Fix comfy extras dependency issue for V3
This commit is contained in:
bash-j
@@ -158,3 +158,4 @@ cython_debug/
|
||||
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
||||
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
||||
#.idea/
|
||||
.vscode/settings.json
|
||||
|
||||
+123
-28
@@ -24,15 +24,108 @@ import torch.nn.functional as F
|
||||
from tqdm import tqdm
|
||||
|
||||
import folder_paths
|
||||
from comfy_extras.nodes_clip_sdxl import CLIPTextEncodeSDXL, CLIPTextEncodeSDXLRefiner
|
||||
import comfy_extras
|
||||
from comfy_extras.nodes_upscale_model import UpscaleModelLoader, ImageUpscaleWithModel
|
||||
from comfy.model_management import soft_empty_cache, free_memory, get_torch_device, current_loaded_models, load_model_gpu
|
||||
from spandrel import ModelLoader, ImageModelDescriptor
|
||||
from comfy import model_management
|
||||
from nodes import LoraLoader, ConditioningAverage, common_ksampler, ImageScale, ImageScaleBy, VAEEncode, VAEDecode
|
||||
import comfy.utils
|
||||
from comfy_extras.chainner_models import model_loading
|
||||
from comfy_extras.nodes_custom_sampler import Noise_EmptyNoise, Noise_RandomNoise
|
||||
from comfy import model_management, model_base
|
||||
|
||||
# region COMFY_EXTRAS
|
||||
def CLIPTextEncodeSDXLRefiner_encode(clip, ascore, width, height, text):
|
||||
tokens = clip.tokenize(text)
|
||||
return (clip.encode_from_tokens_scheduled(tokens, add_dict={"aesthetic_score": ascore, "width": width, "height": height}), )
|
||||
|
||||
def CLIPTextEncodeSDXL_encode(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"]
|
||||
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"]
|
||||
return (clip.encode_from_tokens_scheduled(tokens, add_dict={"width": width, "height": height, "crop_w": crop_w, "crop_h": crop_h, "target_width": target_width, "target_height": target_height}), )
|
||||
|
||||
class UpscaleModelLoader:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": { "model_name": (folder_paths.get_filename_list("upscale_models"), ),
|
||||
}}
|
||||
RETURN_TYPES = ("UPSCALE_MODEL",)
|
||||
FUNCTION = "load_model"
|
||||
|
||||
CATEGORY = "loaders"
|
||||
|
||||
def load_model(self, model_name):
|
||||
model_path = folder_paths.get_full_path_or_raise("upscale_models", model_name)
|
||||
sd = comfy.utils.load_torch_file(model_path, safe_load=True)
|
||||
if "module.layers.0.residual_group.blocks.0.norm1.weight" in sd:
|
||||
sd = comfy.utils.state_dict_prefix_replace(sd, {"module.":""})
|
||||
out = ModelLoader().load_from_state_dict(sd).eval()
|
||||
|
||||
if not isinstance(out, ImageModelDescriptor):
|
||||
raise Exception("Upscale model must be a single-image model.")
|
||||
|
||||
return (out, )
|
||||
|
||||
class ImageUpscaleWithModel:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": { "upscale_model": ("UPSCALE_MODEL",),
|
||||
"image": ("IMAGE",),
|
||||
}}
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
FUNCTION = "upscale"
|
||||
|
||||
CATEGORY = "image/upscaling"
|
||||
|
||||
def upscale(self, upscale_model, image):
|
||||
device = model_management.get_torch_device()
|
||||
|
||||
memory_required = model_management.module_size(upscale_model.model)
|
||||
memory_required += (512 * 512 * 3) * image.element_size() * max(upscale_model.scale, 1.0) * 384.0 #The 384.0 is an estimate of how much some of these models take, TODO: make it more accurate
|
||||
memory_required += image.nelement() * image.element_size()
|
||||
model_management.free_memory(memory_required, device)
|
||||
|
||||
upscale_model.to(device)
|
||||
in_img = image.movedim(-1,-3).to(device)
|
||||
|
||||
tile = 512
|
||||
overlap = 32
|
||||
|
||||
oom = True
|
||||
while oom:
|
||||
try:
|
||||
steps = in_img.shape[0] * comfy.utils.get_tiled_scale_steps(in_img.shape[3], in_img.shape[2], tile_x=tile, tile_y=tile, overlap=overlap)
|
||||
pbar = comfy.utils.ProgressBar(steps)
|
||||
s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, pbar=pbar)
|
||||
oom = False
|
||||
except model_management.OOM_EXCEPTION as e:
|
||||
tile //= 2
|
||||
if tile < 128:
|
||||
raise e
|
||||
|
||||
upscale_model.to("cpu")
|
||||
s = torch.clamp(s.movedim(-3,-1), min=0, max=1.0)
|
||||
return (s,)
|
||||
|
||||
class Noise_EmptyNoise:
|
||||
def __init__(self):
|
||||
self.seed = 0
|
||||
|
||||
def generate_noise(self, input_latent):
|
||||
latent_image = input_latent["samples"]
|
||||
return torch.zeros(latent_image.shape, dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
|
||||
|
||||
class Noise_RandomNoise:
|
||||
def __init__(self, seed):
|
||||
self.seed = seed
|
||||
|
||||
def generate_noise(self, input_latent):
|
||||
latent_image = input_latent["samples"]
|
||||
batch_inds = input_latent["batch_index"] if "batch_index" in input_latent else None
|
||||
return comfy.sample.prepare_noise(latent_image, self.seed, batch_inds)
|
||||
# end region
|
||||
|
||||
def calculate_file_hash(file_path):
|
||||
# open the file in binary mode
|
||||
@@ -1816,6 +1909,8 @@ class PromptWithStyleV2:
|
||||
FUNCTION = 'start'
|
||||
CATEGORY = 'Mikey'
|
||||
|
||||
|
||||
|
||||
def start(self, clip_base, clip_refiner, positive_prompt, negative_prompt, style, ratio_selected, batch_size, seed):
|
||||
""" get output from PromptWithStyle.start """
|
||||
(latent,
|
||||
@@ -1835,10 +1930,10 @@ class PromptWithStyleV2:
|
||||
# 'Target Width:', target_width, 'Target Height:', target_height,
|
||||
# 'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
|
||||
# encode text
|
||||
sdxl_pos_cond = CLIPTextEncodeSDXL.encode(self, clip_base, width, height, 0, 0, target_width, target_height, pos_prompt, pos_style)[0]
|
||||
sdxl_neg_cond = CLIPTextEncodeSDXL.encode(self, clip_base, width, height, 0, 0, target_width, target_height, neg_prompt, neg_style)[0]
|
||||
refiner_pos_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 6, refiner_width, refiner_height, pos_prompt)[0]
|
||||
refiner_neg_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt)[0]
|
||||
sdxl_pos_cond = CLIPTextEncodeSDXL_encode(clip_base, width, height, 0, 0, target_width, target_height, pos_prompt, pos_style)[0]
|
||||
sdxl_neg_cond = CLIPTextEncodeSDXL_encode(clip_base, width, height, 0, 0, target_width, target_height, neg_prompt, neg_style)[0]
|
||||
refiner_pos_cond = CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 6, refiner_width, refiner_height, pos_prompt)[0]
|
||||
refiner_neg_cond = CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt)[0]
|
||||
# return
|
||||
return (latent,
|
||||
sdxl_pos_cond, sdxl_neg_cond,
|
||||
@@ -2117,10 +2212,10 @@ class PromptWithStyleV3:
|
||||
# encode text
|
||||
add_metadata_to_dict(prompt_with_style, style=style_, clip_g_positive=pos_prompt, clip_l_positive=pos_style_)
|
||||
add_metadata_to_dict(prompt_with_style, clip_g_negative=neg_prompt, clip_l_negative=neg_style_)
|
||||
sdxl_pos_cond = CLIPTextEncodeSDXL.encode(self, clip_base_pos, width, height, 0, 0, target_width, target_height, pos_prompt_, pos_style_)[0]
|
||||
sdxl_neg_cond = CLIPTextEncodeSDXL.encode(self, clip_base_neg, width, height, 0, 0, target_width, target_height, neg_prompt_, neg_style_)[0]
|
||||
refiner_pos_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 6, refiner_width, refiner_height, pos_prompt_)[0]
|
||||
refiner_neg_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt_)[0]
|
||||
sdxl_pos_cond = CLIPTextEncodeSDXL_encode(clip_base_pos, width, height, 0, 0, target_width, target_height, pos_prompt_, pos_style_)[0]
|
||||
sdxl_neg_cond = CLIPTextEncodeSDXL_encode(clip_base_neg, width, height, 0, 0, target_width, target_height, neg_prompt_, neg_style_)[0]
|
||||
refiner_pos_cond = CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 6, refiner_width, refiner_height, pos_prompt_)[0]
|
||||
refiner_neg_cond = CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt_)[0]
|
||||
#prompt.get(str(unique_id))['inputs']['output_positive_prompt'] = pos_prompt_
|
||||
#prompt.get(str(unique_id))['inputs']['output_negative_prompt'] = neg_prompt_
|
||||
#prompt.get(str(unique_id))['inputs']['output_latent_width'] = width
|
||||
@@ -2166,10 +2261,10 @@ class PromptWithStyleV3:
|
||||
# encode text
|
||||
add_metadata_to_dict(prompt_with_style, style=style_, clip_g_positive=pos_prompt_, clip_l_positive=pos_style_)
|
||||
add_metadata_to_dict(prompt_with_style, clip_g_negative=neg_prompt_, clip_l_negative=neg_style_)
|
||||
base_pos_conds.append(CLIPTextEncodeSDXL.encode(self, clip_base_pos, width_, height_, 0, 0, target_width, target_height, pos_prompt_, pos_style_)[0])
|
||||
base_neg_conds.append(CLIPTextEncodeSDXL.encode(self, clip_base_neg, width_, height_, 0, 0, target_width, target_height, neg_prompt_, neg_style_)[0])
|
||||
refiner_pos_conds.append(CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 6, refiner_width_, refiner_height_, pos_prompt_)[0])
|
||||
refiner_neg_conds.append(CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 2.5, refiner_width_, refiner_height_, neg_prompt_)[0])
|
||||
base_pos_conds.append(CLIPTextEncodeSDXL_encode(clip_base_pos, width_, height_, 0, 0, target_width, target_height, pos_prompt_, pos_style_)[0])
|
||||
base_neg_conds.append(CLIPTextEncodeSDXL_encode(clip_base_neg, width_, height_, 0, 0, target_width, target_height, neg_prompt_, neg_style_)[0])
|
||||
refiner_pos_conds.append(CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 6, refiner_width_, refiner_height_, pos_prompt_)[0])
|
||||
refiner_neg_conds.append(CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 2.5, refiner_width_, refiner_height_, neg_prompt_)[0])
|
||||
# if none of the styles matched we will get an empty list so we need to check for that again
|
||||
if len(base_pos_conds) == 0:
|
||||
style_ = 'none'
|
||||
@@ -2180,10 +2275,10 @@ class PromptWithStyleV3:
|
||||
# encode text
|
||||
add_metadata_to_dict(prompt_with_style, style=style_, clip_g_positive=pos_prompt_, clip_l_positive=pos_style_)
|
||||
add_metadata_to_dict(prompt_with_style, clip_g_negative=neg_prompt_, clip_l_negative=neg_style_)
|
||||
sdxl_pos_cond = CLIPTextEncodeSDXL.encode(self, clip_base_pos, width, height, 0, 0, target_width, target_height, pos_prompt_, pos_style_)[0]
|
||||
sdxl_neg_cond = CLIPTextEncodeSDXL.encode(self, clip_base_neg, width, height, 0, 0, target_width, target_height, neg_prompt_, neg_style_)[0]
|
||||
refiner_pos_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 6, refiner_width, refiner_height, pos_prompt_)[0]
|
||||
refiner_neg_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt_)[0]
|
||||
sdxl_pos_cond = CLIPTextEncodeSDXL_encode(clip_base_pos, width, height, 0, 0, target_width, target_height, pos_prompt_, pos_style_)[0]
|
||||
sdxl_neg_cond = CLIPTextEncodeSDXL_encode(clip_base_neg, width, height, 0, 0, target_width, target_height, neg_prompt_, neg_style_)[0]
|
||||
refiner_pos_cond = CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 6, refiner_width, refiner_height, pos_prompt_)[0]
|
||||
refiner_neg_cond = CLIPTextEncodeSDXLRefiner_encode(clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt_)[0]
|
||||
#prompt.get(str(unique_id))['inputs']['output_positive_prompt'] = pos_prompt_
|
||||
#prompt.get(str(unique_id))['inputs']['output_negative_prompt'] = neg_prompt_
|
||||
#prompt.get(str(unique_id))['inputs']['output_latent_width'] = width
|
||||
@@ -2388,10 +2483,10 @@ class StyleConditioner:
|
||||
if style == 'none':
|
||||
return (positive_cond_base, negative_cond_base, positive_cond_refiner, negative_cond_refiner, style, )
|
||||
# encode the style prompt
|
||||
positive_cond_base_new = CLIPTextEncodeSDXL.encode(self, base_clip, 1024, 1024, 0, 0, 1024, 1024, pos_prompt, pos_prompt)[0]
|
||||
negative_cond_base_new = CLIPTextEncodeSDXL.encode(self, base_clip, 1024, 1024, 0, 0, 1024, 1024, neg_prompt, neg_prompt)[0]
|
||||
positive_cond_refiner_new = CLIPTextEncodeSDXLRefiner.encode(self, refiner_clip, 6, 4096, 4096, pos_prompt)[0]
|
||||
negative_cond_refiner_new = CLIPTextEncodeSDXLRefiner.encode(self, refiner_clip, 2.5, 4096, 4096, neg_prompt)[0]
|
||||
positive_cond_base_new = CLIPTextEncodeSDXL_encode(base_clip, 1024, 1024, 0, 0, 1024, 1024, pos_prompt, pos_prompt)[0]
|
||||
negative_cond_base_new = CLIPTextEncodeSDXL_encode(base_clip, 1024, 1024, 0, 0, 1024, 1024, neg_prompt, neg_prompt)[0]
|
||||
positive_cond_refiner_new = CLIPTextEncodeSDXLRefiner_encode(refiner_clip, 6, 4096, 4096, pos_prompt)[0]
|
||||
negative_cond_refiner_new = CLIPTextEncodeSDXLRefiner_encode(refiner_clip, 2.5, 4096, 4096, neg_prompt)[0]
|
||||
# average the style prompt with the existing conditioning
|
||||
positive_cond_base = ConditioningAverage.addWeighted(self, positive_cond_base_new, positive_cond_base, strength)[0]
|
||||
negative_cond_base = ConditioningAverage.addWeighted(self, negative_cond_base_new, negative_cond_base, strength)[0]
|
||||
@@ -2430,8 +2525,8 @@ class StyleConditionerBaseOnly:
|
||||
if style == 'none':
|
||||
return (positive_cond_base, negative_cond_base, style, )
|
||||
# encode the style prompt
|
||||
positive_cond_base_new = CLIPTextEncodeSDXL.encode(self, base_clip, 1024, 1024, 0, 0, 1024, 1024, pos_prompt, pos_prompt)[0]
|
||||
negative_cond_base_new = CLIPTextEncodeSDXL.encode(self, base_clip, 1024, 1024, 0, 0, 1024, 1024, neg_prompt, neg_prompt)[0]
|
||||
positive_cond_base_new = CLIPTextEncodeSDXL_encode(base_clip, 1024, 1024, 0, 0, 1024, 1024, pos_prompt, pos_prompt)[0]
|
||||
negative_cond_base_new = CLIPTextEncodeSDXL_encode(base_clip, 1024, 1024, 0, 0, 1024, 1024, neg_prompt, neg_prompt)[0]
|
||||
# average the style prompt with the existing conditioning
|
||||
positive_cond_base = ConditioningAverage.addWeighted(self, positive_cond_base_new, positive_cond_base, strength)[0]
|
||||
negative_cond_base = ConditioningAverage.addWeighted(self, negative_cond_base_new, negative_cond_base, strength)[0]
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "mikey_nodes"
|
||||
description = "Collection of convenient nodes. Wildcard, style, image, llm, haldclut, metadata, and more."
|
||||
version = "1.0.4"
|
||||
version = "1.0.5"
|
||||
license = { text = "MIT License" }
|
||||
|
||||
[project.urls]
|
||||
|
||||
Reference in New Issue
Block a user