Fix basic xyplot lora load error #257
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@@ -1,8 +1,8 @@
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import comfy.model_management
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import comfy.samplers
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from torch.nn import Linear
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def add_model_patch(model, sd):
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from torch.nn import Linear
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load_device = comfy.model_management.get_torch_device()
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encoder_hid_proj_weight = sd.pop("encoder_hid_proj.weight")
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encoder_hid_proj_bias = sd.pop("encoder_hid_proj.bias")
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@@ -486,7 +486,6 @@ class easyLoader:
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else:
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from ..kolors.loader import applyKolorsUnet
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with applyKolorsUnet():
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unet_path = folder_paths.get_full_path("unet", unet_name)
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sd = comfy.utils.load_torch_file(unet_path)
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model = comfy.sd.load_unet_state_dict(sd)
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@@ -5,6 +5,19 @@ class AlwaysEqualProxy(str):
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def __ne__(self, _):
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return False
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class TautologyStr(str):
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def __ne__(self, other):
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return False
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class ByPassTypeTuple(tuple):
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def __getitem__(self, index):
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if index>0:
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index=0
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item = super().__getitem__(index)
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if isinstance(item, str):
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return TautologyStr(item)
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return item
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comfy_ui_revision = None
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def get_comfyui_revision():
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try:
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+1
-1
@@ -394,7 +394,7 @@ class easyXYPlot():
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model, clip, vae, clip_vision = self.easyCache.load_checkpoint(plot_image_vars['ckpt_name'])
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if plot_image_vars['lora_name'] != "None":
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lora = {"lora_name": plot_image_vars['lora_name'], "model": model, "clip": clip, "model_strength": plot_image_vars['model_strength'], "clip_strength": plot_image_vars['lora_clip_strength']}
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lora = {"lora_name": plot_image_vars['lora_name'], "model": model, "clip": clip, "model_strength": plot_image_vars['lora_model_strength'], "clip_strength": plot_image_vars['lora_clip_strength']}
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model, clip = self.easyCache.load_lora(lora)
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# Check for custom VAE
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+4
-5
@@ -1,7 +1,7 @@
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from typing import Iterator, List, Tuple, Dict, Any, Union, Optional
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from _decimal import Context, getcontext
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from decimal import Decimal
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from .libs.utils import AlwaysEqualProxy, cleanGPUUsedForce
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from .libs.utils import AlwaysEqualProxy, ByPassTypeTuple, cleanGPUUsedForce
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from .libs.cache import remove_cache
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import numpy as np
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import json
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@@ -424,19 +424,18 @@ class ConvertAnything:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {
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"anything": (AlwaysEqualProxy("*"),),
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"*": (AlwaysEqualProxy("*"),),
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"output_type": (["string", "int", "float", "boolean"], {"default": "string"}),
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}}
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RETURN_TYPES = (AlwaysEqualProxy("*"),),
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RETURN_NAMES = ('*',)
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RETURN_TYPES = ByPassTypeTuple((AlwaysEqualProxy("*"),))
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OUTPUT_NODE = True
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FUNCTION = "convert"
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CATEGORY = "EasyUse/Logic"
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def convert(self, *args, **kwargs):
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print(kwargs)
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anything = kwargs['anything']
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anything = kwargs['*']
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output_type = kwargs['output_type']
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params = None
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if output_type == 'string':
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@@ -1176,22 +1176,15 @@ app.registerExtension({
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if(nodeData.name == 'easy convertAnything'){
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const onNodeCreated = nodeType.prototype.onNodeCreated;
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const changeType = async function (type) {
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const body = new FormData();
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body.append("type", type);
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const response = await api.fetchApi("/easyuse/convert", { method:'POST',body});
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}
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nodeType.prototype.onNodeCreated = async function () {
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onNodeCreated ? onNodeCreated.apply(this, []) : undefined;
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setTimeout(_=>{
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const type_control = this.widgets[this.widgets.findIndex((w) => w.name === "output_type")]
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let _this = this
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changeType(type_control.value)
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type_control.callback = async() => {
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_this.outputs[0].type = (type_control.value).toUpperCase()
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_this.outputs[0].name = type_control.value
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_this.outputs[0].label = type_control.value
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changeType(type_control.value)
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}
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},300)
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