Hui Zhang
2 years ago
commit
bdf876ea7b
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Before Width: | Height: | Size: 84 KiB |
@ -1,13 +1,8 @@
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aiofiles
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faiss-cpu
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fastapi
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librosa
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numpy
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paddlenlp
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paddlepaddle
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paddlespeech
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praatio==5.0.0
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pydantic
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python-multipartscikit_learn
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SoundFile
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python-multipart
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scikit_learn
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starlette
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uvicorn
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@ -0,0 +1,198 @@
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import os
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from .util import get_ngpu
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from .util import MAIN_ROOT
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from .util import run_cmd
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class SAT:
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def __init__(self):
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# pretrain model path
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self.zh_pretrain_model_path = os.path.realpath(
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"source/model/erniesat_aishell3_ckpt_1.2.0")
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self.en_pretrain_model_path = os.path.realpath(
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"source/model/erniesat_vctk_ckpt_1.2.0")
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self.cross_pretrain_model_path = os.path.realpath(
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"source/model/erniesat_aishell3_vctk_ckpt_1.2.0")
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self.zh_voc_model_path = os.path.realpath(
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"source/model/hifigan_aishell3_ckpt_0.2.0")
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self.eb_voc_model_path = os.path.realpath(
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"source/model/hifigan_vctk_ckpt_0.2.0")
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self.cross_voc_model_path = os.path.realpath(
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"source/model/hifigan_aishell3_ckpt_0.2.0")
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self.BIN_DIR = os.path.join(MAIN_ROOT,
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"paddlespeech/t2s/exps/ernie_sat")
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def zh_synthesize_edit(self,
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old_str: str,
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new_str: str,
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input_name: os.PathLike,
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output_name: os.PathLike,
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task_name: str="synthesize",
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erniesat_ckpt_name: str="snapshot_iter_289500.pdz"):
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if task_name not in ['synthesize', 'edit']:
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print("task name only in ['edit', 'synthesize']")
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return None
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# 推理文件配置
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config_path = os.path.join(self.zh_pretrain_model_path, "default.yaml")
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phones_dict = os.path.join(self.zh_pretrain_model_path,
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"phone_id_map.txt")
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erniesat_ckpt = os.path.join(self.zh_pretrain_model_path,
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erniesat_ckpt_name)
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erniesat_stat = os.path.join(self.zh_pretrain_model_path,
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"speech_stats.npy")
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voc = "hifigan_aishell3"
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voc_config = os.path.join(self.zh_voc_model_path, "default.yaml")
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voc_ckpt = os.path.join(self.zh_voc_model_path,
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"snapshot_iter_2500000.pdz")
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voc_stat = os.path.join(self.zh_voc_model_path, "feats_stats.npy")
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cmd = self.get_cmd(
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task_name=task_name,
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input_name=input_name,
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old_str=old_str,
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new_str=new_str,
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config_path=config_path,
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phones_dict=phones_dict,
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erniesat_ckpt=erniesat_ckpt,
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erniesat_stat=erniesat_stat,
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voc=voc,
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voc_config=voc_config,
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voc_ckpt=voc_ckpt,
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voc_stat=voc_stat,
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output_name=output_name,
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source_lang="zh",
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target_lang="zh")
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return run_cmd(cmd, output_name)
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def crossclone(self,
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old_str: str,
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new_str: str,
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input_name: os.PathLike,
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output_name: os.PathLike,
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source_lang: str,
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target_lang: str,
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erniesat_ckpt_name: str="snapshot_iter_489000.pdz"):
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# 推理文件配置
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config_path = os.path.join(self.cross_pretrain_model_path,
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"default.yaml")
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phones_dict = os.path.join(self.cross_pretrain_model_path,
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"phone_id_map.txt")
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erniesat_ckpt = os.path.join(self.cross_pretrain_model_path,
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erniesat_ckpt_name)
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erniesat_stat = os.path.join(self.cross_pretrain_model_path,
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"speech_stats.npy")
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voc = "hifigan_aishell3"
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voc_config = os.path.join(self.cross_voc_model_path, "default.yaml")
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voc_ckpt = os.path.join(self.cross_voc_model_path,
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"snapshot_iter_2500000.pdz")
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voc_stat = os.path.join(self.cross_voc_model_path, "feats_stats.npy")
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task_name = "synthesize"
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cmd = self.get_cmd(
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task_name=task_name,
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input_name=input_name,
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old_str=old_str,
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new_str=new_str,
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config_path=config_path,
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phones_dict=phones_dict,
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erniesat_ckpt=erniesat_ckpt,
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erniesat_stat=erniesat_stat,
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voc=voc,
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voc_config=voc_config,
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voc_ckpt=voc_ckpt,
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voc_stat=voc_stat,
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output_name=output_name,
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source_lang=source_lang,
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target_lang=target_lang)
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return run_cmd(cmd, output_name)
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def en_synthesize_edit(self,
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old_str: str,
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new_str: str,
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input_name: os.PathLike,
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output_name: os.PathLike,
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task_name: str="synthesize",
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erniesat_ckpt_name: str="snapshot_iter_199500.pdz"):
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# 推理文件配置
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config_path = os.path.join(self.en_pretrain_model_path, "default.yaml")
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phones_dict = os.path.join(self.en_pretrain_model_path,
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"phone_id_map.txt")
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erniesat_ckpt = os.path.join(self.en_pretrain_model_path,
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erniesat_ckpt_name)
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erniesat_stat = os.path.join(self.en_pretrain_model_path,
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"speech_stats.npy")
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voc = "hifigan_aishell3"
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voc_config = os.path.join(self.zh_voc_model_path, "default.yaml")
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voc_ckpt = os.path.join(self.zh_voc_model_path,
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"snapshot_iter_2500000.pdz")
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voc_stat = os.path.join(self.zh_voc_model_path, "feats_stats.npy")
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cmd = self.get_cmd(
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task_name=task_name,
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input_name=input_name,
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old_str=old_str,
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new_str=new_str,
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config_path=config_path,
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phones_dict=phones_dict,
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erniesat_ckpt=erniesat_ckpt,
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erniesat_stat=erniesat_stat,
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voc=voc,
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voc_config=voc_config,
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voc_ckpt=voc_ckpt,
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voc_stat=voc_stat,
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output_name=output_name,
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source_lang="en",
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target_lang="en")
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return run_cmd(cmd, output_name)
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def get_cmd(self,
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task_name: str,
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input_name: str,
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old_str: str,
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new_str: str,
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config_path: str,
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phones_dict: str,
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erniesat_ckpt: str,
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erniesat_stat: str,
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voc: str,
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voc_config: str,
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voc_ckpt: str,
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voc_stat: str,
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output_name: str,
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source_lang: str,
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target_lang: str):
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ngpu = get_ngpu()
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cmd = f"""
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FLAGS_allocator_strategy=naive_best_fit \
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FLAGS_fraction_of_gpu_memory_to_use=0.01 \
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python3 {self.BIN_DIR}/synthesize_e2e.py \
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--task_name={task_name} \
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--wav_path={input_name} \
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--old_str='{old_str}' \
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--new_str='{new_str}' \
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--source_lang={source_lang} \
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--target_lang={target_lang} \
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--erniesat_config={config_path} \
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--phones_dict={phones_dict} \
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--erniesat_ckpt={erniesat_ckpt} \
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--erniesat_stat={erniesat_stat} \
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--voc={voc} \
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--voc_config={voc_config} \
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--voc_ckpt={voc_ckpt} \
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--voc_stat={voc_stat} \
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--output_name={output_name} \
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--ngpu={ngpu}
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"""
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return cmd
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@ -0,0 +1,127 @@
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import os
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from .util import get_ngpu
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from .util import MAIN_ROOT
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from .util import run_cmd
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def find_max_ckpt(model_path):
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max_ckpt = 0
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for filename in os.listdir(model_path):
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if filename.endswith('.pdz'):
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files = filename[:-4]
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a1, a2, it = files.split("_")
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if int(it) > max_ckpt:
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max_ckpt = int(it)
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return max_ckpt
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class FineTune:
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def __init__(self):
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self.now_file_path = os.path.dirname(__file__)
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self.PYTHONPATH = os.path.join(MAIN_ROOT,
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"examples/other/tts_finetune/tts3")
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self.BIN_DIR = os.path.join(MAIN_ROOT,
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"paddlespeech/t2s/exps/fastspeech2")
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self.pretrained_model_dir = os.path.realpath(
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"source/model/fastspeech2_aishell3_ckpt_1.1.0")
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self.voc_model_dir = os.path.realpath(
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"source/model/hifigan_aishell3_ckpt_0.2.0")
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self.finetune_config = os.path.join("conf/tts3_finetune.yaml")
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def finetune(self, input_dir, exp_dir='temp', epoch=100):
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"""
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use cmd follow examples/other/tts_finetune/tts3/run.sh
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"""
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newdir_name = "newdir"
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new_dir = os.path.join(input_dir, newdir_name)
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mfa_dir = os.path.join(exp_dir, 'mfa_result')
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dump_dir = os.path.join(exp_dir, 'dump')
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output_dir = os.path.join(exp_dir, 'exp')
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lang = "zh"
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ngpu = get_ngpu()
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cmd = f"""
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# check oov
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python3 {self.PYTHONPATH}/local/check_oov.py \
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--input_dir={input_dir} \
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--pretrained_model_dir={self.pretrained_model_dir} \
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--newdir_name={newdir_name} \
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--lang={lang}
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# get mfa result
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python3 {self.PYTHONPATH}/local/get_mfa_result.py \
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--input_dir={new_dir} \
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--mfa_dir={mfa_dir} \
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--lang={lang}
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# generate durations.txt
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python3 {self.PYTHONPATH}/local/generate_duration.py \
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--mfa_dir={mfa_dir}
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# extract feature
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python3 {self.PYTHONPATH}/local/extract_feature.py \
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--duration_file="./durations.txt" \
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--input_dir={new_dir} \
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--dump_dir={dump_dir} \
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--pretrained_model_dir={self.pretrained_model_dir}
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# create finetune env
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python3 {self.PYTHONPATH}/local/prepare_env.py \
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--pretrained_model_dir={self.pretrained_model_dir} \
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--output_dir={output_dir}
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# finetune
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python3 {self.PYTHONPATH}/local/finetune.py \
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--pretrained_model_dir={self.pretrained_model_dir} \
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--dump_dir={dump_dir} \
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--output_dir={output_dir} \
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--ngpu={ngpu} \
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--epoch=100 \
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--finetune_config={self.finetune_config}
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"""
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print(cmd)
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return run_cmd(cmd, exp_dir)
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def synthesize(self, text, wav_name, out_wav_dir, exp_dir='temp'):
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voc = "hifigan_aishell3"
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dump_dir = os.path.join(exp_dir, 'dump')
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output_dir = os.path.join(exp_dir, 'exp')
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text_path = os.path.join(exp_dir, 'sentences.txt')
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lang = "zh"
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ngpu = get_ngpu()
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model_path = f"{output_dir}/checkpoints"
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ckpt = find_max_ckpt(model_path)
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# 生成对应的语句
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with open(text_path, "w", encoding='utf8') as f:
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f.write(wav_name + " " + text)
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cmd = f"""
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FLAGS_allocator_strategy=naive_best_fit \
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FLAGS_fraction_of_gpu_memory_to_use=0.01 \
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python3 {self.BIN_DIR}/../synthesize_e2e.py \
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--am=fastspeech2_aishell3 \
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--am_config={self.pretrained_model_dir}/default.yaml \
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--am_ckpt={output_dir}/checkpoints/snapshot_iter_{ckpt}.pdz \
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--am_stat={self.pretrained_model_dir}/speech_stats.npy \
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--voc={voc} \
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--voc_config={self.voc_model_dir}/default.yaml \
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--voc_ckpt={self.voc_model_dir}/snapshot_iter_2500000.pdz \
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--voc_stat={self.voc_model_dir}/feats_stats.npy \
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--lang={lang} \
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--text={text_path} \
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--output_dir={out_wav_dir} \
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--phones_dict={dump_dir}/phone_id_map.txt \
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--speaker_dict={dump_dir}/speaker_id_map.txt \
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--spk_id=0 \
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--ngpu={ngpu}
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"""
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out_path = os.path.join(out_wav_dir, f"{wav_name}.wav")
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return run_cmd(cmd, out_path)
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@ -0,0 +1,60 @@
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import os
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import shutil
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from .util import get_ngpu
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from .util import MAIN_ROOT
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from .util import run_cmd
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class VoiceCloneGE2E():
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def __init__(self):
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# Path 到指定路径上
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self.BIN_DIR = os.path.join(MAIN_ROOT, "paddlespeech/t2s/exps")
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# am
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self.am = "fastspeech2_aishell3"
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self.am_config = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/default.yaml"
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self.am_ckpt = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/snapshot_iter_96400.pdz"
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self.am_stat = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/speech_stats.npy"
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self.phones_dict = "source/model/fastspeech2_nosil_aishell3_vc1_ckpt_0.5/phone_id_map.txt"
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# voc
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self.voc = "pwgan_aishell3"
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self.voc_config = "source/model/pwg_aishell3_ckpt_0.5/default.yaml"
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self.voc_ckpt = "source/model/pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz"
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self.voc_stat = "source/model/pwg_aishell3_ckpt_0.5/feats_stats.npy"
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# ge2e
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self.ge2e_params_path = "source/model/ge2e_ckpt_0.3/step-3000000.pdparams"
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def vc(self, text, input_wav, out_wav):
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# input wav 需要形成临时单独文件夹
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_, full_file_name = os.path.split(input_wav)
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ref_audio_dir = os.path.realpath("tmp_dir/ge2e")
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if os.path.exists(ref_audio_dir):
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shutil.rmtree(ref_audio_dir)
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os.makedirs(ref_audio_dir, exist_ok=True)
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shutil.copy(input_wav, ref_audio_dir)
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output_dir = os.path.dirname(out_wav)
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ngpu = get_ngpu()
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cmd = f"""
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python3 {self.BIN_DIR}/voice_cloning.py \
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--am={self.am} \
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--am_config={self.am_config} \
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--am_ckpt={self.am_ckpt} \
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--am_stat={self.am_stat} \
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--voc={self.voc} \
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--voc_config={self.voc_config} \
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--voc_ckpt={self.voc_ckpt} \
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--voc_stat={self.voc_stat} \
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--ge2e_params_path={self.ge2e_params_path} \
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--text="{text}" \
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--input-dir={ref_audio_dir} \
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--output-dir={output_dir} \
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--phones-dict={self.phones_dict} \
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--ngpu={ngpu}
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"""
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output_name = os.path.join(output_dir, full_file_name)
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return run_cmd(cmd, output_name=output_name)
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@ -0,0 +1,56 @@
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import os
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import shutil
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from .util import get_ngpu
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from .util import MAIN_ROOT
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from .util import run_cmd
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class VoiceCloneTDNN():
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def __init__(self):
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||||
# Path 到指定路径上
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self.BIN_DIR = os.path.join(MAIN_ROOT, "paddlespeech/t2s/exps")
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self.am = "fastspeech2_aishell3"
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self.am_config = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/default.yaml"
|
||||
self.am_ckpt = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/snapshot_iter_96400.pdz"
|
||||
self.am_stat = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/speech_stats.npy"
|
||||
self.phones_dict = "source/model/fastspeech2_aishell3_ckpt_vc2_1.2.0/phone_id_map.txt"
|
||||
# voc
|
||||
self.voc = "pwgan_aishell3"
|
||||
self.voc_config = "source/model/pwg_aishell3_ckpt_0.5/default.yaml"
|
||||
self.voc_ckpt = "source/model/pwg_aishell3_ckpt_0.5/snapshot_iter_1000000.pdz"
|
||||
self.voc_stat = "source/model/pwg_aishell3_ckpt_0.5/feats_stats.npy"
|
||||
|
||||
def vc(self, text, input_wav, out_wav):
|
||||
# input wav 需要形成临时单独文件夹
|
||||
_, full_file_name = os.path.split(input_wav)
|
||||
ref_audio_dir = os.path.realpath("tmp_dir/tdnn")
|
||||
if os.path.exists(ref_audio_dir):
|
||||
shutil.rmtree(ref_audio_dir)
|
||||
os.makedirs(ref_audio_dir, exist_ok=True)
|
||||
shutil.copy(input_wav, ref_audio_dir)
|
||||
|
||||
output_dir = os.path.dirname(out_wav)
|
||||
ngpu = get_ngpu()
|
||||
|
||||
cmd = f"""
|
||||
python3 {self.BIN_DIR}/voice_cloning.py \
|
||||
--am={self.am} \
|
||||
--am_config={self.am_config} \
|
||||
--am_ckpt={self.am_ckpt} \
|
||||
--am_stat={self.am_stat} \
|
||||
--voc={self.voc} \
|
||||
--voc_config={self.voc_config} \
|
||||
--voc_ckpt={self.voc_ckpt} \
|
||||
--voc_stat={self.voc_stat} \
|
||||
--text="{text}" \
|
||||
--input-dir={ref_audio_dir} \
|
||||
--output-dir={output_dir} \
|
||||
--phones-dict={self.phones_dict} \
|
||||
--use_ecapa=True \
|
||||
--ngpu={ngpu}
|
||||
"""
|
||||
|
||||
output_name = os.path.join(output_dir, full_file_name)
|
||||
return run_cmd(cmd, output_name=output_name)
|
||||
@ -0,0 +1,88 @@
|
||||
import axios from 'axios'
|
||||
import {apiURL} from "./API.js"
|
||||
|
||||
// 上传音频-vc
|
||||
export async function vcUpload(params){
|
||||
const result = await axios.post(apiURL.VC_Upload, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 上传音频-sat
|
||||
export async function satUpload(params){
|
||||
const result = await axios.post(apiURL.SAT_Upload, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 上传音频-finetune
|
||||
export async function fineTuneUpload(params){
|
||||
const result = await axios.post(apiURL.FineTune_Upload, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 删除音频
|
||||
export async function vcDel(params){
|
||||
const result = await axios.post(apiURL.VC_Del, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 获取音频列表vc
|
||||
export async function vcList(){
|
||||
const result = await axios.get(apiURL.VC_List);
|
||||
return result
|
||||
}
|
||||
// 获取音频列表Sat
|
||||
export async function satList(){
|
||||
const result = await axios.get(apiURL.SAT_List);
|
||||
return result
|
||||
}
|
||||
|
||||
// 获取音频列表fineTune
|
||||
export async function fineTuneList(params){
|
||||
const result = await axios.post(apiURL.FineTune_List, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// fineTune 一键重置 获取新的文件夹
|
||||
export async function fineTuneNewDir(){
|
||||
const result = await axios.get(apiURL.FineTune_NewDir);
|
||||
return result
|
||||
}
|
||||
|
||||
// 获取音频数据
|
||||
export async function vcDownload(params){
|
||||
const result = await axios.post(apiURL.VC_Download, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 获取音频数据Base64
|
||||
export async function vcDownloadBase64(params){
|
||||
const result = await axios.post(apiURL.VC_Download_Base64, params);
|
||||
return result
|
||||
}
|
||||
|
||||
|
||||
// 克隆合成G2P
|
||||
export async function vcCloneG2P(params){
|
||||
const result = await axios.post(apiURL.VC_CloneG2p, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 克隆合成SAT
|
||||
export async function vcCloneSAT(params){
|
||||
const result = await axios.post(apiURL.VC_CloneSAT, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 克隆合成 - finetune 微调
|
||||
export async function vcCloneFineTune(params){
|
||||
const result = await axios.post(apiURL.VC_CloneFineTune, params);
|
||||
return result
|
||||
}
|
||||
|
||||
// 克隆合成 - finetune 合成
|
||||
export async function vcCloneFineTuneSyn(params){
|
||||
const result = await axios.post(apiURL.VC_CloneFineTuneSyn, params);
|
||||
return result
|
||||
}
|
||||
|
||||
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.cls.exps.panns.deploy.predict module
|
||||
=================================================
|
||||
|
||||
.. automodule:: paddlespeech.cls.exps.panns.deploy.predict
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.cls.exps.panns.export\_model module
|
||||
================================================
|
||||
|
||||
.. automodule:: paddlespeech.cls.exps.panns.export_model
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.cls.exps.panns.predict module
|
||||
==========================================
|
||||
|
||||
.. automodule:: paddlespeech.cls.exps.panns.predict
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.cls.exps.panns.train module
|
||||
========================================
|
||||
|
||||
.. automodule:: paddlespeech.cls.exps.panns.train
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.kws.exps.mdtc.plot\_det\_curve module
|
||||
==================================================
|
||||
|
||||
.. automodule:: paddlespeech.kws.exps.mdtc.plot_det_curve
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.decoders.ctcdecoder.scorer\_deprecated module
|
||||
==============================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.decoders.ctcdecoder.scorer_deprecated
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.decoders.recog\_bin module
|
||||
===========================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.decoders.recog_bin
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.decoders.scorers.ngram module
|
||||
==============================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.decoders.scorers.ngram
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.exps.deepspeech2.bin.deploy.client module
|
||||
==========================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.exps.deepspeech2.bin.deploy.client
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.exps.deepspeech2.bin.deploy.record module
|
||||
==========================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.exps.deepspeech2.bin.deploy.record
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.exps.deepspeech2.bin.deploy.send module
|
||||
========================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.exps.deepspeech2.bin.deploy.send
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.exps.u2.trainer module
|
||||
=======================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.exps.u2.trainer
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.exps.u2\_kaldi.bin.recog module
|
||||
================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.exps.u2_kaldi.bin.recog
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.training.extensions.snapshot module
|
||||
====================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.training.extensions.snapshot
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.training.extensions.visualizer module
|
||||
======================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.training.extensions.visualizer
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.training.updaters.trainer module
|
||||
=================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.training.updaters.trainer
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.add\_deltas module
|
||||
=============================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.add_deltas
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.channel\_selector module
|
||||
===================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.channel_selector
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.cmvn module
|
||||
======================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.cmvn
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.functional module
|
||||
============================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.functional
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.perturb module
|
||||
=========================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.perturb
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,24 +0,0 @@
|
||||
paddlespeech.s2t.transform package
|
||||
==================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 4
|
||||
|
||||
paddlespeech.s2t.transform.add_deltas
|
||||
paddlespeech.s2t.transform.channel_selector
|
||||
paddlespeech.s2t.transform.cmvn
|
||||
paddlespeech.s2t.transform.functional
|
||||
paddlespeech.s2t.transform.perturb
|
||||
paddlespeech.s2t.transform.spec_augment
|
||||
paddlespeech.s2t.transform.spectrogram
|
||||
paddlespeech.s2t.transform.transform_interface
|
||||
paddlespeech.s2t.transform.transformation
|
||||
paddlespeech.s2t.transform.wpe
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.spec\_augment module
|
||||
===============================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.spec_augment
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.spectrogram module
|
||||
=============================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.spectrogram
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.transform\_interface module
|
||||
======================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.transform_interface
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.transformation module
|
||||
================================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.transformation
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.s2t.transform.wpe module
|
||||
=====================================
|
||||
|
||||
.. automodule:: paddlespeech.s2t.transform.wpe
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.server.engine.acs.python.acs\_engine module
|
||||
========================================================
|
||||
|
||||
.. automodule:: paddlespeech.server.engine.acs.python.acs_engine
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.server.utils.log module
|
||||
====================================
|
||||
|
||||
.. automodule:: paddlespeech.server.utils.log
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.t2s.exps.stream\_play\_tts module
|
||||
==============================================
|
||||
|
||||
.. automodule:: paddlespeech.t2s.exps.stream_play_tts
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.t2s.models.ernie\_sat.mlm module
|
||||
=============================================
|
||||
|
||||
.. automodule:: paddlespeech.t2s.models.ernie_sat.mlm
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.t2s.models.vits.monotonic\_align.core module
|
||||
=========================================================
|
||||
|
||||
.. automodule:: paddlespeech.t2s.models.vits.monotonic_align.core
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
@ -1,16 +0,0 @@
|
||||
paddlespeech.t2s.models.vits.monotonic\_align package
|
||||
=====================================================
|
||||
|
||||
.. automodule:: paddlespeech.t2s.models.vits.monotonic_align
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 4
|
||||
|
||||
paddlespeech.t2s.models.vits.monotonic_align.core
|
||||
paddlespeech.t2s.models.vits.monotonic_align.setup
|
||||
@ -1,7 +0,0 @@
|
||||
paddlespeech.t2s.models.vits.monotonic\_align.setup module
|
||||
==========================================================
|
||||
|
||||
.. automodule:: paddlespeech.t2s.models.vits.monotonic_align.setup
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,44 @@
|
||||
###########################################################
|
||||
# DATA SETTING #
|
||||
###########################################################
|
||||
dataset_type: Ernie
|
||||
train_path: data/iwslt2012_zh/train.txt
|
||||
dev_path: data/iwslt2012_zh/dev.txt
|
||||
test_path: data/iwslt2012_zh/test.txt
|
||||
batch_size: 64
|
||||
num_workers: 2
|
||||
data_params:
|
||||
pretrained_token: ernie-3.0-base-zh
|
||||
punc_path: data/iwslt2012_zh/punc_vocab
|
||||
seq_len: 100
|
||||
|
||||
|
||||
###########################################################
|
||||
# MODEL SETTING #
|
||||
###########################################################
|
||||
model_type: ErnieLinear
|
||||
model:
|
||||
pretrained_token: ernie-3.0-base-zh
|
||||
num_classes: 4
|
||||
|
||||
###########################################################
|
||||
# OPTIMIZER SETTING #
|
||||
###########################################################
|
||||
optimizer_params:
|
||||
weight_decay: 1.0e-6 # weight decay coefficient.
|
||||
|
||||
scheduler_params:
|
||||
learning_rate: 1.0e-5 # learning rate.
|
||||
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
|
||||
|
||||
###########################################################
|
||||
# TRAINING SETTING #
|
||||
###########################################################
|
||||
max_epoch: 20
|
||||
num_snapshots: 5
|
||||
|
||||
###########################################################
|
||||
# OTHER SETTING #
|
||||
###########################################################
|
||||
num_snapshots: 10 # max number of snapshots to keep while training
|
||||
seed: 42 # random seed for paddle, random, and np.random
|
||||
@ -0,0 +1,44 @@
|
||||
###########################################################
|
||||
# DATA SETTING #
|
||||
###########################################################
|
||||
dataset_type: Ernie
|
||||
train_path: data/iwslt2012_zh/train.txt
|
||||
dev_path: data/iwslt2012_zh/dev.txt
|
||||
test_path: data/iwslt2012_zh/test.txt
|
||||
batch_size: 64
|
||||
num_workers: 2
|
||||
data_params:
|
||||
pretrained_token: ernie-3.0-medium-zh
|
||||
punc_path: data/iwslt2012_zh/punc_vocab
|
||||
seq_len: 100
|
||||
|
||||
|
||||
###########################################################
|
||||
# MODEL SETTING #
|
||||
###########################################################
|
||||
model_type: ErnieLinear
|
||||
model:
|
||||
pretrained_token: ernie-3.0-medium-zh
|
||||
num_classes: 4
|
||||
|
||||
###########################################################
|
||||
# OPTIMIZER SETTING #
|
||||
###########################################################
|
||||
optimizer_params:
|
||||
weight_decay: 1.0e-6 # weight decay coefficient.
|
||||
|
||||
scheduler_params:
|
||||
learning_rate: 1.0e-5 # learning rate.
|
||||
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
|
||||
|
||||
###########################################################
|
||||
# TRAINING SETTING #
|
||||
###########################################################
|
||||
max_epoch: 20
|
||||
num_snapshots: 5
|
||||
|
||||
###########################################################
|
||||
# OTHER SETTING #
|
||||
###########################################################
|
||||
num_snapshots: 10 # max number of snapshots to keep while training
|
||||
seed: 42 # random seed for paddle, random, and np.random
|
||||
@ -0,0 +1,44 @@
|
||||
###########################################################
|
||||
# DATA SETTING #
|
||||
###########################################################
|
||||
dataset_type: Ernie
|
||||
train_path: data/iwslt2012_zh/train.txt
|
||||
dev_path: data/iwslt2012_zh/dev.txt
|
||||
test_path: data/iwslt2012_zh/test.txt
|
||||
batch_size: 64
|
||||
num_workers: 2
|
||||
data_params:
|
||||
pretrained_token: ernie-3.0-mini-zh
|
||||
punc_path: data/iwslt2012_zh/punc_vocab
|
||||
seq_len: 100
|
||||
|
||||
|
||||
###########################################################
|
||||
# MODEL SETTING #
|
||||
###########################################################
|
||||
model_type: ErnieLinear
|
||||
model:
|
||||
pretrained_token: ernie-3.0-mini-zh
|
||||
num_classes: 4
|
||||
|
||||
###########################################################
|
||||
# OPTIMIZER SETTING #
|
||||
###########################################################
|
||||
optimizer_params:
|
||||
weight_decay: 1.0e-6 # weight decay coefficient.
|
||||
|
||||
scheduler_params:
|
||||
learning_rate: 1.0e-5 # learning rate.
|
||||
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
|
||||
|
||||
###########################################################
|
||||
# TRAINING SETTING #
|
||||
###########################################################
|
||||
max_epoch: 20
|
||||
num_snapshots: 5
|
||||
|
||||
###########################################################
|
||||
# OTHER SETTING #
|
||||
###########################################################
|
||||
num_snapshots: 10 # max number of snapshots to keep while training
|
||||
seed: 42 # random seed for paddle, random, and np.random
|
||||
@ -0,0 +1,44 @@
|
||||
###########################################################
|
||||
# DATA SETTING #
|
||||
###########################################################
|
||||
dataset_type: Ernie
|
||||
train_path: data/iwslt2012_zh/train.txt
|
||||
dev_path: data/iwslt2012_zh/dev.txt
|
||||
test_path: data/iwslt2012_zh/test.txt
|
||||
batch_size: 64
|
||||
num_workers: 2
|
||||
data_params:
|
||||
pretrained_token: ernie-3.0-nano-zh
|
||||
punc_path: data/iwslt2012_zh/punc_vocab
|
||||
seq_len: 100
|
||||
|
||||
|
||||
###########################################################
|
||||
# MODEL SETTING #
|
||||
###########################################################
|
||||
model_type: ErnieLinear
|
||||
model:
|
||||
pretrained_token: ernie-3.0-nano-zh
|
||||
num_classes: 4
|
||||
|
||||
###########################################################
|
||||
# OPTIMIZER SETTING #
|
||||
###########################################################
|
||||
optimizer_params:
|
||||
weight_decay: 1.0e-6 # weight decay coefficient.
|
||||
|
||||
scheduler_params:
|
||||
learning_rate: 1.0e-5 # learning rate.
|
||||
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
|
||||
|
||||
###########################################################
|
||||
# TRAINING SETTING #
|
||||
###########################################################
|
||||
max_epoch: 20
|
||||
num_snapshots: 5
|
||||
|
||||
###########################################################
|
||||
# OTHER SETTING #
|
||||
###########################################################
|
||||
num_snapshots: 10 # max number of snapshots to keep while training
|
||||
seed: 42 # random seed for paddle, random, and np.random
|
||||
@ -0,0 +1,44 @@
|
||||
###########################################################
|
||||
# DATA SETTING #
|
||||
###########################################################
|
||||
dataset_type: Ernie
|
||||
train_path: data/iwslt2012_zh/train.txt
|
||||
dev_path: data/iwslt2012_zh/dev.txt
|
||||
test_path: data/iwslt2012_zh/test.txt
|
||||
batch_size: 64
|
||||
num_workers: 2
|
||||
data_params:
|
||||
pretrained_token: ernie-tiny
|
||||
punc_path: data/iwslt2012_zh/punc_vocab
|
||||
seq_len: 100
|
||||
|
||||
|
||||
###########################################################
|
||||
# MODEL SETTING #
|
||||
###########################################################
|
||||
model_type: ErnieLinear
|
||||
model:
|
||||
pretrained_token: ernie-tiny
|
||||
num_classes: 4
|
||||
|
||||
###########################################################
|
||||
# OPTIMIZER SETTING #
|
||||
###########################################################
|
||||
optimizer_params:
|
||||
weight_decay: 1.0e-6 # weight decay coefficient.
|
||||
|
||||
scheduler_params:
|
||||
learning_rate: 1.0e-5 # learning rate.
|
||||
gamma: 0.9999 # scheduler gamma must between(0.0, 1.0) and closer to 1.0 is better.
|
||||
|
||||
###########################################################
|
||||
# TRAINING SETTING #
|
||||
###########################################################
|
||||
max_epoch: 20
|
||||
num_snapshots: 5
|
||||
|
||||
###########################################################
|
||||
# OTHER SETTING #
|
||||
###########################################################
|
||||
num_snapshots: 10 # max number of snapshots to keep while training
|
||||
seed: 42 # random seed for paddle, random, and np.random
|
||||
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Reference in new issue