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Merge pull request #3 from mekinney/bug-xyplot-save-model-and-clip-when-processing-lora-stack-in-xyplot

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Update clip and model when adding loras
This commit is contained in:
Mike Kinney
2025-05-13 16:52:23 -07:00
committed by GitHub
parent 8aadd72494 5d8f0a3b0a
commit 2f2a3035a2
2 changed files with 8 additions and 15 deletions
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py/libs/loader.py
+4
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@@ -432,10 +432,13 @@ class easyLoader:
clip_vision = None
lora_stack = []
# Check for model override
can_load_lora = True
# 判断是否存在 模型或Lora叠加xyplot, 若存在优先缓存第一个模型
# Determine whether there is a model or Lora overlapping xyplot, and if there is, prioritize caching the first model.
xy_model_id = next((x for x in prompt if str(prompt[x]["class_type"]) in ["easy XYInputs: ModelMergeBlocks",
"easy XYInputs: Checkpoint"]), None)
# This will find nodes that aren't actively connected to anything, and skip loading lora's for them.
xy_lora_id = next((x for x in prompt if str(prompt[x]["class_type"]) == "easy XYInputs: Lora"), None)
if xy_lora_id is not None:
can_load_lora = False
@@ -461,6 +464,7 @@ class easyLoader:
if optional_lora_stack is not None and can_load_lora:
for lora in optional_lora_stack:
# This is a subtle bit of code because it saves the model created by the last call, and passes it to the next call.
lora = {"lora_name": lora[0], "model": model, "clip": clip, "model_strength": lora[1],
"clip_strength": lora[2]}
model, clip = self.load_lora(lora)
py/libs/xyplot.py
+4 -15
View File
@@ -211,11 +211,7 @@ class easyXYPlot():
clip = clip if clip is not None else plot_image_vars["clip"]
steps = plot_image_vars['steps'] if "steps" in plot_image_vars else 1
sd_version = get_sd_version(plot_image_vars['model'])
# print(f"sample_plot_image x_type: {self.x_type} y_type: {self.y_type} x_value: {x_value} y_value: {y_value}")
sd_version = get_sd_version(plot_image_vars['model'])
# 高级用法
if plot_image_vars["x_node_type"] == "advanced" or plot_image_vars["y_node_type"] == "advanced":
if self.x_type == "Seeds++ Batch" or self.y_type == "Seeds++ Batch":
@@ -369,25 +365,21 @@ class easyXYPlot():
# print(f"Lora: {x_value} {y_value}")
model = model if model is not None else plot_image_vars["model"]
clip = clip if clip is not None else plot_image_vars["clip"]
xy_values = x_value if self.x_type == "Lora" else y_value
lora_name, lora_model_strength, lora_clip_strength, _ = xy_values.split(",")
lora_stack = [{"lora_name": lora_name, "model": model, "clip" :clip, "model_strength": float(lora_model_strength), "clip_strength": float(lora_clip_strength)}]
# print(f"new_lora_stack: {new_lora_stack}")
# optional_lora_stack = plot_image_vars['lora_stack']
# print(f"optional_lora_stack: {optional_lora_stack}")
# if optional_lora_stack is not None and optional_lora_stack != []:
# for lora in optional_lora_stack:
# print(f"Lora: {lora}")
if 'lora_stack' in plot_image_vars:
lora_stack = lora_stack + plot_image_vars['lora_stack']
# print(f"new_lora_stack: {new_lora_stack}")
if lora_stack is not None and lora_stack != []:
for lora in lora_stack:
# Use the updated model and clip, for the next lora load.
lora['model'] = model
lora['clip'] = clip
model, clip = self.easyCache.load_lora(lora)
# 提示词
@@ -494,9 +486,6 @@ class easyXYPlot():
plot_image_vars['negative_weight_interpretation'], w_max=1.0,
apply_to_pooled="enable", a1111_prompt_style=a1111_prompt_style, steps=steps)
# print(f"plotting image")
# if model is not None:
# pprint.pp(f"Model: {model}")
model = model if model is not None else plot_image_vars["model"]
vae = vae if vae is not None else plot_image_vars["vae"]