Merge pull request #30 from nkchocoai/25-support-lora-stacker

25 support lora stacker

py/capture.py

@@ -41,6 +41,18 @@ class Capture:
                             inputs[meta].append((node_id, value))
                             continue
 
+                        selector = field_data.get("selector")
+                        if selector is not None:
+                            v = selector(
+                                node_id, obj, prompt, extra_data, outputs, input_data
+                            )
+                            if isinstance(v, list):
+                                for x in v:
+                                    inputs[meta].append((node_id, x))
+                            elif v is not None:
+                                inputs[meta].append((node_id, v))
+                            continue
+
                         field_name = field_data["field_name"]
                         value = input_data.get(field_name)
                         if value is not None:

py/defs/ext/efficiency_nodes.py

@@ -1,6 +1,41 @@
 # https://github.com/jags111/efficiency-nodes-comfyui
 from ..meta import MetaField
-from ..formatters import calc_model_hash, convert_skip_clip
+from ..formatters import calc_model_hash, calc_lora_hash, convert_skip_clip
+
+
+def get_lora_model_name_stack(node_id, obj, prompt, extra_data, outputs, input_data):
+    return get_lora_data_stack(input_data, "lora_name")
+
+
+def get_lora_model_hash_stack(node_id, obj, prompt, extra_data, outputs, input_data):
+    return [
+        calc_lora_hash(model_name, input_data)
+        for model_name in get_lora_data_stack(input_data, "lora_name")
+    ]
+
+
+def get_lora_strength_model_stack(
+    node_id, obj, prompt, extra_data, outputs, input_data
+):
+    if input_data["input_mode"][0] == "advanced":
+        return get_lora_data_stack(input_data, "model_str")
+    return get_lora_data_stack(input_data, "lora_wt")
+
+
+def get_lora_strength_clip_stack(node_id, obj, prompt, extra_data, outputs, input_data):
+    if input_data["input_mode"][0] == "advanced":
+        return get_lora_data_stack(input_data, "clip_str")
+    return get_lora_data_stack(input_data, "lora_wt")
+
+
+def get_lora_data_stack(input_data, attribute):
+    lora_count = input_data["lora_count"][0]
+    return [
+        v[0]
+        for k, v in input_data.items()
+        if k.startswith(attribute) and v[0] != "None"
+    ][:lora_count]
+
 
 SAMPLERS = {
     "KSampler (Efficient)": {
@@ -63,4 +98,10 @@ CAPTURE_FIELD_LIST = {
         MetaField.SAMPLER_NAME: {"field_name": "sampler_name"},
         MetaField.SCHEDULER: {"field_name": "scheduler"},
     },
+    "LoRA Stacker": {
+        MetaField.LORA_MODEL_NAME: {"selector": get_lora_model_name_stack},
+        MetaField.LORA_MODEL_HASH: {"selector": get_lora_model_hash_stack},
+        MetaField.LORA_STRENGTH_MODEL: {"selector": get_lora_strength_model_stack},
+        MetaField.LORA_STRENGTH_CLIP: {"selector": get_lora_strength_clip_stack},
+    },
 }

py/defs/ext/rgthree.py

@@ -0,0 +1,65 @@
+# https://github.com/rgthree/rgthree-comfy
+from ..meta import MetaField
+from ..formatters import calc_lora_hash
+
+
+def get_lora_model_name(node_id, obj, prompt, extra_data, outputs, input_data):
+    return get_lora_data(input_data, "lora")
+
+
+def get_lora_model_hash(node_id, obj, prompt, extra_data, outputs, input_data):
+    return [
+        calc_lora_hash(model_name, input_data)
+        for model_name in get_lora_data(input_data, "lora")
+    ]
+
+
+def get_lora_strength(node_id, obj, prompt, extra_data, outputs, input_data):
+    return get_lora_data(input_data, "strength")
+
+
+def get_lora_data(input_data, attribute):
+    return [
+        v[0][attribute]
+        for k, v in input_data.items()
+        if k.startswith("lora_") and v[0]["on"]
+    ]
+
+
+def get_lora_model_name_stack(node_id, obj, prompt, extra_data, outputs, input_data):
+    return get_lora_data_stack(input_data, "lora")
+
+
+def get_lora_model_hash_stack(node_id, obj, prompt, extra_data, outputs, input_data):
+    return [
+        calc_lora_hash(model_name, input_data)
+        for model_name in get_lora_data_stack(input_data, "lora")
+    ]
+
+
+def get_lora_strength_stack(node_id, obj, prompt, extra_data, outputs, input_data):
+    return get_lora_data_stack(input_data, "strength")
+
+
+def get_lora_data_stack(input_data, attribute):
+    return [
+        v[0]
+        for k, v in input_data.items()
+        if k.startswith(attribute + "_") and v[0] != "None"
+    ]
+
+
+CAPTURE_FIELD_LIST = {
+    "Power Lora Loader (rgthree)": {
+        MetaField.LORA_MODEL_NAME: {"selector": get_lora_model_name},
+        MetaField.LORA_MODEL_HASH: {"selector": get_lora_model_hash},
+        MetaField.LORA_STRENGTH_MODEL: {"selector": get_lora_strength},
+        MetaField.LORA_STRENGTH_CLIP: {"selector": get_lora_strength},
+    },
+    "Lora Loader Stack (rgthree)": {
+        MetaField.LORA_MODEL_NAME: {"selector": get_lora_model_name_stack},
+        MetaField.LORA_MODEL_HASH: {"selector": get_lora_model_hash_stack},
+        MetaField.LORA_STRENGTH_MODEL: {"selector": get_lora_strength_stack},
+        MetaField.LORA_STRENGTH_CLIP: {"selector": get_lora_strength_stack},
+    },
+}