Spaces:
Running
on
L40S
Running
on
L40S
| import torch,torchaudio | |
| import os,sys,json | |
| from tqdm import tqdm | |
| #from codeclm_song_v1.codeclm.semantic_extractor.SpeechDecoder_v01.generate import Tango | |
| from generate_2rvq import Tango | |
| import kaldiio | |
| from kaldiio import WriteHelper | |
| import torch | |
| import subprocess | |
| import time | |
| import sys | |
| def get_gpu_memory(): | |
| _output_to_list = lambda x: x.decode('ascii').split('\n')[:-1] | |
| ACCEPTABLE_AVAILABLE_MEMORY = 1024 | |
| COMMAND = "nvidia-smi --query-gpu=memory.free --format=csv" | |
| memory_free_info = _output_to_list(subprocess.check_output(COMMAND.split()))[1:] | |
| memory_free_values = [int(x.split()[0]) for i, x in enumerate(memory_free_info)] | |
| return memory_free_values | |
| if __name__ == "__main__": | |
| # Define Model | |
| json_path = sys.argv[1] | |
| outdir = sys.argv[2] | |
| gpu_idx = int(os.environ['CUDA_VISIBLE_DEVICES']) | |
| while True: | |
| free_mem = get_gpu_memory() | |
| free_mem = free_mem[gpu_idx] | |
| if(free_mem > 25_000): | |
| print("GPU memory {}, run matrix cal".format(free_mem)) | |
| break | |
| else: | |
| print("GPU memory {}, sleep 1min".format(free_mem)) | |
| time.sleep(60) | |
| mus_infos = [] | |
| with open(json_path) as f: | |
| for line in f: | |
| item = json.loads(line) | |
| mus_infos.append(item) | |
| tango = Tango(model_path = './saved/model_2rvq/model_2_fixed.safetensors', rvq_num=2) | |
| # Feature extraction loop | |
| # for i in tqdm(range(2000)): | |
| with WriteHelper('ark,scp:{}/token.ark,{}/token.scp'.format(outdir, outdir), write_function="pickle") as writer: | |
| print('ark,scp:{}/token.ark,{}/token.scp'.format(outdir, outdir)) | |
| for item in tqdm(mus_infos): | |
| try: | |
| # if True: | |
| idx = item['idx'] | |
| # print(idx) | |
| with torch.autocast(device_type="cuda", dtype=torch.float16): | |
| if(os.path.exists(item['path'])): | |
| codes = tango.file2code(item['path']) | |
| else: | |
| codes = tango.file2code('/mnt/share/' + item['path']) | |
| writer(str(idx), codes.cpu()) | |
| except: | |
| print(item['path']) | |
| continue | |
| # idx = item['idx'] | |
| # # print(idx) | |
| # with torch.autocast(device_type="cuda", dtype=torch.float16): | |
| # codes = tango.file2code(item['path']) | |
| # writer(str(idx), codes.cpu()) |