From 3364d77d1ca47d66ebf92df97de08d72e3ae8fed Mon Sep 17 00:00:00 2001 From: Justin John <34035011+justinjohn0306@users.noreply.github.com> Date: Mon, 19 Jun 2023 19:47:08 -0700 Subject: [PATCH] Delete infer_batch_rvc.py --- voice_conversion/infer_batch_rvc.py | 217 ---------------------------- 1 file changed, 217 deletions(-) delete mode 100644 voice_conversion/infer_batch_rvc.py diff --git a/voice_conversion/infer_batch_rvc.py b/voice_conversion/infer_batch_rvc.py deleted file mode 100644 index 311fe91..0000000 --- a/voice_conversion/infer_batch_rvc.py +++ /dev/null @@ -1,217 +0,0 @@ -""" -v1 -runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\logs\mi-test\added_IVF677_Flat_nprobe_7.index" harvest "E:\codes\py39\RVC-beta\output" "E:\codes\py39\test-20230416b\weights\mi-test.pth" 0.66 cuda:0 True 3 0 1 0.33 -v2 -runtime\python.exe myinfer-v2-0528.py 0 "E:\codes\py39\RVC-beta\todo-songs" "E:\codes\py39\test-20230416b\logs\mi-test-v2\aadded_IVF677_Flat_nprobe_1_v2.index" harvest "E:\codes\py39\RVC-beta\output_v2" "E:\codes\py39\test-20230416b\weights\mi-test-v2.pth" 0.66 cuda:0 True 3 0 1 0.33 -""" -import os, sys, pdb, torch - -now_dir = os.getcwd() -sys.path.append(now_dir) -import argparse -import glob -import sys -import torch -import tqdm as tq -from multiprocessing import cpu_count - - -class Config: - def __init__(self, device, is_half): - self.device = device - self.is_half = is_half - self.n_cpu = 0 - self.gpu_name = None - self.gpu_mem = None - self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() - - def device_config(self) -> tuple: - if torch.cuda.is_available(): - i_device = int(self.device.split(":")[-1]) - self.gpu_name = torch.cuda.get_device_name(i_device) - if ( - ("16" in self.gpu_name and "V100" not in self.gpu_name.upper()) - or "P40" in self.gpu_name.upper() - or "1060" in self.gpu_name - or "1070" in self.gpu_name - or "1080" in self.gpu_name - ): - print("16系/10系显卡和P40强制单精度") - self.is_half = False - for config_file in ["32k.json", "40k.json", "48k.json"]: - with open(f"configs/{config_file}", "r") as f: - strr = f.read().replace("true", "false") - with open(f"configs/{config_file}", "w") as f: - f.write(strr) - with open("trainset_preprocess_pipeline_print.py", "r") as f: - strr = f.read().replace("3.7", "3.0") - with open("trainset_preprocess_pipeline_print.py", "w") as f: - f.write(strr) - else: - self.gpu_name = None - self.gpu_mem = int( - torch.cuda.get_device_properties(i_device).total_memory - / 1024 - / 1024 - / 1024 - + 0.4 - ) - if self.gpu_mem <= 4: - with open("trainset_preprocess_pipeline_print.py", "r") as f: - strr = f.read().replace("3.7", "3.0") - with open("trainset_preprocess_pipeline_print.py", "w") as f: - f.write(strr) - elif torch.backends.mps.is_available(): - print("没有发现支持的N卡, 使用MPS进行推理") - self.device = "mps" - else: - print("没有发现支持的N卡, 使用CPU进行推理") - self.device = "cpu" - self.is_half = True - - if self.n_cpu == 0: - self.n_cpu = cpu_count() - - if self.is_half: - # 6G显存配置 - x_pad = 3 - x_query = 10 - x_center = 60 - x_max = 65 - else: - # 5G显存配置 - x_pad = 1 - x_query = 6 - x_center = 38 - x_max = 41 - - if self.gpu_mem != None and self.gpu_mem <= 4: - x_pad = 1 - x_query = 5 - x_center = 30 - x_max = 32 - - return x_pad, x_query, x_center, x_max - - -f0up_key = sys.argv[1] -input_path = sys.argv[2] -index_path = sys.argv[3] -f0method = sys.argv[4] # harvest or pm -opt_path = sys.argv[5] -model_path = sys.argv[6] -index_rate = float(sys.argv[7]) -device = sys.argv[8] -is_half = bool(sys.argv[9]) -filter_radius = int(sys.argv[10]) -resample_sr = int(sys.argv[11]) -rms_mix_rate = float(sys.argv[12]) -protect = float(sys.argv[13]) -print(sys.argv) -config = Config(device, is_half) -now_dir = os.getcwd() -sys.path.append(now_dir) -from vc_infer_pipeline import VC -from infer_pack.models import ( - SynthesizerTrnMs256NSFsid, - SynthesizerTrnMs256NSFsid_nono, - SynthesizerTrnMs768NSFsid, - SynthesizerTrnMs768NSFsid_nono, -) -from my_utils import load_audio -from fairseq import checkpoint_utils -from scipy.io import wavfile - -hubert_model = None - - -def load_hubert(): - global hubert_model - models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task( - ["hubert_base.pt"], - suffix="", - ) - hubert_model = models[0] - hubert_model = hubert_model.to(device) - if is_half: - hubert_model = hubert_model.half() - else: - hubert_model = hubert_model.float() - hubert_model.eval() - - -def vc_single(sid, input_audio, f0_up_key, f0_file, f0_method, file_index, index_rate): - global tgt_sr, net_g, vc, hubert_model, version - if input_audio is None: - return "You need to upload an audio", None - f0_up_key = int(f0_up_key) - audio = load_audio(input_audio, 16000) - times = [0, 0, 0] - if hubert_model == None: - load_hubert() - if_f0 = cpt.get("f0", 1) - # audio_opt=vc.pipeline(hubert_model,net_g,sid,audio,times,f0_up_key,f0_method,file_index,file_big_npy,index_rate,if_f0,f0_file=f0_file) - audio_opt = vc.pipeline( - hubert_model, - net_g, - sid, - audio, - input_audio, - times, - f0_up_key, - f0_method, - file_index, - index_rate, - if_f0, - filter_radius, - tgt_sr, - resample_sr, - rms_mix_rate, - version, - protect, - f0_file=f0_file, - ) - print(times) - return audio_opt - - -def get_vc(model_path): - global n_spk, tgt_sr, net_g, vc, cpt, device, is_half, version - print("loading pth %s" % model_path) - cpt = torch.load(model_path, map_location="cpu") - tgt_sr = cpt["config"][-1] - cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] # n_spk - if_f0 = cpt.get("f0", 1) - version = cpt.get("version", "v1") - if version == "v1": - if if_f0 == 1: - net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=is_half) - else: - net_g = SynthesizerTrnMs256NSFsid_nono(*cpt["config"]) - elif version == "v2": - if if_f0 == 1: # - net_g = SynthesizerTrnMs768NSFsid(*cpt["config"], is_half=is_half) - else: - net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"]) - del net_g.enc_q - print(net_g.load_state_dict(cpt["weight"], strict=False)) # 不加这一行清不干净，真奇葩 - net_g.eval().to(device) - if is_half: - net_g = net_g.half() - else: - net_g = net_g.float() - vc = VC(tgt_sr, config) - n_spk = cpt["config"][-3] - # return {"visible": True,"maximum": n_spk, "__type__": "update"} - - -get_vc(model_path) -audios = os.listdir(input_path) -for file in tq.tqdm(audios): - if file.endswith(".wav"): - file_path = input_path + "/" + file - wav_opt = vc_single( - 0, file_path, f0up_key, None, f0method, index_path, index_rate - ) - out_path = opt_path + "/" + file - wavfile.write(out_path, tgt_sr, wav_opt)