diff --git a/docs/module_usage/tutorials/speech_modules/text_to_pinyin.en.md b/docs/module_usage/tutorials/speech_modules/text_to_pinyin.en.md new file mode 100644 index 0000000000..f56bd00cd4 --- /dev/null +++ b/docs/module_usage/tutorials/speech_modules/text_to_pinyin.en.md @@ -0,0 +1,182 @@ +--- +comments: true +--- + +# Tutorial for Text To Pinyin Module + +## I. Overview +Text to Pinyin is commonly used in the frontend of TTS to convert input Chinese text into a phonetic sequence with tones, providing pronunciation basis for subsequent acoustic models and audio generation. + +## II. Supported Model List + + + + + + + + + + + + + + +
ModelDownload linkModel sizeIntroduction
G2PWModelG2PWModel606M g2pW is an open-source text to pinyin model, commonly used in the frontend of TTS. It converts input Chinese text into a tonal Pinyin sequence, providing pronunciation basis for subsequent acoustic models and audio generation
+ +## III. Quick Integration +Before quick integration, you need to install the PaddleX wheel package. For the installation method, please refer to the [PaddleX Local Installation Tutorial](../../../installation/installation.en.md). After installing the wheel package, a few lines of code can complete the inference of the text to pinyin module. You can switch models under this module freely, and you can also integrate the model inference of the text to pinyin module into your project. + + +```python +from paddlex import create_model +model = create_model(model_name="G2PWModel") +output = model.predict(input="欢迎使用飞桨", batch_size=1) +for res in output: + res.print() + res.save_to_json(save_path="./output/res.json") +``` + +After running, the result obtained is: + +```bash +{'res': {'input_path': '欢迎使用飞桨', 'result': ['huan1', 'ying2', 'shi3', 'yong4', 'fei1', 'jiang3']}} +``` + +The meanings of the runtime parameters are as follows: +- `input_path`: The storage path of the input text. +- `result`: Pinyin converted from the input text. + +Related methods, parameters, and explanations are as follows: +* `create_model` for text to pinyin model, with specific explanations as follows: + + + + + + + + + + + + + + + + + + + + + + + + +
ParameterDescriptionTypeOptionsDefault Value
model_nameThe name of the modelstrG2PWModelG2PWModel
model_dirThe storage path of the modelstrNoneNone
+ +* The `model_name` must be specified. After specifying `model_name`, the built-in model parameters of PaddleX are used by default. If `model_dir` is specified, the user-defined model is used. + +* The `predict()` method of the text to pinyin model is called for inference and prediction. The parameters of the `predict()` method are `input` and `batch_size`, with specific explanations as follows: + + + + + + + + + + + + + + + + + + + + + + + + + +
ParameterDescriptionTypeOptionsDefault Value
inputData to be predictedstr +
    +
  • Input text, such as: 欢迎使用飞桨
    • +
+		None
batch_sizeBatch sizeintCurrently only supports 11
+ +* The prediction results are processed as `dict` type for each sample and support the operation of saving as a `json` file: + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
MethodDescriptionParameterParameter TypeParameter DescriptionDefault Value
print()Print the result to the terminalformat_jsonboolWhether to format the output content with JSON indentationTrue
indentintSpecify the indentation level to beautify the output JSON data, making it more readable. This is only effective when format_json is True4
ensure_asciiboolControl whether to escape non-ASCII characters to Unicode. When set to True, all non-ASCII characters will be escaped; False retains the original characters. This is only effective when format_json is TrueFalse
save_to_json()Save the result as a file in json formatsave_pathstrThe file path for saving. When it is a directory, the saved file name will match the input file nameNone
indentintSpecify the indentation level to beautify the output JSON data, making it more readable. This is only effective when format_json is True4
ensure_asciiboolControl whether to escape non-ASCII characters to Unicode. When set to True, all non-ASCII characters will be escaped; False retains the original characters. This is only effective when format_json is TrueFalse
+ +* Additionally, the prediction results can also be obtained through attributes, as follows: + + + + + + + + + + + + +
AttributeDescription
jsonGet the prediction result in json format
+ +For more information on using PaddleX's single-model inference APIs, please refer to the [PaddleX Single-Model Python Script Usage Instructions](../../instructions/model_python_API.en.md). diff --git a/docs/module_usage/tutorials/speech_modules/text_to_pinyin.md b/docs/module_usage/tutorials/speech_modules/text_to_pinyin.md new file mode 100644 index 0000000000..67a7f1804c --- /dev/null +++ b/docs/module_usage/tutorials/speech_modules/text_to_pinyin.md @@ -0,0 +1,179 @@ +--- +comments: true +--- + +# 文本转拼音模块使用教程 + +## 一、概述 +文本到拼音常用于语音合成的前端，将输入的中文文本转换为带声调的拼音序列，为后续的声学模型和模型生成提供发音依据。 + +## 二、支持模型列表 + + + + + + + + + + + + + + +
模型模型下载链接模型大小介绍
G2PWModelG2PWModel606M g2pW 开源的文本到拼音模型，常用于语音合成的前端，将输入的中文文本转换为带声调的拼音序列，为后续的声学模型和模型生成提供发音依据
+ +## 三、快速集成 +在快速集成前，首先需要安装 PaddleX 的 wheel 包，wheel的安装方式请参考[PaddleX本地安装教程](../../../installation/installation.md)。完成 wheel 包的安装后，几行代码即可完成文本转拼音模块的推理，可以任意切换该模块下的模型，您也可以将文本转拼音模块中的模型推理集成到您的项目中。 + +```python +from paddlex import create_model +model = create_model(model_name="G2PWModel") +output = model.predict(input="欢迎使用飞桨", batch_size=1) +for res in output: + res.print() + res.save_to_json(save_path="./output/res.json") +``` +运行后，得到的结果为： +```bash +{'res': {'input_path': '欢迎使用飞桨', 'result': ['huan1', 'ying2', 'shi3', 'yong4', 'fei1', 'jiang3']}} +``` +运行结果参数含义如下： +- `input_path`: 输入文本 +- `result`: 输入文本转换后的拼音 + +相关方法、参数等说明如下： +* `create_model`文本转拼音模型，具体说明如下： + + + + + + + + + + + + + + + + + + + + + + + + +
参数参数说明参数类型可选项默认值
model_name模型名称strG2PWModelG2PWModel
model_dir模型存储路径str无无
+ +* 其中，`model_name` 必须指定，指定 `model_name` 后，默认使用 PaddleX 内置的模型参数，在此基础上，指定 `model_dir` 时，使用用户自定义的模型。 + +* 调用文本转拼音模型的 `predict()` 方法进行推理预测，`predict()` 方法参数有 `input` 和 `batch_size`，具体说明如下： + + + + + + + + + + + + + + + + + + + + + + + + + +
参数参数说明参数类型可选项默认值
input待预测数据str +
    +
  • 对应文本，如：欢迎使用飞桨
    • +
+		无
batch_size批大小int目前仅支持11
+ +* 对预测结果进行处理，每个样本的预测结果均为对应的Result对象，支持保存为`json`文件的操作: + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
方法方法说明参数参数类型参数说明默认值
print()打印结果到终端format_jsonbool是否对输出内容进行使用 JSON 缩进格式化True
indentint指定缩进级别，以美化输出的 JSON 数据，使其更具可读性，仅当 format_json 为 True 时有效4
ensure_asciibool控制是否将非 ASCII 字符转义为 Unicode。设置为 True 时，所有非 ASCII 字符将被转义；False 则保留原始字符，仅当format_json为True时有效False
save_to_json()将结果保存为json格式的文件save_pathstr保存的文件路径，当为目录时，保存文件命名与输入文件类型命名一致无
indentint指定缩进级别，以美化输出的 JSON 数据，使其更具可读性，仅当 format_json 为 True 时有效4
ensure_asciibool控制是否将非 ASCII 字符转义为 Unicode。设置为 True 时，所有非 ASCII 字符将被转义；False 则保留原始字符，仅当format_json为True时有效False
+ +* 此外，也支持通过属性获取预测结果，具体如下： + + + + + + + + + + + + + +
属性属性说明
json获取预测的json格式的结果
+ +关于更多 PaddleX 的单模型推理的 API 的使用方法，可以参考[PaddleX单模型Python脚本使用说明](../../instructions/model_python_API.md)。 diff --git a/paddlex/configs/modules/text_to_pinyin/G2PWModel.yaml b/paddlex/configs/modules/text_to_pinyin/G2PWModel.yaml new file mode 100644 index 0000000000..e05af7b031 --- /dev/null +++ b/paddlex/configs/modules/text_to_pinyin/G2PWModel.yaml @@ -0,0 +1,11 @@ +Global: + model: G2PWModel + mode: predict # only support predict + device: gpu:0 + output: "output" + +Predict: + batch_size: 1 + input: "欢迎使用飞桨" + kernel_option: + run_mode: paddle diff --git a/paddlex/inference/common/batch_sampler/__init__.py b/paddlex/inference/common/batch_sampler/__init__.py index 42f09a622a..eb0f5f8720 100644 --- a/paddlex/inference/common/batch_sampler/__init__.py +++ b/paddlex/inference/common/batch_sampler/__init__.py @@ -18,3 +18,4 @@ from .ts_batch_sampler import TSBatchSampler from .det_3d_batch_sampler import Det3DBatchSampler from .audio_batch_sampler import AudioBatchSampler +from .text_batch_sampler import TextBatchSampler diff --git a/paddlex/inference/common/batch_sampler/text_batch_sampler.py b/paddlex/inference/common/batch_sampler/text_batch_sampler.py new file mode 100644 index 0000000000..52fc751e8e --- /dev/null +++ b/paddlex/inference/common/batch_sampler/text_batch_sampler.py @@ -0,0 +1,61 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from ....utils import logging +from .base_batch_sampler import BaseBatchSampler + + +class TextBatchSampler(BaseBatchSampler): + def __init__(self): + """Initializes the BaseBatchSampler. + + Args: + batch_size (int, optional): The size of each batch. Only support 1. + """ + super().__init__() + self.batch_size = 1 + + def sample(self, inputs): + """Generate list of input file path. + + Args: + inputs (str): file path. + + Yields: + list: list of file path. + """ + if isinstance(inputs, str): + yield [inputs] + else: + logging.warning( + f"Not supported input data type! Only `str` are supported, but got: {input}." + ) + + @BaseBatchSampler.batch_size.setter + def batch_size(self, batch_size): + """Sets the batch size. + + Args: + batch_size (int): The batch size to set. + + Raises: + Warning: If the batch size is not equal 1. + """ + # only support batch size 1 + if batch_size != 1: + logging.warning( + f"audio batch sampler only support batch size 1, but got {batch_size}." + ) + else: + self._batch_size = batch_size diff --git a/paddlex/inference/models/__init__.py b/paddlex/inference/models/__init__.py index 4cfa66c8f7..253dc7c98f 100644 --- a/paddlex/inference/models/__init__.py +++ b/paddlex/inference/models/__init__.py @@ -38,7 +38,7 @@ from .face_feature import FaceFeaturePredictor from .open_vocabulary_detection import OVDetPredictor from .open_vocabulary_segmentation import OVSegPredictor - +from .text_to_pinyin import TextToPinyinPredictor # from .table_recognition import TablePredictor # from .general_recognition import ShiTuRecPredictor diff --git a/paddlex/inference/models/common/tokenizer/tokenizer_utils_base.py b/paddlex/inference/models/common/tokenizer/tokenizer_utils_base.py index e12ec1879b..1c83cec5bb 100644 --- a/paddlex/inference/models/common/tokenizer/tokenizer_utils_base.py +++ b/paddlex/inference/models/common/tokenizer/tokenizer_utils_base.py @@ -16,7 +16,7 @@ import io import json import os - +import shutil import warnings from collections import OrderedDict, UserDict from dataclasses import dataclass, field @@ -27,6 +27,8 @@ import lazy_paddle as paddle from .....utils import logging +from .....utils.download import download +from .....utils.cache import CACHE_DIR __all__ = [ "AddedToken", @@ -1604,16 +1606,11 @@ def from_pretrained(cls, pretrained_model_name_or_path, *args, **kwargs): resolved_vocab_files[file_id] = file_path continue else: - logging.warnings("need to download tokenizer, but not support yet.") - # tokenizer download not support yet - # resolved_vocab_files[file_id] = resolve_file_path( - # pretrained_model_name_or_path, - # [file_path], - # subfolder, - # cache_dir=cache_dir, - # from_aistudio=from_aistudio, - # from_hf_hub=from_hf_hub, - # ) + download_path = os.path.join( + CACHE_DIR, "official_models", pretrained_model_name_or_path, file_id + ) + download(file_path, download_path) + resolved_vocab_files[file_id] = download_path for file_id, file_path in resolved_vocab_files.items(): if resolved_vocab_files[file_id] is not None: @@ -1901,6 +1898,20 @@ def _save_pretrained( return file_names + (added_tokens_file,) + def save_resources(self, save_directory): + """ + Save tokenizer related resources to `resource_files_names` indicating + files under `save_directory` by copying directly. Override it if necessary. + + Args: + save_directory (str): Directory to save files into. + """ + for name, file_name in self.resource_files_names.items(): + src_path = self.init_kwargs[name] + dst_path = os.path.join(save_directory, file_name) + if os.path.abspath(src_path) != os.path.abspath(dst_path): + shutil.copyfile(src_path, dst_path) + def tokenize( self, text: str, diff --git a/paddlex/inference/models/text_to_pinyin/__init__.py b/paddlex/inference/models/text_to_pinyin/__init__.py new file mode 100644 index 0000000000..82dca7f7f5 --- /dev/null +++ b/paddlex/inference/models/text_to_pinyin/__init__.py @@ -0,0 +1,15 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from .predictor import TextToPinyinPredictor diff --git a/paddlex/inference/models/text_to_pinyin/predictor.py b/paddlex/inference/models/text_to_pinyin/predictor.py new file mode 100644 index 0000000000..fe6238fe08 --- /dev/null +++ b/paddlex/inference/models/text_to_pinyin/predictor.py @@ -0,0 +1,88 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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 lazy_paddle as paddle +import numpy as np + +from ....utils.func_register import FuncRegister +from ...common.batch_sampler import TextBatchSampler + +from ..base import BasicPredictor +from .result import TextToPinyinResult +from ....modules.text_to_pinyin.model_list import MODELS + + +class TextToPinyinPredictor(BasicPredictor): + + entities = MODELS + + def __init__(self, *args, **kwargs): + """Initializes TextSegmentPredictor. + + Args: + *args: Arbitrary positional arguments passed to the superclass. + **kwargs: Arbitrary keyword arguments passed to the superclass. + """ + super().__init__(*args, **kwargs) + self.model = self._build() + + def _build_batch_sampler(self): + """Builds and returns an TextBatchSampler instance. + + Returns: + TextBatchSampler: An instance of TextBatchSampler. + """ + return TextBatchSampler() + + def _get_result_class(self): + """Returns the result class, TextToPinyinResult. + + Returns: + type: The TextToPinyinResult class. + """ + return TextToPinyinResult + + def _build(self): + """Build the model. + + Returns: + G2PWOnnxConverter: An instance of G2PWOnnxConverter. + """ + from .processors import ( + G2PWOnnxConverter, + ) + + # build model + model = G2PWOnnxConverter( + model_dir=self.model_dir, style="pinyin", enable_non_tradional_chinese=True + ) + return model + + def process(self, batch_data): + """ + Process a batch of data through the preprocessing, inference, and postprocessing. + + Args: + batch_data (List[Union[str], ...]): A batch of input text data. + + Returns: + dict: A dictionary containing the input path and result. The result include the output pinyin dict. + """ + + result = self.model(batch_data[0])[0] + + return { + "input_path": batch_data, + "result": [result], + } diff --git a/paddlex/inference/models/text_to_pinyin/processors.py b/paddlex/inference/models/text_to_pinyin/processors.py new file mode 100644 index 0000000000..a38264c0b8 --- /dev/null +++ b/paddlex/inference/models/text_to_pinyin/processors.py @@ -0,0 +1,547 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +""" +Credits + This code is modified from https://github.com/GitYCC/g2pW +""" +import json +import os +import re +from typing import Any +from typing import Dict +from typing import List +from typing import Tuple + +import numpy as np +import onnxruntime +from opencc import OpenCC +from ..common.tokenizer import BertTokenizer +from ....utils.download import download +from pypinyin import pinyin +from pypinyin import Style + +simplified_charcters = 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+ +traditional_characters = 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鐔鐗馗鐙鐝鐠鐡鐦鐨鐩鐫鐬鐱鐳鐶鐻鐽鐿鑀鑅鑌鑐鑕鑚鑛鑢鑤鑥鑪鑭鑯鑱鑴鑵鑷钁钃镻閆閈閌閎閒閔閗閟閡関閤閤閧閬閲閹閺閻閼閽閿闇闉闋闐闑闒闓闘闚闞闟闠闤闥阞阢阤阨阬阯阹阼阽陁陑陔陛陜陡陥陬騭陴険陼陾隂隃隈隒隗隞隠隣隤隩隮隰顴隳隷隹雂雈雉雊雎雑雒雗雘雚雝雟雩雰雱驛霂霅霈霊霑霒霓霙霝霢霣霤霨霩霪霫霮靁靆靉靑靚靣靦靪靮靰靳靷靸靺靼靿鞀鞃鞄鞌鞗鞙鞚鞝鞞鞡鞣鞨鞫鞬鞮鞶鞹鞾韃韅韉馱韍韎韔韖韘韝韞韡韣韭韮韱韹韺頀颳頄頇頊頍頎頏頒頖頞頠頫頬顱頯頲頴頼顇顋顑顒顓顔顕顚顜顢顣顬顳颭颮颱颶颸颺颻颽颾颿飀飂飈飌飜飡飣飤飥飩飫飮飱飶餀餂餄餎餇餈餑餔餕餖餗餚餛餜餟餠餤餧餩餪餫餬餮餱餲餳餺餻餼餽餿饁饅饇饉饊饍饎饐饘饟饢馘馥馝馡馣騮騾馵馹駃駄駅駆駉駋駑駓駔駗駘駙駜駡駢駪駬駰駴駸駹駽駾騂騄騅騆騉騋騍騏驎騑騒験騕騖騠騢騣騤騧驤騵騶騸騺驀驂驃驄驆驈驊驌驍驎驏驒驔驖驙驦驩驫骺鯁骫骭骯骱骴骶骷髏骾髁髂髄髆髈髐髑髕髖髙髝髞髟髡髣髧髪髫髭髯髲髳髹髺髽髾鬁鬃鬅鬈鬋鬎鬏鬐鬑鬒鬖鬗鬘鬙鬠鬣鬪鬫鬬鬮鬯鬰鬲鬵鬷魆魈魊魋魍魎魑魖鰾魛魟魣魦魨魬魴魵魸鮀鮁鮆鮌鮎鮑鮒鮓鮚鮞鮟鱇鮠鮦鮨鮪鮭鮶鮸鮿鯀鯄鯆鯇鯈鯔鯕鯖鯗鯙鯠鯤鯥鯫鯰鯷鯸鯿鰂鰆鶼鰉鰋鰐鰒鰕鰛鰜鰣鰤鰥鰦鰨鰩鰮鰳鰶鰷鱺鰼鰽鱀鱄鱅鱆鱈鱎鱐鱓鱔鱖鱘鱟鱠鱣鱨鱭鱮鱲鱵鱻鲅鳦鳧鳯鳲鳷鳻鴂鴃鴄鴆鴈鴎鴒鴔鴗鴛鴦鴝鵒鴟鴠鴢鴣鴥鴯鶓鴳鴴鴷鴽鵀鵁鵂鵓鵖鵙鵜鶘鵞鵟鵩鵪鵫鵵鵷鵻鵾鶂鶊鶏鶒鶖鶗鶡鶤鶦鶬鶱鶲鶵鶸鶹鶺鶿鷀鷁鷃鷄鷇鷈鷉鷊鷏鷓鷕鷖鷙鷞鷟鷥鷦鷯鷩鷫鷭鷳鷴鷽鷾鷿鸂鸇鸊鸏鸑鸒鸓鸕鸛鸜鸝鹸鹹鹺麀麂麃麄麇麋麌麐麑麒麚麛麝麤麩麪麫麮麯麰麺麾黁黈黌黢黒黓黕黙黝黟黥黦黧黮黰黱黲黶黹黻黼黽黿鼂鼃鼅鼈鼉鼏鼐鼒鼕鼖鼙鼚鼛鼡鼩鼱鼪鼫鼯鼷鼽齁齆齇齈齉齌齎齏齔齕齗齙齚齜齞齟齬齠齢齣齧齩齮齯齰齱齵齾龎龑龒龔龖龘龝龡龢龤" + +assert len(simplified_charcters) == len(simplified_charcters) + +s2t_dict = {} +t2s_dict = {} +for i, item in enumerate(simplified_charcters): + s2t_dict[item] = traditional_characters[i] + t2s_dict[traditional_characters[i]] = item + + +def tranditional_to_simplified(text: str) -> str: + return "".join([t2s_dict[item] if item in t2s_dict else item for item in text]) + + +ANCHOR_CHAR = "▁" + + +def prepare_onnx_input( + tokenizer, + labels: List[str], + char2phonemes: Dict[str, List[int]], + chars: List[str], + texts: List[str], + query_ids: List[int], + use_mask: bool = False, + window_size: int = None, + max_len: int = 512, +) -> Dict[str, np.array]: + if window_size is not None: + truncated_texts, truncated_query_ids = _truncate_texts( + window_size=window_size, texts=texts, query_ids=query_ids + ) + input_ids = [] + token_type_ids = [] + attention_masks = [] + phoneme_masks = [] + char_ids = [] + position_ids = [] + + for idx in range(len(texts)): + text = (truncated_texts if window_size else texts)[idx].lower() + query_id = (truncated_query_ids if window_size else query_ids)[idx] + + try: + tokens, text2token, token2text = tokenize_and_map( + tokenizer=tokenizer, text=text + ) + except Exception: + print(f'warning: text "{text}" is invalid') + return {} + + text, query_id, tokens, text2token, token2text = _truncate( + max_len=max_len, + text=text, + query_id=query_id, + tokens=tokens, + text2token=text2token, + token2text=token2text, + ) + + processed_tokens = ["[CLS]"] + tokens + ["[SEP]"] + + input_id = list(np.array(tokenizer.convert_tokens_to_ids(processed_tokens))) + token_type_id = list(np.zeros((len(processed_tokens),), dtype=int)) + attention_mask = list(np.ones((len(processed_tokens),), dtype=int)) + + query_char = text[query_id] + phoneme_mask = ( + [1 if i in char2phonemes[query_char] else 0 for i in range(len(labels))] + if use_mask + else [1] * len(labels) + ) + char_id = chars.index(query_char) + position_id = text2token[query_id] + 1 # [CLS] token locate at first place + + input_ids.append(input_id) + token_type_ids.append(token_type_id) + attention_masks.append(attention_mask) + phoneme_masks.append(phoneme_mask) + char_ids.append(char_id) + position_ids.append(position_id) + + outputs = { + "input_ids": np.array(input_ids).astype(np.int64), + "token_type_ids": np.array(token_type_ids).astype(np.int64), + "attention_masks": np.array(attention_masks).astype(np.int64), + "phoneme_masks": np.array(phoneme_masks).astype(np.float32), + "char_ids": np.array(char_ids).astype(np.int64), + "position_ids": np.array(position_ids).astype(np.int64), + } + return outputs + + +def _truncate_texts( + window_size: int, texts: List[str], query_ids: List[int] +) -> Tuple[List[str], List[int]]: + truncated_texts = [] + truncated_query_ids = [] + for text, query_id in zip(texts, query_ids): + start = max(0, query_id - window_size // 2) + end = min(len(text), query_id + window_size // 2) + truncated_text = text[start:end] + truncated_texts.append(truncated_text) + + truncated_query_id = query_id - start + truncated_query_ids.append(truncated_query_id) + return truncated_texts, truncated_query_ids + + +def _truncate( + max_len: int, + text: str, + query_id: int, + tokens: List[str], + text2token: List[int], + token2text: List[Tuple[int]], +): + truncate_len = max_len - 2 + if len(tokens) <= truncate_len: + return (text, query_id, tokens, text2token, token2text) + + token_position = text2token[query_id] + + token_start = token_position - truncate_len // 2 + token_end = token_start + truncate_len + font_exceed_dist = -token_start + back_exceed_dist = token_end - len(tokens) + if font_exceed_dist > 0: + token_start += font_exceed_dist + token_end += font_exceed_dist + elif back_exceed_dist > 0: + token_start -= back_exceed_dist + token_end -= back_exceed_dist + + start = token2text[token_start][0] + end = token2text[token_end - 1][1] + + return ( + text[start:end], + query_id - start, + tokens[token_start:token_end], + [i - token_start if i is not None else None for i in text2token[start:end]], + [(s - start, e - start) for s, e in token2text[token_start:token_end]], + ) + + +def get_phoneme_labels( + polyphonic_chars: List[List[str]], +) -> Tuple[List[str], Dict[str, List[int]]]: + labels = sorted(list(set([phoneme for char, phoneme in polyphonic_chars]))) + char2phonemes = {} + for char, phoneme in polyphonic_chars: + if char not in char2phonemes: + char2phonemes[char] = [] + char2phonemes[char].append(labels.index(phoneme)) + return labels, char2phonemes + + +def get_char_phoneme_labels( + polyphonic_chars: List[List[str]], +) -> Tuple[List[str], Dict[str, List[int]]]: + labels = sorted( + list(set([f"{char} {phoneme}" for char, phoneme in polyphonic_chars])) + ) + char2phonemes = {} + for char, phoneme in polyphonic_chars: + if char not in char2phonemes: + char2phonemes[char] = [] + char2phonemes[char].append(labels.index(f"{char} {phoneme}")) + return labels, char2phonemes + + +def wordize_and_map(text: str): + words = [] + index_map_from_text_to_word = [] + index_map_from_word_to_text = [] + while len(text) > 0: + match_space = re.match(r"^ +", text) + if match_space: + space_str = match_space.group(0) + index_map_from_text_to_word += [None] * len(space_str) + text = text[len(space_str) :] + continue + + match_en = re.match(r"^[a-zA-Z0-9]+", text) + if match_en: + en_word = match_en.group(0) + + word_start_pos = len(index_map_from_text_to_word) + word_end_pos = word_start_pos + len(en_word) + index_map_from_word_to_text.append((word_start_pos, word_end_pos)) + + index_map_from_text_to_word += [len(words)] * len(en_word) + + words.append(en_word) + text = text[len(en_word) :] + else: + word_start_pos = len(index_map_from_text_to_word) + word_end_pos = word_start_pos + 1 + index_map_from_word_to_text.append((word_start_pos, word_end_pos)) + + index_map_from_text_to_word += [len(words)] + + words.append(text[0]) + text = text[1:] + return words, index_map_from_text_to_word, index_map_from_word_to_text + + +def tokenize_and_map(tokenizer, text: str): + words, text2word, word2text = wordize_and_map(text=text) + + tokens = [] + index_map_from_token_to_text = [] + for word, (word_start, word_end) in zip(words, word2text): + word_tokens = tokenizer.tokenize(word) + + if len(word_tokens) == 0 or word_tokens == ["[UNK]"]: + index_map_from_token_to_text.append((word_start, word_end)) + tokens.append("[UNK]") + else: + current_word_start = word_start + for word_token in word_tokens: + word_token_len = len(re.sub(r"^##", "", word_token)) + index_map_from_token_to_text.append( + (current_word_start, current_word_start + word_token_len) + ) + current_word_start = current_word_start + word_token_len + tokens.append(word_token) + + index_map_from_text_to_token = text2word + for i, (token_start, token_end) in enumerate(index_map_from_token_to_text): + for token_pos in range(token_start, token_end): + index_map_from_text_to_token[token_pos] = i + + return tokens, index_map_from_text_to_token, index_map_from_token_to_text + + +def _load_config(config_path: os.PathLike): + import importlib.util + + spec = importlib.util.spec_from_file_location("__init__", config_path) + config = importlib.util.module_from_spec(spec) + spec.loader.exec_module(config) + return config + + +default_config_dict = { + "manual_seed": 1313, + "model_source": "bert-base-chinese", + "window_size": 32, + "num_workers": 2, + "use_mask": True, + "use_char_phoneme": False, + "use_conditional": True, + "param_conditional": { + "affect_location": "softmax", + "bias": True, + "char-linear": True, + "pos-linear": False, + "char+pos-second": True, + "char+pos-second_lowrank": False, + "lowrank_size": 0, + "char+pos-second_fm": False, + "fm_size": 0, + "fix_mode": None, + "count_json": "train.count.json", + }, + "lr": 5e-5, + "val_interval": 200, + "num_iter": 10000, + "use_focal": False, + "param_focal": {"alpha": 0.0, "gamma": 0.7}, + "use_pos": True, + "param_pos ": { + "weight": 0.1, + "pos_joint_training": True, + "train_pos_path": "train.pos", + "valid_pos_path": "dev.pos", + "test_pos_path": "test.pos", + }, +} + + +def load_config(config_path: os.PathLike, use_default: bool = False): + config = _load_config(config_path) + if use_default: + for attr, val in default_config_dict.items(): + if not hasattr(config, attr): + setattr(config, attr, val) + elif isinstance(val, dict): + d = getattr(config, attr) + for dict_k, dict_v in val.items(): + if dict_k not in d: + d[dict_k] = dict_v + return config + + +def predict( + session, onnx_input: Dict[str, Any], labels: List[str] +) -> Tuple[List[str], List[float]]: + all_preds = [] + all_confidences = [] + probs = session.run( + [], + { + "input_ids": onnx_input["input_ids"], + "token_type_ids": onnx_input["token_type_ids"], + "attention_mask": onnx_input["attention_masks"], + "phoneme_mask": onnx_input["phoneme_masks"], + "char_ids": onnx_input["char_ids"], + "position_ids": onnx_input["position_ids"], + }, + )[0] + + preds = np.argmax(probs, axis=1).tolist() + max_probs = [] + for index, arr in zip(preds, probs.tolist()): + max_probs.append(arr[index]) + all_preds += [labels[pred] for pred in preds] + all_confidences += max_probs + + return all_preds, all_confidences + + +class G2PWOnnxConverter: + def __init__( + self, + model_dir: str, + style: str = "bopomofo", + model_source: str = None, + enable_non_tradional_chinese: bool = False, + ): + + sess_options = onnxruntime.SessionOptions() + sess_options.graph_optimization_level = ( + onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL + ) + sess_options.execution_mode = onnxruntime.ExecutionMode.ORT_SEQUENTIAL + sess_options.intra_op_num_threads = 2 + self.session_g2pW = onnxruntime.InferenceSession( + os.path.join(model_dir, "g2pW.onnx"), sess_options=sess_options + ) + self.config = load_config( + config_path=os.path.join(model_dir, "config.py"), use_default=True + ) + + self.model_source = model_source if model_source else self.config.model_source + self.enable_opencc = enable_non_tradional_chinese + + self.tokenizer = BertTokenizer.from_pretrained(self.config.model_source) + + polyphonic_chars_path = os.path.join(model_dir, "POLYPHONIC_CHARS.txt") + monophonic_chars_path = os.path.join(model_dir, "MONOPHONIC_CHARS.txt") + self.polyphonic_chars = [ + line.split("\t") + for line in open(polyphonic_chars_path, encoding="utf-8") + .read() + .strip() + .split("\n") + ] + self.non_polyphonic = { + "一", + "不", + "和", + "咋", + "嗲", + "剖", + "差", + "攢", + "倒", + "難", + "奔", + "勁", + "拗", + "肖", + "瘙", + "誒", + "泊", + "听", + "噢", + } + self.non_monophonic = {"似", "攢"} + self.monophonic_chars = [ + line.split("\t") + for line in open(monophonic_chars_path, encoding="utf-8") + .read() + .strip() + .split("\n") + ] + self.labels, self.char2phonemes = ( + get_char_phoneme_labels(polyphonic_chars=self.polyphonic_chars) + if self.config.use_char_phoneme + else get_phoneme_labels(polyphonic_chars=self.polyphonic_chars) + ) + + self.chars = sorted(list(self.char2phonemes.keys())) + + self.polyphonic_chars_new = set(self.chars) + for char in self.non_polyphonic: + if char in self.polyphonic_chars_new: + self.polyphonic_chars_new.remove(char) + + self.monophonic_chars_dict = { + char: phoneme for char, phoneme in self.monophonic_chars + } + for char in self.non_monophonic: + if char in self.monophonic_chars_dict: + self.monophonic_chars_dict.pop(char) + + self.pos_tags = ["UNK", "A", "C", "D", "I", "N", "P", "T", "V", "DE", "SHI"] + + with open( + os.path.join(model_dir, "bopomofo_to_pinyin_wo_tune_dict.json"), + "r", + encoding="utf-8", + ) as fr: + self.bopomofo_convert_dict = json.load(fr) + self.style_convert_func = { + "bopomofo": lambda x: x, + "pinyin": self._convert_bopomofo_to_pinyin, + }[style] + + with open( + os.path.join(model_dir, "char_bopomofo_dict.json"), "r", encoding="utf-8" + ) as fr: + self.char_bopomofo_dict = json.load(fr) + + if self.enable_opencc: + self.cc = OpenCC("s2tw") + + def _convert_bopomofo_to_pinyin(self, bopomofo: str) -> str: + tone = bopomofo[-1] + assert tone in "12345" + component = self.bopomofo_convert_dict.get(bopomofo[:-1]) + if component: + return component + tone + else: + print(f'Warning: "{bopomofo}" cannot convert to pinyin') + return None + + def __call__(self, sentences: List[str]) -> List[List[str]]: + if isinstance(sentences, str): + sentences = [sentences] + + if self.enable_opencc: + translated_sentences = [] + for sent in sentences: + translated_sent = self.cc.convert(sent) + assert len(translated_sent) == len(sent) + translated_sentences.append(translated_sent) + sentences = translated_sentences + + texts, query_ids, sent_ids, partial_results = self._prepare_data( + sentences=sentences + ) + if len(texts) == 0: + # sentences no polyphonic words + return partial_results + + onnx_input = prepare_onnx_input( + tokenizer=self.tokenizer, + labels=self.labels, + char2phonemes=self.char2phonemes, + chars=self.chars, + texts=texts, + query_ids=query_ids, + use_mask=self.config.use_mask, + window_size=None, + ) + + preds, confidences = predict( + session=self.session_g2pW, onnx_input=onnx_input, labels=self.labels + ) + if self.config.use_char_phoneme: + preds = [pred.split(" ")[1] for pred in preds] + + results = partial_results + for sent_id, query_id, pred in zip(sent_ids, query_ids, preds): + results[sent_id][query_id] = self.style_convert_func(pred) + + return results + + def _prepare_data( + self, sentences: List[str] + ) -> Tuple[List[str], List[int], List[int], List[List[str]]]: + texts, query_ids, sent_ids, partial_results = [], [], [], [] + for sent_id, sent in enumerate(sentences): + # pypinyin works well for Simplified Chinese than Traditional Chinese + sent_s = tranditional_to_simplified(sent) + pypinyin_result = pinyin( + sent_s, neutral_tone_with_five=True, style=Style.TONE3 + ) + partial_result = [None] * len(sent) + for i, char in enumerate(sent): + if char in self.polyphonic_chars_new: + texts.append(sent) + query_ids.append(i) + sent_ids.append(sent_id) + elif char in self.monophonic_chars_dict: + partial_result[i] = self.style_convert_func( + self.monophonic_chars_dict[char] + ) + elif char in self.char_bopomofo_dict: + partial_result[i] = pypinyin_result[i][0] + # partial_result[i] = self.style_convert_func(self.char_bopomofo_dict[char][0]) + else: + partial_result[i] = pypinyin_result[i][0] + + partial_results.append(partial_result) + return texts, query_ids, sent_ids, partial_results diff --git a/paddlex/inference/models/text_to_pinyin/result.py b/paddlex/inference/models/text_to_pinyin/result.py new file mode 100644 index 0000000000..d9dc2b5d26 --- /dev/null +++ b/paddlex/inference/models/text_to_pinyin/result.py @@ -0,0 +1,21 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from ...common.result import BaseResult + + +class TextToPinyinResult(BaseResult): + + def __init__(self, data: dict) -> None: + super().__init__(data) diff --git a/paddlex/inference/utils/official_models.py b/paddlex/inference/utils/official_models.py index 4988c361d7..22452138da 100644 --- a/paddlex/inference/utils/official_models.py +++ b/paddlex/inference/utils/official_models.py @@ -333,6 +333,7 @@ "PP-DocLayout-M": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0rc0/PP-DocLayout-M_infer.tar", "PP-DocLayout-S": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0rc0/PP-DocLayout-S_infer.tar", "BEVFusion": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0rc0/BEVFusion_infer.tar", + "G2PWModel": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0rc0/G2PWModel_1.1.tar", } diff --git a/paddlex/modules/text_to_pinyin/__init__.py b/paddlex/modules/text_to_pinyin/__init__.py new file mode 100644 index 0000000000..c6cec820d0 --- /dev/null +++ b/paddlex/modules/text_to_pinyin/__init__.py @@ -0,0 +1,18 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from .dataset_checker import TextToPinyinDatasetChecker +from .trainer import TextToPinyinTrainer +from .evaluator import TextToPinyinEvaluator +from .exportor import TextToPinyinExportor diff --git a/paddlex/modules/text_to_pinyin/dataset_checker.py b/paddlex/modules/text_to_pinyin/dataset_checker.py new file mode 100644 index 0000000000..bb21671c9b --- /dev/null +++ b/paddlex/modules/text_to_pinyin/dataset_checker.py @@ -0,0 +1,27 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from .model_list import MODELS +from ..base import BaseDatasetChecker +from ...utils.errors import UnsupportedAPIError + + +class TextToPinyinDatasetChecker(BaseDatasetChecker): + """Dataset Checker for G2PWModel Model""" + + entities = MODELS + + def __init__(self, config): + # not support for now + raise UnsupportedAPIError("G2PWModel model not support data check for now.") diff --git a/paddlex/modules/text_to_pinyin/evaluator.py b/paddlex/modules/text_to_pinyin/evaluator.py new file mode 100644 index 0000000000..18207a2403 --- /dev/null +++ b/paddlex/modules/text_to_pinyin/evaluator.py @@ -0,0 +1,27 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from .model_list import MODELS +from ..base import BaseEvaluator +from ...utils.errors import UnsupportedAPIError + + +class TextToPinyinEvaluator(BaseEvaluator): + """Instance G2PWModel Model Evaluator""" + + entities = MODELS + + def __init__(self, config): + # not support for now + raise UnsupportedAPIError("G2PWModel model not support evaluate for now.") diff --git a/paddlex/modules/text_to_pinyin/exportor.py b/paddlex/modules/text_to_pinyin/exportor.py new file mode 100644 index 0000000000..29064f1718 --- /dev/null +++ b/paddlex/modules/text_to_pinyin/exportor.py @@ -0,0 +1,27 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from .model_list import MODELS +from ..base import BaseExportor +from ...utils.errors import UnsupportedAPIError + + +class TextToPinyinExportor(BaseExportor): + """Instance G2PWModel Model Exportor""" + + entities = MODELS + + def __init__(self, config): + # not support for now + raise UnsupportedAPIError("G2PWModel model not support export for now.") diff --git a/paddlex/modules/text_to_pinyin/model_list.py b/paddlex/modules/text_to_pinyin/model_list.py new file mode 100644 index 0000000000..8a7ff4e978 --- /dev/null +++ b/paddlex/modules/text_to_pinyin/model_list.py @@ -0,0 +1,18 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + + +MODELS = [ + "G2PWModel", +] diff --git a/paddlex/modules/text_to_pinyin/trainer.py b/paddlex/modules/text_to_pinyin/trainer.py new file mode 100644 index 0000000000..95a57d2891 --- /dev/null +++ b/paddlex/modules/text_to_pinyin/trainer.py @@ -0,0 +1,40 @@ +# copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve. +# +# 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. + +from .model_list import MODELS +from ..base import BaseTrainer +from ...utils.errors import UnsupportedAPIError + + +class TextToPinyinTrainer(BaseTrainer): + """Instance G2PWModel Model Trainer""" + + entities = MODELS + + def __init__(self, config): + # not support for now + raise UnsupportedAPIError("G2PWModel model not support train for now.") + + def update_config(self): + """update training config""" + pass + + def get_train_kwargs(self) -> dict: + """get key-value arguments of model training function + + Returns: + dict: the arguments of training function. + """ + train_args = {"device": self.get_device()} + return train_args diff --git a/requirements.txt b/requirements.txt index ab4f62f262..cc749ec135 100644 --- a/requirements.txt +++ b/requirements.txt @@ -51,6 +51,9 @@ jinja2 regex ######## For Speech ####### soundfile +opencc +onnxruntime +pypinyin ######## For 3D BEVFusion ####### nuscenes-devkit pyquaternion