" if device not in models.keys(): - models[device] = AutoModelForMaskedLM.from_pretrained( - "./bert/chinese-roberta-wwm-ext-large" - ).to(device) + models[device] = AutoModelForMaskedLM.from_pretrained(LOCAL_PATH).to(device) with torch.no_grad(): inputs = tokenizer(text, return_tensors="pt") for i in inputs: @@ -41,8 +43,6 @@ def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): if __name__ == "__main__": - import torch - word_level_feature = torch.rand(38, 1024) # 12个词,每个词1024维特征 word2phone = [ 1, diff --git a/text/english_bert_mock.py b/text/english_bert_mock.py index 11206d2..4aba0fc 100644 --- a/text/english_bert_mock.py +++ b/text/english_bert_mock.py @@ -1,9 +1,14 @@ -import torch -from transformers import DebertaV2Model, DebertaV2Tokenizer -from config import config import sys -tokenizer = DebertaV2Tokenizer.from_pretrained("./bert/deberta-v3-large") +import torch +from transformers import DebertaV2Model, DebertaV2Tokenizer + +from config import config + + +LOCAL_PATH = "./bert/deberta-v3-large" + +tokenizer = DebertaV2Tokenizer.from_pretrained(LOCAL_PATH) models = dict() @@ -18,9 +23,7 @@ def get_bert_feature(text, word2ph, device=config.bert_gen_config.device): if not device: device = "cuda" if device not in models.keys(): - models[device] = DebertaV2Model.from_pretrained("./bert/deberta-v3-large").to( - device - ) + models[device] = DebertaV2Model.from_pretrained(LOCAL_PATH).to(device) with torch.no_grad(): inputs = tokenizer(text, return_tensors="pt") for i in inputs: diff --git a/text/japanese_bert.py b/text/japanese_bert.py index 2fa9ea1..338726f 100644 --- a/text/japanese_bert.py +++ b/text/japanese_bert.py @@ -1,10 +1,14 @@ -import torch -from transformers import AutoTokenizer, AutoModelForMaskedLM import sys -from text.japanese import text2sep_kata -from config import config -tokenizer = AutoTokenizer.from_pretrained("./bert/deberta-v2-large-japanese") +import torch +from transformers import AutoModelForMaskedLM, AutoTokenizer + +from config import config +from text.japanese import text2sep_kata + +LOCAL_PATH = "./bert/deberta-v2-large-japanese" + +tokenizer = AutoTokenizer.from_pretrained(LOCAL_PATH) models = dict() @@ -27,9 +31,7 @@ def get_bert_feature_with_token(tokens, word2ph, device=config.bert_gen_config.d if not device: device = "cuda" if device not in models.keys(): - models[device] = AutoModelForMaskedLM.from_pretrained( - "./bert/deberta-v2-large-japanese" - ).to(device) + models[device] = AutoModelForMaskedLM.from_pretrained(LOCAL_PATH).to(device) with torch.no_grad(): inputs = torch.tensor(tokens).to(device).unsqueeze(0) token_type_ids = torch.zeros_like(inputs).to(device)