first pass to try and fix ComfyUI loading
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+15
-29
@@ -5,13 +5,14 @@ import torch
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from huggingface_hub import hf_hub_download
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import os, json, random, time, sys
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sys.path.append('.')
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sys.path.append('..')
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from trainer.models import load_models, pretrained_models
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from trainer.lora import patch_pipe_with_lora
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from trainer.utils.val_prompts import val_prompts
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from trainer.utils.io import make_validation_img_grid
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from trainer.utils.utils import seed_everything, pick_best_gpu_id
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from trainer.utils.inference import encode_prompt_advanced
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from trainer.inference import encode_prompt_advanced
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def load_model(pretrained_model):
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if pretrained_model['version'] == "sd15":
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@@ -29,16 +30,16 @@ def load_model(pretrained_model):
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if __name__ == "__main__":
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pretrained_model = pretrained_models['sdxl']
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lora_path = 'lora_models/xander--07_19-19-35-sdxl_face_dora/checkpoints/checkpoint-360'
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lora_scales = np.linspace(0.4, 0.6, 3)
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render_size = (1024, 256+1024) # H,W
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lora_path = 'lora_models/lizzo--09_02-04-26-sdxl_object_lora_640_0.1_blip/checkpoints/checkpoint-500'
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lora_scales = np.linspace(0.5, 0.7, 3)
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render_size = (768, 768) # H,W
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n_imgs = 10
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n_loops = 4
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n_steps = 35
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guidance_scale = 7.5
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seed = 3
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use_lightning = 1
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seed = 2
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use_lightning = 0
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#####################################################################################
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@@ -70,27 +71,11 @@ if __name__ == "__main__":
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validation_prompts_raw = random.choices(val_prompts['object'], k=n_imgs)
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validation_prompts_raw = [
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'an elderly <concept>, old man',
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'a photo of <concept> as a young boy',
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'a painting of elderly <concept>, impressionism, stunning composition',
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'a painting of <concept> as a young kid, playing in the garden',
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'A digital illustration of <concept> as a child, exploring a mystical forest, vibrant colors',
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'An old-fashioned portrait of elderly <concept>, sitting in a cozy armchair, reading a book',
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'A watercolor painting of young <concept>, running through a meadow with a kite, bright and joyful',
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'A sketch of <concept> as a teenager, gazing at the stars, dreamy and contemplative',
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'A vintage photograph of elderly <concept>, wearing a classic hat, exuding wisdom and elegance',
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'A cartoon drawing of young <concept>, having a playful snowball fight, full of energy and laughter',
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'A surrealist painting of <concept> as a child, riding a fantastical creature, imaginative and whimsical',
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'A black and white photo of elderly <concept>, sitting on a park bench, reflecting on lifes journey',
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'A futuristic hologram of elderly <concept>, floating in a space station, surrounded by stars and galaxies'
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'A clay animation of baby <concept>, crawling in a magical garden with talking flowers and dancing insects',
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'An abstract painting of ancient <concept>, merging with the roots of an ancient tree, symbolizing wisdom and eternity',
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'A neon-lit digital art piece of toddler <concept>, playing with holographic toys in a cyberpunk playground',
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'A mosaic of centenarian <concept>, composed of thousands of tiny images from their life, telling a story of a century',
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'A pop art portrait of young <concept>, riding a colorful unicorn, surrounded by rainbows and candy clouds',
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'A steampunk illustration of elderly <concept>, inventing a time machine, surrounded by gears and steam',
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'A fantasy drawing of newborn <concept>, cradled in the arms of a gentle giant, in a land of giants and mythical creatures'
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"actress in TOK at a gala",
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"TOK, facy dinner party",
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"woman in TOK and jacket",
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"smiling woman in TOK at a party",
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"jennifer jones on TOK at music awards"
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]
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negative_prompt = "nude, naked, poorly drawn face, ugly, tiling, out of frame, extra limbs, disfigured, deformed body, blurry, blurred, watermark, text, grainy, signature, cut off, draft"
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@@ -103,8 +88,9 @@ if __name__ == "__main__":
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for jj in range(n_loops):
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for i in range(len(validation_prompts_raw)):
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for lora_scale in lora_scales:
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pipe = load_model(pretrained_model)
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pipe.unet = PeftModel.from_pretrained(model = pipe.unet, model_id = lora_path, adapter_name = 'eden_lora')
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seed += 1
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#pipe = load_model(pretrained_model)
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#pipe.unet = PeftModel.from_pretrained(model = pipe.unet, model_id = lora_path, adapter_name = 'eden_lora')
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pipe = patch_pipe_with_lora(pipe, lora_path, lora_scale=lora_scale)
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generator = torch.Generator(device='cuda').manual_seed(seed)
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