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feat(lora_randomizer): implement dual seed mechanism for batch queue synchronization, fixes #773

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- Add execution_seed and next_seed parameters to support deterministic randomization across batch executions
- Separate UI display generation from execution stack generation to maintain consistency in batch queues
- Update LoraService to accept optional seed parameter for reproducible randomization
- Ensure each execution with a different seed produces unique results without affecting global random state
This commit is contained in:
Will Miao
2026-01-21 00:52:08 +08:00
parent 50c012ae33
commit fd06086a05
7 changed files with 134 additions and 19 deletions
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31
py/nodes/lora_randomizer.py
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@@ -74,21 +74,38 @@ class LoraRandomizerNode:
roll_mode = randomizer_config.get("roll_mode", "always")
logger.debug(f"[LoraRandomizerNode] roll_mode: {roll_mode}")
# Dual seed mechanism for batch queue synchronization
# execution_seed: seed for generating execution_stack (= previous next_seed)
# next_seed: seed for generating ui_loras (= what will be displayed after execution)
execution_seed = randomizer_config.get("execution_seed", None)
next_seed = randomizer_config.get("next_seed", None)
if roll_mode == "fixed":
ui_loras = loras
execution_loras = loras
else:
scanner = await ServiceRegistry.get_lora_scanner()
# Generate execution_loras from execution_seed (if available)
if execution_seed is not None:
# Use execution_seed to regenerate the same loras that were shown to user
execution_loras = await self._generate_random_loras_for_ui(
scanner, randomizer_config, loras, pool_config, seed=execution_seed
)
else:
# First execution: use loras input (what user sees in the widget)
execution_loras = loras
# Generate ui_loras from next_seed (for display after execution)
ui_loras = await self._generate_random_loras_for_ui(
scanner, randomizer_config, loras, pool_config
scanner, randomizer_config, loras, pool_config, seed=next_seed
)
print("pool config", pool_config)
execution_stack = self._build_execution_stack_from_input(loras)
execution_stack = self._build_execution_stack_from_input(execution_loras)
return {
"result": (execution_stack,),
"ui": {"loras": ui_loras, "last_used": loras},
"ui": {"loras": ui_loras, "last_used": execution_loras},
}
def _build_execution_stack_from_input(self, loras):
@@ -126,7 +143,7 @@ class LoraRandomizerNode:
return lora_stack
async def _generate_random_loras_for_ui(
self, scanner, randomizer_config, input_loras, pool_config=None
self, scanner, randomizer_config, input_loras, pool_config=None, seed=None
):
"""
Generate new random loras for UI display.
@@ -136,6 +153,7 @@ class LoraRandomizerNode:
randomizer_config: Dict with randomizer settings
input_loras: Current input loras (for extracting locked loras)
pool_config: Optional pool filters
seed: Optional seed for deterministic randomization
Returns:
List of LoRA dicts for UI display
@@ -182,6 +200,7 @@ class LoraRandomizerNode:
use_recommended_strength=use_recommended_strength,
recommended_strength_scale_min=recommended_strength_scale_min,
recommended_strength_scale_max=recommended_strength_scale_max,
seed=seed,
)
return result_loras