weedge

from melo.api import TTS
import os
import torch
from openvoice import se_extractor
from openvoice.api import ToneColorConverter

ckpt_converter = 'checkpoints_v2/converter'
device = "cuda:0" if torch.cuda.is_available() else "cpu"
output_dir = 'outputs_v2'
print(device)

weedge

import os
import torch
from openvoice import se_extractor
from openvoice.api import ToneColorConverter

ckpt_converter = 'checkpoints_v2/converter'
device = "cuda:0" if torch.cuda.is_available() else "cpu"
output_dir = 'outputs_v2'
print(device)

weedge

"""
Author: Awni Hannun

This is an example CTC decoder written in Python. The code is
intended to be a simple example and is not designed to be
especially efficient.

The algorithm is a prefix beam search for a model trained
with the CTC loss function.