From 7b0e97163285a8328167e80ee8c907de763cd1cb Mon Sep 17 00:00:00 2001 From: Brandon Thomas Date: Wed, 3 May 2023 20:43:50 -0700 Subject: [PATCH] cleanup dead code, non-relative import --- .../src/so_vits_svc_fork/fakeyou_infer.py | 375 +----------------- .../src/so_vits_svc_fork/fakeyou_infer.py | 371 ----------------- 2 files changed, 2 insertions(+), 744 deletions(-) diff --git a/voice_conversion/so-vits-svc-paul-v2/src/so_vits_svc_fork/fakeyou_infer.py b/voice_conversion/so-vits-svc-paul-v2/src/so_vits_svc_fork/fakeyou_infer.py index 63abe55..fa73343 100644 --- a/voice_conversion/so-vits-svc-paul-v2/src/so_vits_svc_fork/fakeyou_infer.py +++ b/voice_conversion/so-vits-svc-paul-v2/src/so_vits_svc_fork/fakeyou_infer.py @@ -119,29 +119,6 @@ def cli(): init_logger() -#@cli.command() -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(exists=True), -# help="path to config", -# default=Path("./configs/44k/config.json"), -#) -#@click.option( -# "-m", -# "--model-path", -# type=click.Path(), -# help="path to output dir", -# default=Path("./logs/44k"), -#) -#def train(config_path: Path, model_path: Path): -# """Train model -# If D_0.pth or G_0.pth not found, automatically download from hub.""" -# from .train import train -# -# config_path = Path(config_path) -# model_path = Path(model_path) -# train(config_path=config_path, model_path=model_path) @cli.command() @@ -218,8 +195,8 @@ def infer( device: Literal["cpu", "cuda"] = "cuda" if torch.cuda.is_available() else "cpu", ): """Inference""" - from .inference_main import infer - #from inference_main import infer + #from .inference_main import infer + from inference_main import infer if not auto_predict_f0: LOG.warning( @@ -260,353 +237,5 @@ def infer( ) -#@cli.command() -#@click.option( -# "-m", -# "--model-path", -# type=click.Path(exists=True), -# default=Path("./logs/44k/"), -# help="path to model", -#) -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(exists=True), -# default=Path("./configs/44k/config.json"), -# help="path to config", -#) -#@click.option( -# "-k", -# "--cluster-model-path", -# type=click.Path(exists=True), -# default=None, -# help="path to cluster model", -#) -#@click.option("-t", "--transpose", type=int, default=12, help="transpose") -#@click.option( -# "-a", -# "--auto-predict-f0", -# type=bool, -# default=False, -# help="auto predict f0 (not recommended for realtime since voice pitch will not be stable)", -#) -#@click.option( -# "-r", "--cluster-infer-ratio", type=float, default=0, help="cluster infer ratio" -#) -#@click.option("-n", "--noise-scale", type=float, default=0.4, help="noise scale") -#@click.option( -# "-db", "--db-thresh", type=int, default=-30, help="threshold (DB) (ABSOLUTE)" -#) -#@click.option( -# "-fm", -# "--f0-method", -# type=click.Choice(["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"]), -# default="crepe", -# help="f0 prediction method", -#) -#@click.option("-p", "--pad-seconds", type=float, default=0.02, help="pad seconds") -#@click.option("-ch", "--chunk-seconds", type=float, default=0.5, help="chunk seconds") -#@click.option( -# "-cr", -# "--crossfade-seconds", -# type=float, -# default=0.01, -# help="crossfade seconds", -#) -#@click.option( -# "-ab", -# "--additional-infer-before-seconds", -# type=float, -# default=0.2, -# help="additional infer before seconds", -#) -#@click.option( -# "-aa", -# "--additional-infer-after-seconds", -# type=float, -# default=0.1, -# help="additional infer after seconds", -#) -#@click.option("-b", "--block-seconds", type=float, default=0.5, help="block seconds") -#@click.option( -# "-d", -# "--device", -# type=str, -# default="cuda" if torch.cuda.is_available() else "cpu", -# help="device", -#) -#@click.option("-s", "--speaker", type=str, default=None, help="speaker name") -#@click.option("-v", "--version", type=int, default=2, help="version") -#@click.option("-i", "--input-device", type=int, default=None, help="input device") -#@click.option("-o", "--output-device", type=int, default=None, help="output device") -#@click.option( -# "-po", -# "--passthrough-original", -# type=bool, -# default=False, -# is_flag=True, -# help="passthrough original (for latency check)", -#) -#def vc( -# # paths -# model_path: Path, -# config_path: Path, -# # svc config -# speaker: str, -# cluster_model_path: Path | None, -# transpose: int, -# auto_predict_f0: bool, -# cluster_infer_ratio: float, -# noise_scale: float, -# f0_method: Literal["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"], -# # slice config -# db_thresh: int, -# pad_seconds: float, -# chunk_seconds: float, -# # realtime config -# crossfade_seconds: float, -# additional_infer_before_seconds: float, -# additional_infer_after_seconds: float, -# block_seconds: float, -# version: int, -# input_device: int | str | None, -# output_device: int | str | None, -# device: Literal["cpu", "cuda"], -# passthrough_original: bool = False, -#) -> None: -# """Realtime inference from microphone""" -# from .inference_main import realtime -# -# if auto_predict_f0: -# LOG.warning( -# "auto_predict_f0 = True in realtime inference will cause unstable voice pitch, use with caution" -# ) -# else: -# LOG.warning( -# f"auto_predict_f0 = False, transpose = {transpose}. If you want to change the pitch, please change the transpose value." -# "Generally transpose = 0 does not work because your voice pitch and target voice pitch are different." -# ) -# model_path = Path(model_path) -# config_path = Path(config_path) -# if cluster_model_path is not None: -# cluster_model_path = Path(cluster_model_path) -# if model_path.is_dir(): -# model_path = list(sorted(model_path.glob("*.pth")))[-1] -# LOG.info(f"Since model_path is a directory, use {model_path}") -# -# realtime( -# # paths -# model_path=model_path, -# config_path=config_path, -# # svc config -# speaker=speaker, -# cluster_model_path=cluster_model_path, -# transpose=transpose, -# auto_predict_f0=auto_predict_f0, -# cluster_infer_ratio=cluster_infer_ratio, -# noise_scale=noise_scale, -# f0_method=f0_method, -# # slice config -# db_thresh=db_thresh, -# pad_seconds=pad_seconds, -# chunk_seconds=chunk_seconds, -# # realtime config -# crossfade_seconds=crossfade_seconds, -# additional_infer_before_seconds=additional_infer_before_seconds, -# additional_infer_after_seconds=additional_infer_after_seconds, -# block_seconds=block_seconds, -# version=version, -# input_device=input_device, -# output_device=output_device, -# device=device, -# passthrough_original=passthrough_original, -# ) - - -#@cli.command() -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# default=Path("./dataset_raw"), -# help="path to source dir", -#) -#@click.option( -# "-o", -# "--output-dir", -# type=click.Path(), -# default=Path("./dataset/44k"), -# help="path to output dir", -#) -#@click.option("-s", "--sampling-rate", type=int, default=44100, help="sampling rate") -#def pre_resample(input_dir: Path, output_dir: Path, sampling_rate: int) -> None: -# """Preprocessing part 1: resample""" -# from .preprocess_resample import preprocess_resample -# -# input_dir = Path(input_dir) -# output_dir = Path(output_dir) -# preprocess_resample( -# input_dir=input_dir, output_dir=output_dir, sampling_rate=sampling_rate -# ) - - -#@cli.command() -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# default=Path("./dataset/44k"), -# help="path to source dir", -#) -#@click.option( -# "-f", -# "--filelist-path", -# type=click.Path(), -# default=Path("./filelists/44k"), -# help="path to filelist dir", -#) -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(), -# default=Path("./configs/44k/config.json"), -# help="path to config", -#) -#def pre_config( -# input_dir: Path, -# filelist_path: Path, -# config_path: Path, -#): -# """Preprocessing part 2: config""" -# from .preprocess_flist_config import preprocess_config -# -# input_dir = Path(input_dir) -# filelist_path = Path(filelist_path) -# config_path = Path(config_path) -# preprocess_config( -# input_dir=input_dir, -# train_list_path=filelist_path / "train.txt", -# val_list_path=filelist_path / "val.txt", -# test_list_path=filelist_path / "test.txt", -# config_path=config_path, -# ) - - -#@cli.command() -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# default=Path("./dataset/44k"), -# help="path to source dir", -#) -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(exists=True), -# help="path to config", -# default=Path("./configs/44k/config.json"), -#) -#@click.option( -# "-n", -# "--n_jobs", -# type=int, -# default=4, -# help="number of jobs (optimal value may depend on your VRAM capacity and audio duration per file)", -#) -#@click.option( -# "-f", -# "--force-rebuild", -# type=bool, -# default=True, -# help="force rebuild existing preprocessed files", -#) -#@click.option( -# "-fm", -# "--f0-method", -# type=click.Choice(["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"]), -# default="dio", -#) -#def pre_hubert( -# input_dir: Path, -# config_path: Path, -# n_jobs: bool, -# force_rebuild: bool, -# f0_method: Literal["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"], -#) -> None: -# """Preprocessing part 3: hubert -# If the HuBERT model is not found, it will be downloaded automatically.""" -# from .preprocess_hubert_f0 import preprocess_hubert_f0 -# -# input_dir = Path(input_dir) -# config_path = Path(config_path) -# preprocess_hubert_f0( -# input_dir=input_dir, -# config_path=config_path, -# n_jobs=n_jobs, -# force_rebuild=force_rebuild, -# f0_method=f0_method, -# ) - - -#@cli.command -#def clean(): -# """Clean up files, only useful if you are using the default file structure""" -# import shutil -# -# folders = ["dataset", "filelists", "logs"] -# if pyip.inputYesNo(f"Are you sure you want to delete files in {folders}?") == "yes": -# for folder in folders: -# if Path(folder).exists(): -# shutil.rmtree(folder) -# LOG.info("Cleaned up files") -# else: -# LOG.info("Aborted") - - -#@cli.command -#@click.option("-i", "--input-path", type=click.Path(exists=True), help="model path") -#@click.option("-o", "--output-path", type=click.Path(), help="onnx model path to save") -#@click.option("-c", "--config-path", type=click.Path(), help="config path") -#@click.option("-d", "--device", type=str, default="cpu", help="torch device") -#def onnx(input_path: Path, output_path: Path, config_path: Path, device: str) -> None: -# """Export model to onnx""" -# input_path = Path(input_path) -# output_path = Path(output_path) -# config_path = Path(config_path) -# device_ = torch.device(device) -# from .onnx_export import onnx_export -# -# onnx_export( -# input_path=input_path, -# output_path=output_path, -# config_path=config_path, -# device=device_, -# ) - - -#@cli.command -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# help="dataset directory", -# default=Path("./dataset/44k"), -#) -#@click.option( -# "-o", -# "--output-path", -# type=click.Path(), -# help="model path to save", -# default=Path("./models/44k/kmeans.pt"), -#) -#@click.option("-n", "--n-clusters", type=int, help="number of clusters", default=10000) -#def train_cluster(input_dir: Path, output_path: Path, n_clusters: int) -> None: -# """Train k-means clustering""" -# from .cluster.train_cluster import main -# -# main(input_dir=input_dir, output_path=output_path, n_clusters=n_clusters) - - if __name__ == '__main__': infer() diff --git a/voice_conversion/so-vits-svc-paul/src/so_vits_svc_fork/fakeyou_infer.py b/voice_conversion/so-vits-svc-paul/src/so_vits_svc_fork/fakeyou_infer.py index 63abe55..b3602e0 100644 --- a/voice_conversion/so-vits-svc-paul/src/so_vits_svc_fork/fakeyou_infer.py +++ b/voice_conversion/so-vits-svc-paul/src/so_vits_svc_fork/fakeyou_infer.py @@ -119,30 +119,6 @@ def cli(): init_logger() -#@cli.command() -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(exists=True), -# help="path to config", -# default=Path("./configs/44k/config.json"), -#) -#@click.option( -# "-m", -# "--model-path", -# type=click.Path(), -# help="path to output dir", -# default=Path("./logs/44k"), -#) -#def train(config_path: Path, model_path: Path): -# """Train model -# If D_0.pth or G_0.pth not found, automatically download from hub.""" -# from .train import train -# -# config_path = Path(config_path) -# model_path = Path(model_path) -# train(config_path=config_path, model_path=model_path) - @cli.command() @click.argument( @@ -260,353 +236,6 @@ def infer( ) -#@cli.command() -#@click.option( -# "-m", -# "--model-path", -# type=click.Path(exists=True), -# default=Path("./logs/44k/"), -# help="path to model", -#) -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(exists=True), -# default=Path("./configs/44k/config.json"), -# help="path to config", -#) -#@click.option( -# "-k", -# "--cluster-model-path", -# type=click.Path(exists=True), -# default=None, -# help="path to cluster model", -#) -#@click.option("-t", "--transpose", type=int, default=12, help="transpose") -#@click.option( -# "-a", -# "--auto-predict-f0", -# type=bool, -# default=False, -# help="auto predict f0 (not recommended for realtime since voice pitch will not be stable)", -#) -#@click.option( -# "-r", "--cluster-infer-ratio", type=float, default=0, help="cluster infer ratio" -#) -#@click.option("-n", "--noise-scale", type=float, default=0.4, help="noise scale") -#@click.option( -# "-db", "--db-thresh", type=int, default=-30, help="threshold (DB) (ABSOLUTE)" -#) -#@click.option( -# "-fm", -# "--f0-method", -# type=click.Choice(["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"]), -# default="crepe", -# help="f0 prediction method", -#) -#@click.option("-p", "--pad-seconds", type=float, default=0.02, help="pad seconds") -#@click.option("-ch", "--chunk-seconds", type=float, default=0.5, help="chunk seconds") -#@click.option( -# "-cr", -# "--crossfade-seconds", -# type=float, -# default=0.01, -# help="crossfade seconds", -#) -#@click.option( -# "-ab", -# "--additional-infer-before-seconds", -# type=float, -# default=0.2, -# help="additional infer before seconds", -#) -#@click.option( -# "-aa", -# "--additional-infer-after-seconds", -# type=float, -# default=0.1, -# help="additional infer after seconds", -#) -#@click.option("-b", "--block-seconds", type=float, default=0.5, help="block seconds") -#@click.option( -# "-d", -# "--device", -# type=str, -# default="cuda" if torch.cuda.is_available() else "cpu", -# help="device", -#) -#@click.option("-s", "--speaker", type=str, default=None, help="speaker name") -#@click.option("-v", "--version", type=int, default=2, help="version") -#@click.option("-i", "--input-device", type=int, default=None, help="input device") -#@click.option("-o", "--output-device", type=int, default=None, help="output device") -#@click.option( -# "-po", -# "--passthrough-original", -# type=bool, -# default=False, -# is_flag=True, -# help="passthrough original (for latency check)", -#) -#def vc( -# # paths -# model_path: Path, -# config_path: Path, -# # svc config -# speaker: str, -# cluster_model_path: Path | None, -# transpose: int, -# auto_predict_f0: bool, -# cluster_infer_ratio: float, -# noise_scale: float, -# f0_method: Literal["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"], -# # slice config -# db_thresh: int, -# pad_seconds: float, -# chunk_seconds: float, -# # realtime config -# crossfade_seconds: float, -# additional_infer_before_seconds: float, -# additional_infer_after_seconds: float, -# block_seconds: float, -# version: int, -# input_device: int | str | None, -# output_device: int | str | None, -# device: Literal["cpu", "cuda"], -# passthrough_original: bool = False, -#) -> None: -# """Realtime inference from microphone""" -# from .inference_main import realtime -# -# if auto_predict_f0: -# LOG.warning( -# "auto_predict_f0 = True in realtime inference will cause unstable voice pitch, use with caution" -# ) -# else: -# LOG.warning( -# f"auto_predict_f0 = False, transpose = {transpose}. If you want to change the pitch, please change the transpose value." -# "Generally transpose = 0 does not work because your voice pitch and target voice pitch are different." -# ) -# model_path = Path(model_path) -# config_path = Path(config_path) -# if cluster_model_path is not None: -# cluster_model_path = Path(cluster_model_path) -# if model_path.is_dir(): -# model_path = list(sorted(model_path.glob("*.pth")))[-1] -# LOG.info(f"Since model_path is a directory, use {model_path}") -# -# realtime( -# # paths -# model_path=model_path, -# config_path=config_path, -# # svc config -# speaker=speaker, -# cluster_model_path=cluster_model_path, -# transpose=transpose, -# auto_predict_f0=auto_predict_f0, -# cluster_infer_ratio=cluster_infer_ratio, -# noise_scale=noise_scale, -# f0_method=f0_method, -# # slice config -# db_thresh=db_thresh, -# pad_seconds=pad_seconds, -# chunk_seconds=chunk_seconds, -# # realtime config -# crossfade_seconds=crossfade_seconds, -# additional_infer_before_seconds=additional_infer_before_seconds, -# additional_infer_after_seconds=additional_infer_after_seconds, -# block_seconds=block_seconds, -# version=version, -# input_device=input_device, -# output_device=output_device, -# device=device, -# passthrough_original=passthrough_original, -# ) - - -#@cli.command() -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# default=Path("./dataset_raw"), -# help="path to source dir", -#) -#@click.option( -# "-o", -# "--output-dir", -# type=click.Path(), -# default=Path("./dataset/44k"), -# help="path to output dir", -#) -#@click.option("-s", "--sampling-rate", type=int, default=44100, help="sampling rate") -#def pre_resample(input_dir: Path, output_dir: Path, sampling_rate: int) -> None: -# """Preprocessing part 1: resample""" -# from .preprocess_resample import preprocess_resample -# -# input_dir = Path(input_dir) -# output_dir = Path(output_dir) -# preprocess_resample( -# input_dir=input_dir, output_dir=output_dir, sampling_rate=sampling_rate -# ) - - -#@cli.command() -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# default=Path("./dataset/44k"), -# help="path to source dir", -#) -#@click.option( -# "-f", -# "--filelist-path", -# type=click.Path(), -# default=Path("./filelists/44k"), -# help="path to filelist dir", -#) -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(), -# default=Path("./configs/44k/config.json"), -# help="path to config", -#) -#def pre_config( -# input_dir: Path, -# filelist_path: Path, -# config_path: Path, -#): -# """Preprocessing part 2: config""" -# from .preprocess_flist_config import preprocess_config -# -# input_dir = Path(input_dir) -# filelist_path = Path(filelist_path) -# config_path = Path(config_path) -# preprocess_config( -# input_dir=input_dir, -# train_list_path=filelist_path / "train.txt", -# val_list_path=filelist_path / "val.txt", -# test_list_path=filelist_path / "test.txt", -# config_path=config_path, -# ) - - -#@cli.command() -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# default=Path("./dataset/44k"), -# help="path to source dir", -#) -#@click.option( -# "-c", -# "--config-path", -# type=click.Path(exists=True), -# help="path to config", -# default=Path("./configs/44k/config.json"), -#) -#@click.option( -# "-n", -# "--n_jobs", -# type=int, -# default=4, -# help="number of jobs (optimal value may depend on your VRAM capacity and audio duration per file)", -#) -#@click.option( -# "-f", -# "--force-rebuild", -# type=bool, -# default=True, -# help="force rebuild existing preprocessed files", -#) -#@click.option( -# "-fm", -# "--f0-method", -# type=click.Choice(["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"]), -# default="dio", -#) -#def pre_hubert( -# input_dir: Path, -# config_path: Path, -# n_jobs: bool, -# force_rebuild: bool, -# f0_method: Literal["crepe", "crepe-tiny", "parselmouth", "dio", "harvest"], -#) -> None: -# """Preprocessing part 3: hubert -# If the HuBERT model is not found, it will be downloaded automatically.""" -# from .preprocess_hubert_f0 import preprocess_hubert_f0 -# -# input_dir = Path(input_dir) -# config_path = Path(config_path) -# preprocess_hubert_f0( -# input_dir=input_dir, -# config_path=config_path, -# n_jobs=n_jobs, -# force_rebuild=force_rebuild, -# f0_method=f0_method, -# ) - - -#@cli.command -#def clean(): -# """Clean up files, only useful if you are using the default file structure""" -# import shutil -# -# folders = ["dataset", "filelists", "logs"] -# if pyip.inputYesNo(f"Are you sure you want to delete files in {folders}?") == "yes": -# for folder in folders: -# if Path(folder).exists(): -# shutil.rmtree(folder) -# LOG.info("Cleaned up files") -# else: -# LOG.info("Aborted") - - -#@cli.command -#@click.option("-i", "--input-path", type=click.Path(exists=True), help="model path") -#@click.option("-o", "--output-path", type=click.Path(), help="onnx model path to save") -#@click.option("-c", "--config-path", type=click.Path(), help="config path") -#@click.option("-d", "--device", type=str, default="cpu", help="torch device") -#def onnx(input_path: Path, output_path: Path, config_path: Path, device: str) -> None: -# """Export model to onnx""" -# input_path = Path(input_path) -# output_path = Path(output_path) -# config_path = Path(config_path) -# device_ = torch.device(device) -# from .onnx_export import onnx_export -# -# onnx_export( -# input_path=input_path, -# output_path=output_path, -# config_path=config_path, -# device=device_, -# ) - - -#@cli.command -#@click.option( -# "-i", -# "--input-dir", -# type=click.Path(exists=True), -# help="dataset directory", -# default=Path("./dataset/44k"), -#) -#@click.option( -# "-o", -# "--output-path", -# type=click.Path(), -# help="model path to save", -# default=Path("./models/44k/kmeans.pt"), -#) -#@click.option("-n", "--n-clusters", type=int, help="number of clusters", default=10000) -#def train_cluster(input_dir: Path, output_path: Path, n_clusters: int) -> None: -# """Train k-means clustering""" -# from .cluster.train_cluster import main -# -# main(input_dir=input_dir, output_path=output_path, n_clusters=n_clusters) - if __name__ == '__main__': infer()