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Merge pull request #136 from ace-step/add_lora_support

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add chinese_rap_lora
This commit is contained in:
Gong Junmin
2025-05-13 15:01:17 +08:00
committed by GitHub
parent a064d710df 6ca5bd880e
commit 02f823f406
56 changed files with 1333 additions and 177 deletions
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acestep/pipeline_ace_step.py
+22 -2
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@@ -113,6 +113,7 @@ class ACEStepPipeline:
ensure_directory_exists(checkpoint_dir)
self.checkpoint_dir = checkpoint_dir
self.lora_path = "none"
device = (
torch.device(f"cuda:{device_id}")
if torch.cuda.is_available()
@@ -1563,6 +1564,21 @@ class ACEStepPipeline:
input_audio = input_audio.to(device=device, dtype=dtype)
latents, _ = self.music_dcae.encode(input_audio, sr=sr)
return latents
def load_lora(self, lora_name_or_path):
if lora_name_or_path != self.lora_path and lora_name_or_path != "none":
if not os.path.exists(lora_name_or_path):
lora_download_path = snapshot_download(lora_name_or_path, cache_dir=self.checkpoint_dir)
else:
lora_download_path = lora_name_or_path
if self.lora_path != "none":
self.ace_step_transformer.unload_lora()
self.ace_step_transformer.load_lora_adapter(os.path.join(lora_download_path, "pytorch_lora_weights.safetensors"), adapter_name="zh_rap_lora", with_alpha=True)
logger.info(f"Loading lora weights from: {lora_name_or_path} download path is: {lora_download_path}")
self.lora_path = lora_name_or_path
elif self.lora_path != "none" and lora_name_or_path == "none":
logger.info("No lora weights to load.")
self.ace_step_transformer.unload_lora()
def __call__(
self,
@@ -1587,6 +1603,7 @@ class ACEStepPipeline:
audio2audio_enable: bool = False,
ref_audio_strength: float = 0.5,
ref_audio_input: str = None,
lora_name_or_path: str = "none",
retake_seeds: list = None,
retake_variance: float = 0.5,
task: str = "text2music",
@@ -1615,8 +1632,10 @@ class ACEStepPipeline:
self.load_quantized_checkpoint(self.checkpoint_dir)
else:
self.load_checkpoint(self.checkpoint_dir)
load_model_cost = time.time() - start_time
logger.info(f"Model loaded in {load_model_cost:.2f} seconds.")
self.load_lora(lora_name_or_path)
load_model_cost = time.time() - start_time
logger.info(f"Model loaded in {load_model_cost:.2f} seconds.")
start_time = time.time()
@@ -1813,6 +1832,7 @@ class ACEStepPipeline:
}
input_params_json = {
"lora_name_or_path": lora_name_or_path,
"task": task,
"prompt": prompt if task != "edit" else edit_target_prompt,
"lyrics": lyrics if task != "edit" else edit_target_lyrics,