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feat: add seq_parallel and cfg_parallel options to LightX2VDefaultConfig; refactor apply_teacache_config and apply_quantization_config methods for improved readability

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gaclove
2025-08-15 11:16:10 +08:00
parent 3500884a17
commit 413ab4c98e
1 changed files with 11 additions and 27 deletions
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bridge.py
+11 -27
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@@ -155,6 +155,8 @@ class LightX2VDefaultConfig:
"parallel_attn_type": None,
"parallel_vae": False,
"parallel": False,
"seq_parallel": False,
"cfg_parallel": False,
"max_area": False,
"use_prompt_enhancer": False,
"text_len": 512,
@@ -341,9 +343,7 @@ class ModularConfigManager:
return updates
def apply_teacache_config(
self, config: Dict[str, Any], model_info: Dict[str, Any]
) -> Dict[str, Any]:
def apply_teacache_config(self, config: Dict[str, Any], model_info: Dict[str, Any]) -> Dict[str, Any]:
"""Apply TeaCache configuration."""
updates = {}
@@ -359,18 +359,14 @@ class ModularConfigManager:
model_info.get("target_height", 480),
)
coeffs = CoefficientCalculator.get_coefficients(
task, model_size, resolution, updates["use_ret_steps"]
)
coeffs = CoefficientCalculator.get_coefficients(task, model_size, resolution, updates["use_ret_steps"])
updates["coefficients"] = coeffs
else:
updates["feature_caching"] = "NoCaching"
return updates
def apply_quantization_config(
self, config: Dict[str, Any], model_path: str
) -> Dict[str, Any]:
def apply_quantization_config(self, config: Dict[str, Any], model_path: str) -> Dict[str, Any]:
"""Apply quantization configuration."""
updates = {}
@@ -384,18 +380,14 @@ class ModularConfigManager:
updates["t5_quantized"] = t5_scheme != "bf16"
if t5_scheme != "bf16":
t5_path = os.path.join(model_path, t5_scheme)
updates["t5_quantized_ckpt"] = os.path.join(
t5_path, f"models_t5_umt5-xxl-enc-{t5_scheme}.pth"
)
updates["t5_quantized_ckpt"] = os.path.join(t5_path, f"models_t5_umt5-xxl-enc-{t5_scheme}.pth")
clip_scheme = config.get("clip_precision", "fp16")
updates["clip_quant_scheme"] = clip_scheme
updates["clip_quantized"] = clip_scheme != "fp16"
if clip_scheme != "fp16":
clip_path = os.path.join(model_path, clip_scheme)
updates["clip_quantized_ckpt"] = os.path.join(
clip_path, f"clip-{clip_scheme}.pth"
)
updates["clip_quantized_ckpt"] = os.path.join(clip_path, f"clip-{clip_scheme}.pth")
quant_backend = config.get("quant_backend", "vllm")
updates["quant_op"] = quant_backend
@@ -409,9 +401,7 @@ class ModularConfigManager:
else:
mm_type = f"W-{dit_scheme}-channel-sym-A-{dit_scheme}-channel-sym-dynamic-Sgl"
elif quant_backend == "q8f":
mm_type = (
f"W-{dit_scheme}-channel-sym-A-{dit_scheme}-channel-sym-dynamic-Q8F"
)
mm_type = f"W-{dit_scheme}-channel-sym-A-{dit_scheme}-channel-sym-dynamic-Q8F"
updates["t5_quant_scheme"] = "int8-q8f"
updates["clip_quant_scheme"] = "int8-q8f"
elif quant_backend == "torchao":
@@ -456,9 +446,7 @@ class ModularConfigManager:
# T5 offloading
if level in ["high", "extreme"]:
updates["t5_cpu_offload"] = True
updates["t5_offload_granularity"] = (
"block" if level == "extreme" else "model"
)
updates["t5_offload_granularity"] = "block" if level == "extreme" else "model"
# Module management
if config.get("lazy_load", False) or level == "extreme":
@@ -476,9 +464,7 @@ class ModularConfigManager:
return updates
def apply_vae_config(
self, config: Dict[str, Any], model_path: str
) -> Dict[str, Any]:
def apply_vae_config(self, config: Dict[str, Any], model_path: str) -> Dict[str, Any]:
"""Apply VAE configuration."""
updates = {}
@@ -508,9 +494,7 @@ class ModularConfigManager:
if "quantization" in configs:
model_path = final_config.get("model_path", "")
quant_updates = self.apply_quantization_config(
configs["quantization"], model_path
)
quant_updates = self.apply_quantization_config(configs["quantization"], model_path)
final_config.update(quant_updates)
if "memory" in configs: