mirror of
https://github.com/modelscope/DiffSynth-Studio.git
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67 lines
2.4 KiB
Python
67 lines
2.4 KiB
Python
from diffsynth.diffusion.template import TemplatePipeline
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from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
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import torch
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from modelscope import dataset_snapshot_download
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from PIL import Image
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vram_config = {
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"offload_dtype": "disk",
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"offload_device": "disk",
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"onload_dtype": torch.float8_e4m3fn,
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"onload_device": "cpu",
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"preparing_dtype": torch.float8_e4m3fn,
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"preparing_device": "cuda",
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"computation_dtype": torch.bfloat16,
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"computation_device": "cuda",
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}
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pipe = Flux2ImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors", **vram_config),
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ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors", **vram_config),
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ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
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],
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tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
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vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
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)
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template = TemplatePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Upscaler")],
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lazy_loading=True,
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)
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dataset_snapshot_download(
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"DiffSynth-Studio/examples_in_diffsynth",
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allow_file_pattern=["templates/*"],
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local_dir="data/examples",
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)
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image = template(
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pipe,
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prompt="A cat is sitting on a stone.",
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seed=0, cfg_scale=4, num_inference_steps=50,
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template_inputs = [{
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"image": Image.open("data/examples/templates/image_lowres_512.jpg"),
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"prompt": "A cat is sitting on a stone.",
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}],
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negative_template_inputs = [{
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"image": Image.open("data/examples/templates/image_lowres_512.jpg"),
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"prompt": "",
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}],
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)
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image.save("image_Upscaler_1.png")
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image = template(
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pipe,
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prompt="A cat is sitting on a stone.",
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seed=0, cfg_scale=4, num_inference_steps=50,
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template_inputs = [{
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"image": Image.open("data/examples/templates/image_lowres_100.jpg"),
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"prompt": "A cat is sitting on a stone.",
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}],
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negative_template_inputs = [{
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"image": Image.open("data/examples/templates/image_lowres_100.jpg"),
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"prompt": "",
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}],
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)
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image.save("image_Upscaler_2.png")
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