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title = "DIFF-SVC"
description = """
<p>
<body style="background-color: #18181a; color: white;"></body>
<center>
<h1>DIFF-SVC Inference Cloud</h1>
This is a Cloud Inference where you can render your models with your wav files
<p>Enter a link:</p>
<input type="text" id="link-input"/>
<p>Upload a WAV file:</p> <input type="file" id="wav-input" accept=".wav"/>
<button id="render-button">Render</button>
<p>Diff-SVC prediction:</p>
<p id="prediction-output"></p>
</center>
</p>
"""
from utils.hparams import hparams
from preprocessing.data_gen_utils import get_pitch_parselmouth,get_pitch_crepe
import numpy as np
import matplotlib.pyplot as plt
import IPython.display as ipd
import utils
import librosa
import torchcrepe
from infer import *
import logging
from infer_tools.infer_tool import *
##EDIT FOR CPU
# Open the file and read it into a string
with open("/home/user/.local/lib/python3.8/site-packages/torch/serialization.py") as f:
text = f.read()
# Replace the original line with the new line
text = text.replace("def load(f, map_location=None, pickle_module=pickle, **pickle_load_args):", "def load(f, map_location='cpu', pickle_module=pickle, **pickle_load_args):")
# Save the modified string to the original file
with open("/home/user/.local/lib/python3.8/site-packages/torch/serialization.py", "w") as f:
f.write(text)
print("Replaced")
with open("/home/user/.local/lib/python3.8/site-packages/torch/serialization.py") as f:
text = f.read()
print(text)
############
logging.getLogger('numba').setLevel(logging.WARNING)
# 工程文件夹名，训练时用的那个
project_name = "Unnamed"
model_path = f'./checkpoints/Unnamed/model_ckpt_steps_192000.ckpt'
config_path=f'./checkpoints/Unnamed/config.yaml'
hubert_gpu=False
svc_model = Svc(project_name,config_path,hubert_gpu, model_path)
print('model loaded')
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