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https://github.com/jags111/efficiency-nodes-comfyui.git
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Merge pull request #182 from LucianoCirino/XY-Input-LoRA-Stacks-Fix
XY Input LoRA Stacks Fix
This commit is contained in:
TSC
@@ -852,7 +852,7 @@ class TSC_KSampler:
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else (os.path.basename(v[0]), v[1]) if v[2] is None
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else (os.path.basename(v[0]),) + v[1:] for v in value]
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elif type_ == "LoRA" and isinstance(value, list):
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elif (type_ == "LoRA" or type_ == "LoRA Stacks") and isinstance(value, list):
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# Return only the first Tuple of each inner array
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return [[(os.path.basename(v[0][0]),) + v[0][1:], "..."] if len(v) > 1
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else [(os.path.basename(v[0][0]),) + v[0][1:]] for v in value]
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@@ -953,6 +953,7 @@ class TSC_KSampler:
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"Checkpoint",
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"Refiner",
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"LoRA",
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"LoRA Stacks",
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"VAE",
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]
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conditioners = {
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@@ -997,6 +998,9 @@ class TSC_KSampler:
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# Create a list of tuples with types and values
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type_value_pairs = [(X_type, X_value.copy()), (Y_type, Y_value.copy())]
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# Replace "LoRA Stacks" with "LoRA"
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type_value_pairs = [('LoRA' if t == 'LoRA Stacks' else t, v) for t, v in type_value_pairs]
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# Iterate over type-value pairs
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for t, v in type_value_pairs:
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if t in dict_map:
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@@ -1039,7 +1043,7 @@ class TSC_KSampler:
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elif X_type == "Refiner":
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ckpt_dict = []
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lora_dict = []
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elif X_type == "LoRA":
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elif X_type in ("LoRA", "LoRA Stacks"):
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ckpt_dict = []
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refn_dict = []
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@@ -1202,7 +1206,7 @@ class TSC_KSampler:
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text = f"RefClipSkip ({refiner_clip_skip[0]})"
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elif "LoRA" in var_type:
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if not lora_stack:
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if not lora_stack or var_type == "LoRA Stacks":
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lora_stack = var.copy()
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else:
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# Updating the first tuple of lora_stack
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@@ -1212,7 +1216,7 @@ class TSC_KSampler:
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lora_name, lora_model_wt, lora_clip_wt = lora_stack[0]
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lora_filename = os.path.splitext(os.path.basename(lora_name))[0]
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if var_type == "LoRA":
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if var_type == "LoRA" or var_type == "LoRA Stacks":
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if len(lora_stack) == 1:
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lora_model_wt = format(float(lora_model_wt), ".2f").rstrip('0').rstrip('.')
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lora_clip_wt = format(float(lora_clip_wt), ".2f").rstrip('0').rstrip('.')
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@@ -1335,7 +1339,7 @@ class TSC_KSampler:
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# Note: Index is held at 0 when Y_type == "Nothing"
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# Load Checkpoint if required. If Y_type is LoRA, required models will be loaded by load_lora func.
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if (X_type == "Checkpoint" and index == 0 and Y_type != "LoRA"):
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if (X_type == "Checkpoint" and index == 0 and Y_type not in ("LoRA", "LoRA Stacks")):
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if lora_stack is None:
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model, clip, _ = load_checkpoint(ckpt_name, xyplot_id, cache=cache[1])
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else: # Load Efficient Loader LoRA
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@@ -1344,11 +1348,11 @@ class TSC_KSampler:
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encode = True
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# Load LoRA if required
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elif (X_type == "LoRA" and index == 0):
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elif (X_type in ("LoRA", "LoRA Stacks") and index == 0):
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# Don't cache Checkpoints
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model, clip = load_lora(lora_stack, ckpt_name, xyplot_id, cache=cache[2])
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encode = True
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elif Y_type == "LoRA": # X_type must be Checkpoint, so cache those as defined
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elif Y_type in ("LoRA", "LoRA Stacks"): # X_type must be Checkpoint, so cache those as defined
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model, clip = load_lora(lora_stack, ckpt_name, xyplot_id,
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cache=None, ckpt_cache=cache[1])
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encode = True
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@@ -1568,7 +1572,7 @@ class TSC_KSampler:
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clear_cache_by_exception(xyplot_id, lora_dict=[], refn_dict=[])
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elif X_type == "Refiner":
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clear_cache_by_exception(xyplot_id, ckpt_dict=[], lora_dict=[])
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elif X_type == "LoRA":
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elif X_type in ("LoRA", "LoRA Stacks"):
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clear_cache_by_exception(xyplot_id, ckpt_dict=[], refn_dict=[])
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# __________________________________________________________________________________________________________
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@@ -1668,7 +1672,7 @@ class TSC_KSampler:
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lora_name = lora_wt = lora_model_str = lora_clip_str = None
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# Check for all possible LoRA types
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lora_types = ["LoRA", "LoRA Batch", "LoRA Wt", "LoRA MStr", "LoRA CStr"]
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lora_types = ["LoRA", "LoRA Stacks", "LoRA Batch", "LoRA Wt", "LoRA MStr", "LoRA CStr"]
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if X_type not in lora_types and Y_type not in lora_types:
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if lora_stack:
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@@ -1681,7 +1685,7 @@ class TSC_KSampler:
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else:
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if X_type in lora_types:
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value = get_lora_sublist_name(X_type, X_value)
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if X_type == "LoRA":
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if X_type in ("LoRA", "LoRA Stacks"):
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lora_name = value
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lora_model_str = None
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lora_clip_str = None
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@@ -1703,7 +1707,7 @@ class TSC_KSampler:
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if Y_type in lora_types:
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value = get_lora_sublist_name(Y_type, Y_value)
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if Y_type == "LoRA":
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if Y_type in ("LoRA", "LoRA Stacks"):
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lora_name = value
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lora_model_str = None
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lora_clip_str = None
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@@ -1726,13 +1730,13 @@ class TSC_KSampler:
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return lora_name, lora_wt, lora_model_str, lora_clip_str
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def get_lora_sublist_name(lora_type, lora_value):
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if lora_type == "LoRA" or lora_type == "LoRA Batch":
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if lora_type in ("LoRA", "LoRA Batch", "LoRA Stacks"):
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formatted_sublists = []
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for sublist in lora_value:
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formatted_entries = []
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for x in sublist:
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base_name = os.path.splitext(os.path.basename(str(x[0])))[0]
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formatted_str = f"{base_name}({round(x[1], 3)},{round(x[2], 3)})" if lora_type == "LoRA" else f"{base_name}"
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formatted_str = f"{base_name}({round(x[1], 3)},{round(x[2], 3)})" if lora_type in ("LoRA", "LoRA Stacks") else f"{base_name}"
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formatted_entries.append(formatted_str)
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formatted_sublists.append(f"{', '.join(formatted_entries)}")
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return "\n ".join(formatted_sublists)
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@@ -2375,7 +2379,7 @@ class TSC_XYplot:
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# Check that dependencies are connected for specific plot types
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encode_types = {
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"Checkpoint", "Refiner",
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"LoRA", "LoRA Batch", "LoRA Wt", "LoRA MStr", "LoRA CStr",
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"LoRA", "LoRA Stacks", "LoRA Batch", "LoRA Wt", "LoRA MStr", "LoRA CStr",
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"Positive Prompt S/R", "Negative Prompt S/R",
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"AScore+", "AScore-",
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"Clip Skip", "Clip Skip (Refiner)",
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@@ -2391,8 +2395,13 @@ class TSC_XYplot:
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# Check if both X_type and Y_type are special lora_types
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lora_types = {"LoRA Batch", "LoRA Wt", "LoRA MStr", "LoRA CStr"}
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if (X_type in lora_types and Y_type not in lora_types) or (Y_type in lora_types and X_type not in lora_types):
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print(
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f"{error('XY Plot Error:')} Both X and Y must be connected to use the 'LoRA Plot' node.")
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print(f"{error('XY Plot Error:')} Both X and Y must be connected to use the 'LoRA Plot' node.")
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return (None,)
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# Do not allow LoRA and LoRA Stacks
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lora_types = {"LoRA", "LoRA Stacks"}
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if (X_type in lora_types and Y_type in lora_types):
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print(f"{error('XY Plot Error:')} X and Y input types must be different.")
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return (None,)
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# Clean Schedulers from Sampler data (if other type is Scheduler)
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@@ -3139,7 +3148,7 @@ class TSC_XYplot_LoRA_Stacks:
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CATEGORY = "Efficiency Nodes/XY Inputs"
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def xy_value(self, node_state, lora_stack_1=None, lora_stack_2=None, lora_stack_3=None, lora_stack_4=None, lora_stack_5=None):
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xy_type = "LoRA"
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xy_type = "LoRA Stacks"
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xy_value = [stack for stack in [lora_stack_1, lora_stack_2, lora_stack_3, lora_stack_4, lora_stack_5] if stack is not None]
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if not xy_value or not any(xy_value) or node_state == "Disabled":
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return (None,)
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