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14ff14a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | import os
from src.rwkv7 import RWKV7
from src.text_tokenizer import TextTokenizer
import torch
# os.environ["CUDA_VISIBLE_DEVICES"] = "3"
device = torch.device("cuda:2")
# model = RWKV7(text_vocab=128, audio_vocab=8192 + 1, dim=512, n_blocks=12).to(device)
model = RWKV7(text_vocab=128, audio_vocab=8192 + 1, dim=1024, n_blocks=12).to(device)
tokenizer = TextTokenizer()
config = "lucadellalib/focalcodec_12_5hz"
codec = torch.hub.load(
"lucadellalib/focalcodec", "focalcodec", config=config, force_reload=False
)
codec.eval().requires_grad_(False).to(device)
checkpoint_dir = './checkpoints'
checkpoint_files = [f for f in os.listdir(checkpoint_dir) if f.endswith('.pt')]
if not checkpoint_files:
print("No checkpoint files found in the directory.")
exit(0)
latest_checkpoint = max(checkpoint_files, key=lambda x: os.path.getctime(os.path.join(checkpoint_dir, x)))
checkpoint_path = os.path.join(checkpoint_dir, latest_checkpoint)
model.load_state_dict(torch.load(checkpoint_path))
print(f"Loaded checkpoint: {checkpoint_path}")
MAX_LENGTH = 2000
print("Start")
while(True):
text = str(input())
print("Computing...")
tokens = tokenizer.tokenize(text)
text_tensor = torch.tensor(tokens).unsqueeze(0).to(device) # 1, seq,
print(f"text_tensor:{text_tensor}")
tokens = model.generate(None, text_tensor, 2000, device) #return a tensor
# print(tokens.shape)
print(tokens)
signal = codec.toks_to_sig(tokens).squeeze(0)
import scipy.io.wavfile as wavfile
signal_list = signal.cpu().numpy()
wavfile.write(f'test.wav', codec.sample_rate, signal_list)
print("Finish")
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