wangbo/ComfyUI
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Merge branch 'Main' into execution

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Dr.Lt.Data 2023-07-04 10:08:29 +09:00
commit e3d819ae99
5 changed files with 57 additions and 5 deletions
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3
comfy/sd.py
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@ -526,12 +526,13 @@ class CLIP:
def __init__(self, target=None, embedding_directory=None, no_init=False):
if no_init:
return
params = target.params
params = target.params.copy()
clip = target.clip
tokenizer = target.tokenizer
load_device = model_management.text_encoder_device()
offload_device = model_management.text_encoder_offload_device()
params['device'] = load_device
self.cond_stage_model = clip(**(params))
#TODO: make sure this doesn't have a quality loss before enabling.
# if model_management.should_use_fp16(load_device):

4
comfy/sd2_clip.py
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@ -3,9 +3,9 @@ import torch
import os
class SD2ClipModel(sd1_clip.SD1ClipModel):
def __init__(self, arch="ViT-H-14", device="cpu", max_length=77, freeze=True, layer="penultimate", layer_idx=None):
def __init__(self, arch="ViT-H-14", device="cpu", max_length=77, freeze=True, layer="penultimate", layer_idx=None, textmodel_path=None):
textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "sd2_clip_config.json")
super().__init__(device=device, freeze=freeze, textmodel_json_config=textmodel_json_config)
super().__init__(device=device, freeze=freeze, textmodel_json_config=textmodel_json_config, textmodel_path=textmodel_path)
self.empty_tokens = [[49406] + [49407] + [0] * 75]
if layer == "last":
pass

4
comfy/sdxl_clip.py
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@ -3,9 +3,9 @@ import torch
import os
class SDXLClipG(sd1_clip.SD1ClipModel):
def __init__(self, device="cpu", max_length=77, freeze=True, layer="penultimate", layer_idx=None):
def __init__(self, device="cpu", max_length=77, freeze=True, layer="penultimate", layer_idx=None, textmodel_path=None):
textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "clip_config_bigg.json")
super().__init__(device=device, freeze=freeze, textmodel_json_config=textmodel_json_config)
super().__init__(device=device, freeze=freeze, textmodel_json_config=textmodel_json_config, textmodel_path=textmodel_path)
self.empty_tokens = [[49406] + [49407] + [0] * 75]
self.text_projection = torch.nn.Parameter(torch.empty(1280, 1280))
self.layer_norm_hidden_state = False

50
comfy_extras/nodes_clip_sdxl.py Normal file
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@ -0,0 +1,50 @@
import torch
from nodes import MAX_RESOLUTION
class CLIPTextEncodeSDXLRefiner:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"ascore": ("FLOAT", {"default": 6.0, "min": 0.0, "max": 1000.0, "step": 0.01}),
"width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text": ("STRING", {"multiline": True}), "clip": ("CLIP", ),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
CATEGORY = "advanced/conditioning"
def encode(self, clip, ascore, width, height, text):
tokens = clip.tokenize(text)
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
return ([[cond, {"pooled_output": pooled, "aesthetic_score": ascore, "width": width,"height": height}]], )
class CLIPTextEncodeSDXL:
@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}),
"crop_w": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"crop_h": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION}),
"target_width": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"target_height": ("INT", {"default": 1024.0, "min": 0, "max": MAX_RESOLUTION}),
"text_g": ("STRING", {"multiline": True, "default": "CLIP_G"}), "clip": ("CLIP", ),
"text_l": ("STRING", {"multiline": True, "default": "CLIP_L"}), "clip": ("CLIP", ),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "encode"
CATEGORY = "advanced/conditioning"
def encode(self, clip, width, height, crop_w, crop_h, target_width, target_height, text_g, text_l):
tokens = clip.tokenize(text_g)
tokens["l"] = clip.tokenize(text_l)["l"]
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}]], )
NODE_CLASS_MAPPINGS = {
"CLIPTextEncodeSDXLRefiner": CLIPTextEncodeSDXLRefiner,
"CLIPTextEncodeSDXL": CLIPTextEncodeSDXL,
}

1
nodes.py
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@ -1501,5 +1501,6 @@ def init_custom_nodes():
load_custom_node(os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_extras"), "nodes_rebatch.py"))
load_custom_node(os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_extras"), "nodes_model_merging.py"))
load_custom_node(os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_extras"), "nodes_tomesd.py"))
load_custom_node(os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_extras"), "nodes_clip_sdxl.py"))
load_custom_node(os.path.join(os.path.join(os.path.dirname(os.path.realpath(__file__)), "comfy_extras"), "nodes_execution_control.py"))
load_custom_nodes()