mirror of
https://github.com/modelscope/DiffSynth-Studio.git
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support training for eligen and nexusgen
This commit is contained in:
mi804
@@ -96,12 +96,12 @@ image.save("image.jpg")
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|[FLUX.1-dev-Controlnet-Upscaler](https://www.modelscope.cn/models/jasperai/Flux.1-dev-Controlnet-Upscaler)|`controlnet_inputs`|[code](./examples/flux/model_inference/FLUX.1-dev-Controlnet-Upscaler.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-Controlnet-Upscaler.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-Controlnet-Upscaler.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-Controlnet-Upscaler.py)|[code](./examples/flux/model_training/lora/FLUX.1-dev-Controlnet-Upscaler.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-Controlnet-Upscaler.py)|
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|[FLUX.1-dev-IP-Adapter](https://www.modelscope.cn/models/InstantX/FLUX.1-dev-IP-Adapter)|`ipadapter_images`, `ipadapter_scale`|[code](./examples/flux/model_inference/FLUX.1-dev-IP-Adapter.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-IP-Adapter.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-IP-Adapter.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-IP-Adapter.py)|[code](./examples/flux/model_training/lora/FLUX.1-dev-IP-Adapter.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-IP-Adapter.py)|
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|[FLUX.1-dev-InfiniteYou](https://www.modelscope.cn/models/ByteDance/InfiniteYou)|`infinityou_id_image`, `infinityou_guidance`, `controlnet_inputs`|[code](./examples/flux/model_inference/FLUX.1-dev-InfiniteYou.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-InfiniteYou.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-InfiniteYou.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-InfiniteYou.py)|[code](./examples/flux/model_training/lora/FLUX.1-dev-InfiniteYou.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-InfiniteYou.py)|
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|[FLUX.1-dev-EliGen](https://www.modelscope.cn/models/DiffSynth-Studio/Eligen)|`eligen_entity_prompts`, `eligen_entity_masks`, `eligen_enable_on_negative`, `eligen_enable_inpaint`|[code](./examples/flux/model_inference/FLUX.1-dev-EliGen.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-EliGen.py)|-|-|||
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|[FLUX.1-dev-EliGen](https://www.modelscope.cn/models/DiffSynth-Studio/Eligen)|`eligen_entity_prompts`, `eligen_entity_masks`, `eligen_enable_on_negative`, `eligen_enable_inpaint`|[code](./examples/flux/model_inference/FLUX.1-dev-EliGen.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-EliGen.py)|-|-|[code](./examples/flux/model_training/lora/FLUX.1-dev-EliGen.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-EliGen.py)|
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|[FLUX.1-dev-LoRA-Encoder](https://www.modelscope.cn/models/DiffSynth-Studio/LoRA-Encoder-FLUX.1-Dev)|`lora_encoder_inputs`, `lora_encoder_scale`|[code](./examples/flux/model_inference/FLUX.1-dev-LoRA-Encoder.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-LoRA-Encoder.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-LoRA-Encoder.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-LoRA-Encoder.py)|-|-|
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|[FLUX.1-dev-LoRA-Fusion-Preview](https://modelscope.cn/models/DiffSynth-Studio/LoRAFusion-preview-FLUX.1-dev)||[code](./examples/flux/model_inference/FLUX.1-dev-LoRA-Fusion.py)|-|-|-|-|-|
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|[Step1X-Edit](https://www.modelscope.cn/models/stepfun-ai/Step1X-Edit)|`step1x_reference_image`|[code](./examples/flux/model_inference/Step1X-Edit.py)|[code](./examples/flux/model_inference_low_vram/Step1X-Edit.py)|[code](./examples/flux/model_training/full/Step1X-Edit.sh)|[code](./examples/flux/model_training/validate_full/Step1X-Edit.py)|[code](./examples/flux/model_training/lora/Step1X-Edit.sh)|[code](./examples/flux/model_training/validate_lora/Step1X-Edit.py)|
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|[FLEX.2-preview](https://www.modelscope.cn/models/ostris/Flex.2-preview)|`flex_inpaint_image`, `flex_inpaint_mask`, `flex_control_image`, `flex_control_strength`, `flex_control_stop`|[code](./examples/flux/model_inference/FLEX.2-preview.py)|[code](./examples/flux/model_inference_low_vram/FLEX.2-preview.py)|[code](./examples/flux/model_training/full/FLEX.2-preview.sh)|[code](./examples/flux/model_training/validate_full/FLEX.2-preview.py)|[code](./examples/flux/model_training/lora/FLEX.2-preview.sh)|[code](./examples/flux/model_training/validate_lora/FLEX.2-preview.py)|
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|[Nexus-Gen-Edit](https://www.modelscope.cn/models/DiffSynth-Studio/Nexus-GenV2)|`nexus_gen_reference_image`|[code](./examples/flux/model_inference/Nexus-Gen-Editing.py)|[code](./examples/flux/model_inference_low_vram/Nexus-Gen-Editing.py)|[code](./examples/flux/model_training/full/FLUX.1-NexusGen-Edit.sh)|[code](./examples/flux/model_training/validate_full/Nexus-Gen-Editing.py)|[code](./examples/flux/model_training/lora/FLUX.1-NexusGen-Edit.sh)|[code](./examples/flux/model_training/validate_lora/Nexus-Gen-Editing.py)|
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</details>
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@@ -98,12 +98,12 @@ image.save("image.jpg")
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|[FLUX.1-dev-Controlnet-Upscaler](https://www.modelscope.cn/models/jasperai/Flux.1-dev-Controlnet-Upscaler)|`controlnet_inputs`|[code](./examples/flux/model_inference/FLUX.1-dev-Controlnet-Upscaler.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-Controlnet-Upscaler.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-Controlnet-Upscaler.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-Controlnet-Upscaler.py)|[code](./examples/flux/model_training/lora/FLUX.1-dev-Controlnet-Upscaler.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-Controlnet-Upscaler.py)|
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|[FLUX.1-dev-IP-Adapter](https://www.modelscope.cn/models/InstantX/FLUX.1-dev-IP-Adapter)|`ipadapter_images`, `ipadapter_scale`|[code](./examples/flux/model_inference/FLUX.1-dev-IP-Adapter.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-IP-Adapter.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-IP-Adapter.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-IP-Adapter.py)|[code](./examples/flux/model_training/lora/FLUX.1-dev-IP-Adapter.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-IP-Adapter.py)|
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|[FLUX.1-dev-InfiniteYou](https://www.modelscope.cn/models/ByteDance/InfiniteYou)|`infinityou_id_image`, `infinityou_guidance`, `controlnet_inputs`|[code](./examples/flux/model_inference/FLUX.1-dev-InfiniteYou.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-InfiniteYou.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-InfiniteYou.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-InfiniteYou.py)|[code](./examples/flux/model_training/lora/FLUX.1-dev-InfiniteYou.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-InfiniteYou.py)|
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|[FLUX.1-dev-EliGen](https://www.modelscope.cn/models/DiffSynth-Studio/Eligen)|`eligen_entity_prompts`, `eligen_entity_masks`, `eligen_enable_on_negative`, `eligen_enable_inpaint`|[code](./examples/flux/model_inference/FLUX.1-dev-EliGen.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-EliGen.py)|-|-|||
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|[FLUX.1-dev-EliGen](https://www.modelscope.cn/models/DiffSynth-Studio/Eligen)|`eligen_entity_prompts`, `eligen_entity_masks`, `eligen_enable_on_negative`, `eligen_enable_inpaint`|[code](./examples/flux/model_inference/FLUX.1-dev-EliGen.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-EliGen.py)|-|-|[code](./examples/flux/model_training/lora/FLUX.1-dev-EliGen.sh)|[code](./examples/flux/model_training/validate_lora/FLUX.1-dev-EliGen.py)|
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|[FLUX.1-dev-LoRA-Encoder](https://www.modelscope.cn/models/DiffSynth-Studio/LoRA-Encoder-FLUX.1-Dev)|`lora_encoder_inputs`, `lora_encoder_scale`|[code](./examples/flux/model_inference/FLUX.1-dev-LoRA-Encoder.py)|[code](./examples/flux/model_inference_low_vram/FLUX.1-dev-LoRA-Encoder.py)|[code](./examples/flux/model_training/full/FLUX.1-dev-LoRA-Encoder.sh)|[code](./examples/flux/model_training/validate_full/FLUX.1-dev-LoRA-Encoder.py)|-|-|
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|[FLUX.1-dev-LoRA-Fusion-Preview](https://modelscope.cn/models/DiffSynth-Studio/LoRAFusion-preview-FLUX.1-dev)||[code](./examples/flux/model_inference/FLUX.1-dev-LoRA-Fusion.py)|-|-|-|-|-|
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|[Step1X-Edit](https://www.modelscope.cn/models/stepfun-ai/Step1X-Edit)|`step1x_reference_image`|[code](./examples/flux/model_inference/Step1X-Edit.py)|[code](./examples/flux/model_inference_low_vram/Step1X-Edit.py)|[code](./examples/flux/model_training/full/Step1X-Edit.sh)|[code](./examples/flux/model_training/validate_full/Step1X-Edit.py)|[code](./examples/flux/model_training/lora/Step1X-Edit.sh)|[code](./examples/flux/model_training/validate_lora/Step1X-Edit.py)|
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|[FLEX.2-preview](https://www.modelscope.cn/models/ostris/Flex.2-preview)|`flex_inpaint_image`, `flex_inpaint_mask`, `flex_control_image`, `flex_control_strength`, `flex_control_stop`|[code](./examples/flux/model_inference/FLEX.2-preview.py)|[code](./examples/flux/model_inference_low_vram/FLEX.2-preview.py)|[code](./examples/flux/model_training/full/FLEX.2-preview.sh)|[code](./examples/flux/model_training/validate_full/FLEX.2-preview.py)|[code](./examples/flux/model_training/lora/FLEX.2-preview.sh)|[code](./examples/flux/model_training/validate_lora/FLEX.2-preview.py)|
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|[Nexus-Gen-Edit](https://www.modelscope.cn/models/DiffSynth-Studio/Nexus-GenV2)|`nexus_gen_reference_image`|[code](./examples/flux/model_inference/Nexus-Gen-Editing.py)|[code](./examples/flux/model_inference_low_vram/Nexus-Gen-Editing.py)|[code](./examples/flux/model_training/full/FLUX.1-NexusGen-Edit.sh)|[code](./examples/flux/model_training/validate_full/Nexus-Gen-Editing.py)|[code](./examples/flux/model_training/lora/FLUX.1-NexusGen-Edit.sh)|[code](./examples/flux/model_training/validate_lora/Nexus-Gen-Editing.py)|
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</details>
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### Wan 系列
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@@ -14,7 +14,7 @@ class NexusGenAutoregressiveModel(torch.nn.Module):
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self.model = Qwen2_5_VLForConditionalGeneration(model_config)
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self.processor = Qwen2_5_VLProcessor.from_pretrained(model_path)
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@staticmethod
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def state_dict_converter():
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return NexusGenAutoregressiveModelStateDictConverter()
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@@ -34,6 +34,7 @@ class NexusGenAutoregressiveModel(torch.nn.Module):
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return messages
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def get_generation_msg(self, instruction):
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instruction = "Generate an image according to the following description: {}".format(instruction)
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messages = [{"role":"user", "content":instruction}, {"role":"assistant", "content":"Here is an image based on the description: <image>"}]
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return messages
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@@ -80,9 +81,10 @@ class NexusGenAutoregressiveModel(torch.nn.Module):
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)
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input_embeds = input_embeds.masked_scatter(gt_image_mask.unsqueeze(-1).expand_as(input_embeds), image_prefill_embeds)
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position_ids, _ = model.get_rope_index(inputs['input_ids'],
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inputs['image_grid_thw'],
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attention_mask=inputs['attention_mask'])
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position_ids, _ = model.get_rope_index(
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inputs['input_ids'],
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inputs['image_grid_thw'],
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attention_mask=inputs['attention_mask'])
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position_ids = position_ids.contiguous()
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outputs = model(inputs_embeds=input_embeds, position_ids=position_ids, attention_mask=inputs['attention_mask'], return_dict=True)
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output_image_embeddings = outputs.image_embeddings[:, :-1, :]
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@@ -97,4 +99,3 @@ class NexusGenAutoregressiveModelStateDictConverter:
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def from_civitai(self, state_dict):
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state_dict = {"model." + key: value for key, value in state_dict.items()}
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return state_dict
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@@ -767,9 +767,10 @@ class FluxImageUnit_EntityControl(PipelineUnit):
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if eligen_entity_prompts is None or eligen_entity_masks is None:
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return inputs_shared, inputs_posi, inputs_nega
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pipe.load_models_to_device(self.onload_model_names)
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eligen_enable_on_negative = inputs_shared.get("eligen_enable_on_negative", False)
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eligen_kwargs_posi, eligen_kwargs_nega = self.prepare_eligen(pipe, inputs_nega,
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eligen_entity_prompts, eligen_entity_masks, inputs_shared["width"], inputs_shared["height"],
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inputs_shared["t5_sequence_length"], inputs_shared["eligen_enable_on_negative"], inputs_shared["cfg_scale"])
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inputs_shared["t5_sequence_length"], eligen_enable_on_negative, inputs_shared["cfg_scale"])
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inputs_posi.update(eligen_kwargs_posi)
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if inputs_shared.get("cfg_scale", 1.0) != 1.0:
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inputs_nega.update(eligen_kwargs_nega)
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@@ -120,8 +120,13 @@ class ImageDataset(torch.utils.data.Dataset):
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data = self.data[data_id % len(self.data)].copy()
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for key in self.data_file_keys:
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if key in data:
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path = os.path.join(self.base_path, data[key])
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data[key] = self.load_data(path)
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if isinstance(data[key], list):
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print(f"Loading multiple files for key '{key}'.")
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path = [os.path.join(self.base_path, p) for p in data[key]]
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data[key] = [self.load_data(p) for p in path]
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else:
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path = os.path.join(self.base_path, data[key])
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data[key] = self.load_data(path)
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if data[key] is None:
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warnings.warn(f"cannot load file {data[key]}.")
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return None
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@@ -2,7 +2,7 @@ import importlib
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import torch
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from PIL import Image
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from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
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from modelscope import snapshot_download
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from modelscope import snapshot_download, dataset_snapshot_download
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if importlib.util.find_spec("transformers") is None:
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raise ImportError("You are using Nexus-GenV2. It depends on transformers, which is not installed. Please install it with `pip install transformers==4.49.0`.")
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@@ -23,12 +23,13 @@ pipe = FluxImagePipeline.from_pretrained(
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],
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)
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prompt = "给猫加一副太阳镜"
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ref_image = Image.open("cat.png").convert("RGB")
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dataset_snapshot_download(dataset_id="DiffSynth-Studio/examples_in_diffsynth", local_dir="./", allow_file_pattern=f"data/examples/nexusgen/cat.jpg")
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ref_image = Image.open("data/examples/nexusgen/cat.jpg").convert("RGB")
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prompt = "Add a crown."
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image = pipe(
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prompt=prompt, negative_prompt="",
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seed=0, cfg_scale=1.0, num_inference_steps=50,
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seed=42, cfg_scale=2.0, num_inference_steps=50,
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nexus_gen_reference_image=ref_image,
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height=512, width=512,
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)
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image.save("cat_glasses.jpg")
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image.save("cat_crown.jpg")
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36
examples/flux/model_inference_low_vram/Nexus-Gen-Editing.py
Normal file
36
examples/flux/model_inference_low_vram/Nexus-Gen-Editing.py
Normal file
@@ -0,0 +1,36 @@
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import importlib
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import torch
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from PIL import Image
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from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
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from modelscope import snapshot_download, dataset_snapshot_download
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if importlib.util.find_spec("transformers") is None:
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raise ImportError("You are using Nexus-GenV2. It depends on transformers, which is not installed. Please install it with `pip install transformers==4.49.0`.")
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else:
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import transformers
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assert transformers.__version__ == "4.49.0", "Nexus-GenV2 requires transformers==4.49.0, please install it with `pip install transformers==4.49.0`."
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snapshot_download("DiffSynth-Studio/Nexus-GenV2", local_dir="models/DiffSynth-Studio/Nexus-GenV2")
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pipe = FluxImagePipeline.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="DiffSynth-Studio/Nexus-GenV2", origin_file_pattern="model*.safetensors"),
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ModelConfig(model_id="DiffSynth-Studio/Nexus-GenV2", origin_file_pattern="edit_decoder.bin"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
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],
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)
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pipe.enable_vram_management()
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dataset_snapshot_download(dataset_id="DiffSynth-Studio/examples_in_diffsynth", local_dir="./", allow_file_pattern=f"data/examples/nexusgen/cat.jpg")
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ref_image = Image.open("data/examples/nexusgen/cat.jpg").convert("RGB")
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prompt = "Add a crown."
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image = pipe(
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prompt=prompt, negative_prompt="",
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seed=42, cfg_scale=2.0, num_inference_steps=50,
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nexus_gen_reference_image=ref_image,
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height=512, width=512,
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)
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image.save("cat_crown.jpg")
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14
examples/flux/model_training/full/FLUX.1-NexusGen-Edit.sh
Normal file
14
examples/flux/model_training/full/FLUX.1-NexusGen-Edit.sh
Normal file
@@ -0,0 +1,14 @@
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accelerate launch --config_file examples/flux/model_training/full/accelerate_config_zero2offload.yaml examples/flux/model_training/train.py \
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--dataset_base_path data/example_image_dataset \
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--dataset_metadata_path data/example_image_dataset/metadata_nexusgen_edit.csv \
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--data_file_keys "image,nexus_gen_reference_image" \
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--max_pixels 262144 \
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--dataset_repeat 400 \
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--model_id_with_origin_paths "DiffSynth-Studio/Nexus-GenV2:model*.safetensors,DiffSynth-Studio/Nexus-GenV2:edit_decoder.bin,black-forest-labs/FLUX.1-dev:text_encoder/model.safetensors,black-forest-labs/FLUX.1-dev:text_encoder_2/,black-forest-labs/FLUX.1-dev:ae.safetensors" \
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--learning_rate 1e-5 \
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--num_epochs 1 \
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/FLUX.1-NexusGen-Edit_full" \
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--trainable_models "dit" \
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--extra_inputs "nexus_gen_reference_image" \
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--use_gradient_checkpointing_offload
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@@ -0,0 +1,22 @@
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compute_environment: LOCAL_MACHINE
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debug: false
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deepspeed_config:
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gradient_accumulation_steps: 1
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offload_optimizer_device: 'cpu'
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offload_param_device: 'cpu'
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zero3_init_flag: false
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zero_stage: 2
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distributed_type: DEEPSPEED
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downcast_bf16: 'no'
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enable_cpu_affinity: false
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machine_rank: 0
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main_training_function: main
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mixed_precision: bf16
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num_machines: 1
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num_processes: 8
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rdzv_backend: static
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same_network: true
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tpu_env: []
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tpu_use_cluster: false
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tpu_use_sudo: false
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use_cpu: false
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||||
17
examples/flux/model_training/lora/FLUX.1-NexusGen-Edit.sh
Normal file
17
examples/flux/model_training/lora/FLUX.1-NexusGen-Edit.sh
Normal file
@@ -0,0 +1,17 @@
|
||||
accelerate launch examples/flux/model_training/train.py \
|
||||
--dataset_base_path data/example_image_dataset \
|
||||
--dataset_metadata_path data/example_image_dataset/metadata_nexusgen_edit.csv \
|
||||
--data_file_keys "image,nexus_gen_reference_image" \
|
||||
--max_pixels 1048576 \
|
||||
--dataset_repeat 400 \
|
||||
--model_id_with_origin_paths "DiffSynth-Studio/Nexus-GenV2:model*.safetensors,DiffSynth-Studio/Nexus-GenV2:edit_decoder.bin,black-forest-labs/FLUX.1-dev:text_encoder/model.safetensors,black-forest-labs/FLUX.1-dev:text_encoder_2/,black-forest-labs/FLUX.1-dev:ae.safetensors" \
|
||||
--learning_rate 1e-4 \
|
||||
--num_epochs 5 \
|
||||
--remove_prefix_in_ckpt "pipe.dit." \
|
||||
--output_path "./models/train/FLUX.1-NexusGen-Edit_lora" \
|
||||
--lora_base_model "dit" \
|
||||
--lora_target_modules "a_to_qkv,b_to_qkv,ff_a.0,ff_a.2,ff_b.0,ff_b.2,a_to_out,b_to_out,proj_out,norm.linear,norm1_a.linear,norm1_b.linear,to_qkv_mlp" \
|
||||
--lora_rank 32 \
|
||||
--align_to_opensource_format \
|
||||
--extra_inputs "nexus_gen_reference_image" \
|
||||
--use_gradient_checkpointing
|
||||
17
examples/flux/model_training/lora/FLUX.1-dev-EliGen.sh
Normal file
17
examples/flux/model_training/lora/FLUX.1-dev-EliGen.sh
Normal file
@@ -0,0 +1,17 @@
|
||||
accelerate launch examples/flux/model_training/train.py \
|
||||
--dataset_base_path data/example_image_dataset \
|
||||
--dataset_metadata_path data/example_image_dataset/metadata_eligen.json \
|
||||
--data_file_keys "image,eligen_entity_masks" \
|
||||
--max_pixels 1048576 \
|
||||
--dataset_repeat 50 \
|
||||
--model_id_with_origin_paths "black-forest-labs/FLUX.1-dev:flux1-dev.safetensors,black-forest-labs/FLUX.1-dev:text_encoder/model.safetensors,black-forest-labs/FLUX.1-dev:text_encoder_2/,black-forest-labs/FLUX.1-dev:ae.safetensors" \
|
||||
--learning_rate 1e-4 \
|
||||
--num_epochs 5 \
|
||||
--remove_prefix_in_ckpt "pipe.dit." \
|
||||
--output_path "./models/train/FLUX.1-dev-EliGen_lora" \
|
||||
--lora_base_model "dit" \
|
||||
--lora_target_modules "a_to_qkv,b_to_qkv,ff_a.0,ff_a.2,ff_b.0,ff_b.2,a_to_out,b_to_out,proj_out,norm.linear,norm1_a.linear,norm1_b.linear,to_qkv_mlp" \
|
||||
--lora_rank 32 \
|
||||
--align_to_opensource_format \
|
||||
--extra_inputs "eligen_entity_masks,eligen_entity_prompts" \
|
||||
--use_gradient_checkpointing
|
||||
@@ -0,0 +1,28 @@
|
||||
import torch
|
||||
from PIL import Image
|
||||
from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
|
||||
from diffsynth import load_state_dict
|
||||
|
||||
pipe = FluxImagePipeline.from_pretrained(
|
||||
torch_dtype=torch.bfloat16,
|
||||
device="cuda",
|
||||
model_configs=[
|
||||
ModelConfig(model_id="DiffSynth-Studio/Nexus-GenV2", origin_file_pattern="model*.safetensors"),
|
||||
ModelConfig(model_id="DiffSynth-Studio/Nexus-GenV2", origin_file_pattern="edit_decoder.bin"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
|
||||
],
|
||||
)
|
||||
state_dict = load_state_dict("models/train/FLUX.1-NexusGen-Edit_full/epoch-0.safetensors")
|
||||
pipe.dit.load_state_dict(state_dict)
|
||||
|
||||
ref_image = Image.open("data/example_image_dataset/nexus_gen/image_1.png").convert("RGB")
|
||||
prompt = "Add a pair of sunglasses."
|
||||
image = pipe(
|
||||
prompt=prompt, negative_prompt="",
|
||||
seed=42, cfg_scale=2.0, num_inference_steps=50,
|
||||
nexus_gen_reference_image=ref_image,
|
||||
height=512, width=512,
|
||||
)
|
||||
image.save("NexusGen-Edit_full.jpg")
|
||||
@@ -0,0 +1,33 @@
|
||||
import torch
|
||||
from PIL import Image
|
||||
from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
|
||||
|
||||
pipe = FluxImagePipeline.from_pretrained(
|
||||
torch_dtype=torch.bfloat16,
|
||||
device="cuda",
|
||||
model_configs=[
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="flux1-dev.safetensors"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
|
||||
],
|
||||
)
|
||||
|
||||
pipe.load_lora(pipe.dit, "models/train/FLUX.1-dev-EliGen_lora/epoch-4.safetensors", alpha=1)
|
||||
|
||||
entity_prompts = ["A beautiful girl", "sign 'Entity Control'", "shorts", "shirt"]
|
||||
global_prompt = "A beautiful girl wearing shirt and shorts in the street, holding a sign 'Entity Control'"
|
||||
masks = [Image.open(f"data/example_image_dataset/eligen/{i}.png").convert('RGB') for i in range(len(entity_prompts))]
|
||||
# generate image
|
||||
image = pipe(
|
||||
prompt=global_prompt,
|
||||
cfg_scale=1.0,
|
||||
num_inference_steps=50,
|
||||
embedded_guidance=3.5,
|
||||
seed=42,
|
||||
height=1024,
|
||||
width=1024,
|
||||
eligen_entity_prompts=entity_prompts,
|
||||
eligen_entity_masks=masks,
|
||||
)
|
||||
image.save(f"EliGen_lora.png")
|
||||
@@ -0,0 +1,26 @@
|
||||
import torch
|
||||
from PIL import Image
|
||||
from diffsynth.pipelines.flux_image_new import FluxImagePipeline, ModelConfig
|
||||
|
||||
pipe = FluxImagePipeline.from_pretrained(
|
||||
torch_dtype=torch.bfloat16,
|
||||
device="cuda",
|
||||
model_configs=[
|
||||
ModelConfig(model_id="DiffSynth-Studio/Nexus-GenV2", origin_file_pattern="model*.safetensors"),
|
||||
ModelConfig(model_id="DiffSynth-Studio/Nexus-GenV2", origin_file_pattern="edit_decoder.bin"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/"),
|
||||
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
|
||||
],
|
||||
)
|
||||
pipe.load_lora(pipe.dit, "models/train/FLUX.1-NexusGen-Edit_lora/epoch-4.safetensors", alpha=1)
|
||||
|
||||
ref_image = Image.open("data/example_image_dataset/nexus_gen/image_1.png").convert("RGB")
|
||||
prompt = "Add a pair of sunglasses."
|
||||
image = pipe(
|
||||
prompt=prompt, negative_prompt="",
|
||||
seed=42, cfg_scale=1.0, num_inference_steps=50,
|
||||
nexus_gen_reference_image=ref_image,
|
||||
height=512, width=512,
|
||||
)
|
||||
image.save("NexusGen-Edit_lora.jpg")
|
||||
Reference in New Issue
Block a user