TheStinger commited on
Commit
aa7549b
1 Parent(s): 5f5ae6a

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +14 -17
app.py CHANGED
@@ -4,7 +4,6 @@ os.environ["no_proxy"] = "localhost, 127.0.0.1, ::1"
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  import threading
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  from time import sleep
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  from subprocess import Popen
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- from typing import Any
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  import faiss
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  import spaces
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  from random import shuffle
@@ -195,7 +194,6 @@ else:
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  or "M4" in gpu_name.upper()
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  or "T4" in gpu_name.upper()
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  or "TITAN" in gpu_name.upper()
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- or "ZERO" in gpu_name.upper()
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  ): # A10#A100#V100#A40#P40#M40#K80#A4500
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  if_gpu_ok = True # 至少有一张能用的N卡
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  gpu_infos.append("%s\t%s" % (i, gpu_name))
@@ -222,31 +220,30 @@ from lib.infer_pack.models import (
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  SynthesizerTrnMs768NSFsid_nono,
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  )
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  import soundfile as sf
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- from fairseq import checkpoint_utils
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  import gradio as gr
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  import logging
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  from vc_infer_pipeline import VC
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  from config import Config
 
 
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  config = Config()
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  # from trainset_preprocess_pipeline import PreProcess
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  logging.getLogger("numba").setLevel(logging.WARNING)
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- hubert_model = None
 
 
 
 
 
 
 
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  def load_hubert():
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- global hubert_model
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- models, _, _ = checkpoint_utils.load_model_ensemble_and_task(
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- ["hubert_base.pt"],
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- suffix="",
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- )
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- hubert_model = models[0]
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- hubert_model = hubert_model.to(config.device)
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- if config.is_half:
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- hubert_model = hubert_model.half()
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- else:
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- hubert_model = hubert_model.float()
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- hubert_model.eval()
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  weight_root = "weights"
@@ -262,7 +259,7 @@ for root, dirs, files in os.walk(index_root, topdown=False):
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  index_paths.append("%s/%s" % (root, name))
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- @spaces.GPU
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  def vc_single(
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  sid,
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  input_audio_path,
 
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  import threading
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  from time import sleep
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  from subprocess import Popen
 
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  import faiss
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  import spaces
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  from random import shuffle
 
194
  or "M4" in gpu_name.upper()
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  or "T4" in gpu_name.upper()
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  or "TITAN" in gpu_name.upper()
 
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  ): # A10#A100#V100#A40#P40#M40#K80#A4500
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  if_gpu_ok = True # 至少有一张能用的N卡
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  gpu_infos.append("%s\t%s" % (i, gpu_name))
 
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  SynthesizerTrnMs768NSFsid_nono,
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  )
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  import soundfile as sf
 
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  import gradio as gr
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  import logging
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  from vc_infer_pipeline import VC
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  from config import Config
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+ import torch.nn as nn
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+ import numpy as np
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  config = Config()
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  # from trainset_preprocess_pipeline import PreProcess
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  logging.getLogger("numba").setLevel(logging.WARNING)
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+
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+ class HuBERT(nn.Module):
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+ def __init__(self, model_path):
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+ super(HuBERT, self).__init__()
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+ self.model = torch.hub.load('pytorch/fairseq', 'hubert_base') # should load without using hubert_base.pt, and without fairseq.
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+
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+ def extract_features(self, waveform):
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+ return self.model.extract_features(waveform)
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  def load_hubert():
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+ model_path = "hubert_base.pt" # Your model path
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+ hubert_model = HuBERT(model_path)
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+ return hubert_model
 
 
 
 
 
 
 
 
 
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  weight_root = "weights"
 
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  index_paths.append("%s/%s" % (root, name))
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+
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  def vc_single(
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  sid,
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  input_audio_path,