| | import torch |
| | from nodes import MAX_RESOLUTION, ConditioningZeroOut, ConditioningSetTimestepRange, ConditioningCombine |
| |
|
| | class CLIPTextEncodeSDXLSimplified: |
| | @classmethod |
| | def INPUT_TYPES(s): |
| | return {"required": { |
| | "width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}), |
| | "height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}), |
| | "size_cond_factor": ("INT", {"default": 4, "min": 1, "max": 16 }), |
| | "text": ("STRING", {"multiline": True, "dynamicPrompts": True, "default": ""}), |
| | "clip": ("CLIP", ), |
| | }} |
| | RETURN_TYPES = ("CONDITIONING",) |
| | FUNCTION = "execute" |
| | CATEGORY = "essentials/conditioning" |
| |
|
| | def execute(self, clip, width, height, size_cond_factor, text): |
| | crop_w = 0 |
| | crop_h = 0 |
| | width = width*size_cond_factor |
| | height = height*size_cond_factor |
| | target_width = width |
| | target_height = height |
| | text_g = text_l = text |
| |
|
| | tokens = clip.tokenize(text_g) |
| | tokens["l"] = clip.tokenize(text_l)["l"] |
| | if len(tokens["l"]) != len(tokens["g"]): |
| | empty = clip.tokenize("") |
| | while len(tokens["l"]) < len(tokens["g"]): |
| | tokens["l"] += empty["l"] |
| | while len(tokens["l"]) > len(tokens["g"]): |
| | tokens["g"] += empty["g"] |
| | cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True) |
| | return ([[cond, {"pooled_output": pooled, "width": width, "height": height, "crop_w": crop_w, "crop_h": crop_h, "target_width": target_width, "target_height": target_height}]], ) |
| |
|
| | class ConditioningCombineMultiple: |
| | @classmethod |
| | def INPUT_TYPES(s): |
| | return { |
| | "required": { |
| | "conditioning_1": ("CONDITIONING",), |
| | "conditioning_2": ("CONDITIONING",), |
| | }, "optional": { |
| | "conditioning_3": ("CONDITIONING",), |
| | "conditioning_4": ("CONDITIONING",), |
| | "conditioning_5": ("CONDITIONING",), |
| | }, |
| | } |
| | RETURN_TYPES = ("CONDITIONING",) |
| | FUNCTION = "execute" |
| | CATEGORY = "essentials/conditioning" |
| |
|
| | def execute(self, conditioning_1, conditioning_2, conditioning_3=None, conditioning_4=None, conditioning_5=None): |
| | c = conditioning_1 + conditioning_2 |
| |
|
| | if conditioning_3 is not None: |
| | c += conditioning_3 |
| | if conditioning_4 is not None: |
| | c += conditioning_4 |
| | if conditioning_5 is not None: |
| | c += conditioning_5 |
| |
|
| | return (c,) |
| |
|
| | class SD3NegativeConditioning: |
| | @classmethod |
| | def INPUT_TYPES(s): |
| | return {"required": { |
| | "conditioning": ("CONDITIONING",), |
| | "end": ("FLOAT", {"default": 0.1, "min": 0.0, "max": 1.0, "step": 0.001 }), |
| | }} |
| | RETURN_TYPES = ("CONDITIONING",) |
| | FUNCTION = "execute" |
| | CATEGORY = "essentials/conditioning" |
| |
|
| | def execute(self, conditioning, end): |
| | zero_c = ConditioningZeroOut().zero_out(conditioning)[0] |
| |
|
| | if end == 0: |
| | return (zero_c, ) |
| |
|
| | c = ConditioningSetTimestepRange().set_range(conditioning, 0, end)[0] |
| | zero_c = ConditioningSetTimestepRange().set_range(zero_c, end, 1.0)[0] |
| | c = ConditioningCombine().combine(zero_c, c)[0] |
| |
|
| | return (c, ) |
| |
|
| | COND_CLASS_MAPPINGS = { |
| | "CLIPTextEncodeSDXL+": CLIPTextEncodeSDXLSimplified, |
| | "ConditioningCombineMultiple+": ConditioningCombineMultiple, |
| | "SD3NegativeConditioning+": SD3NegativeConditioning, |
| | } |
| |
|
| | COND_NAME_MAPPINGS = { |
| | "CLIPTextEncodeSDXL+": "🔧 SDXL CLIPTextEncode", |
| | "ConditioningCombineMultiple+": "🔧 Cond Combine Multiple", |
| | "SD3NegativeConditioning+": "🔧 SD3 Negative Conditioning" |
| | } |