File size: 2,045 Bytes
256e3e6 | 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 51 52 53 54 55 56 57 58 59 60 | """Warm RTF benchmark for the Bulgarian ref-audio vLLM setup."""
import asyncio
import os
from audio import LLMAudioPlayer, StreamingAudioWriter
from config import CHUNK_SIZE, LOOKBACK_FRAMES, REF_AUDIO_SECONDS, GPU_MEMORY_UTILIZATION, MAX_MODEL_LEN
from generation.vllm_generator import VLLMTTSGenerator
PROMPTS = [
"Това е кратък тест за real-time factor на ref-audio сървъра.",
"Рано сутрин реката е спокойна, а гласът трябва да звучи ясно, плавно и естествено.",
]
async def run_once(generator, player, prompt, reference_audio_tokens):
audio_writer = StreamingAudioWriter(
player,
output_file=None,
chunk_size=CHUNK_SIZE,
lookback_frames=LOOKBACK_FRAMES,
)
audio_writer.start()
result = await generator._generate_async(
prompt,
audio_writer,
reference_audio_tokens=reference_audio_tokens,
)
audio_writer.finalize()
return result
async def main():
generator = VLLMTTSGenerator(
tensor_parallel_size=1,
gpu_memory_utilization=GPU_MEMORY_UTILIZATION,
max_model_len=MAX_MODEL_LEN,
)
await generator.initialize_engine()
player = LLMAudioPlayer(generator.tokenizer)
reference_audio_path = os.environ.get("KANITTS_TEST_REF_AUDIO", "/home/nasko/besttts/REF/woman.wav")
reference_audio_tokens, reference_frames = player.prepare_reference_audio_tokens(
reference_audio_path=reference_audio_path,
ref_seconds=REF_AUDIO_SECONDS,
)
print(f"Reference frames: {reference_frames}")
for index, prompt in enumerate(PROMPTS, start=1):
result = await run_once(generator, player, prompt, reference_audio_tokens)
print(
f"RUN {index}: tokens={len(result['all_token_ids'])} "
f"dur={result['audio_duration']:.2f}s gen={result['generation_time']:.2f}s "
f"RTF={result['rtf']:.3f}"
)
if __name__ == "__main__":
asyncio.run(main()) |