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https://github.com/svc-develop-team/so-vits-svc.git
synced 2025-01-07 03:17:31 +08:00
chore: make Ruff happy
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parent
fab65746d6
commit
4ae070bb77
@ -1,4 +1,4 @@
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select = ["E", "F", "I"]
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# Never enforce `E501` (line length violations).
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ignore = ["E501"]
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ignore = ["E501", "E741"]
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@ -1,6 +1,6 @@
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import torch
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import torch.nn as nn
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from torch.nn.utils import weight_norm, remove_weight_norm
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from torch.nn.utils import remove_weight_norm, weight_norm
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class Depthwise_Separable_Conv1D(nn.Module):
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def __init__(
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@ -53,7 +53,9 @@ def spectrogram_torch(y, n_fft, sampling_rate, hop_size, win_size, center=False)
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y = y.squeeze(1)
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y_dtype = y.dtype
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if y.dtype == torch.bfloat16: y = y.to(torch.float32)
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if y.dtype == torch.bfloat16:
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y = y.to(torch.float32)
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spec = torch.stft(y, n_fft, hop_length=hop_size, win_length=win_size, window=hann_window[wnsize_dtype_device],
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center=center, pad_mode='reflect', normalized=False, onesided=True, return_complex=True)
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spec = torch.view_as_real(spec).to(y_dtype)
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@ -1,12 +1,14 @@
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import torch
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from torch import nn
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from torch.nn import Conv1d
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from torch.nn import functional as F
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from modules.DSConv import weight_norm_modules, remove_weight_norm_modules, Depthwise_Separable_Conv1D
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import modules.commons as commons
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from modules.commons import init_weights, get_padding
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from modules.commons import get_padding, init_weights
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from modules.DSConv import (
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Depthwise_Separable_Conv1D,
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remove_weight_norm_modules,
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weight_norm_modules,
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)
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LRELU_SLOPE = 0.1
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12
webUI.py
12
webUI.py
@ -6,6 +6,7 @@ import subprocess
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import time
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import traceback
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from itertools import chain
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from pathlib import Path
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# os.system("wget -P cvec/ https://huggingface.co/spaces/innnky/nanami/resolve/main/checkpoint_best_legacy_500.pt")
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import gradio as gr
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@ -15,7 +16,6 @@ import numpy as np
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import soundfile
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import torch
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from scipy.io import wavfile
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from pathlib import Path
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from compress_model import removeOptimizer
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from inference.infer_tool import Svc
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@ -172,14 +172,18 @@ def vc_fn(sid, input_audio, output_format, vc_transform, auto_f0,cluster_ratio,
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model.clear_empty()
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#os.remove(temp_path)
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#构建保存文件的路径,并保存到results文件夹内
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timestamp = str(int(time.time()))
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str(int(time.time()))
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if not os.path.exists("results"):
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os.makedirs("results")
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key = "auto" if auto_f0 else f"{int(vc_transform)}key"
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cluster = "_" if cluster_ratio == 0 else f"_{cluster_ratio}_"
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isdiffusion = "sovits"
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if model.shallow_diffusion : isdiffusion = "sovdiff"
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if model.only_diffusion : isdiffusion = "diff"
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if model.shallow_diffusion:
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isdiffusion = "sovdiff"
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if model.only_diffusion:
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isdiffusion = "diff"
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output_file_name = 'result_'+truncated_basename+f'_{sid}_{key}{cluster}{isdiffusion}.{output_format}'
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output_file = os.path.join("results", output_file_name)
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soundfile.write(output_file, _audio, model.target_sample, format=output_format)
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