wenjian
872011d8f1
- Add ComfyUI custom nodes: model loader, t2v, i2v, v2v - Fix kernels import: move to try block for graceful fallback when not installed - Fix diffusers compatibility: add fallback imports for HeliosLoraLoaderMixin, HeliosTransformer3DModel, HeliosScheduler, and apply_lora_scale - Fix infer_helios: cast num_blocks_per_group to int, add low_cpu_mem_usage - Add rh_config.json, model index compat, and deployment scripts Made-with: Cursor
81 lines
3.1 KiB
Python
81 lines
3.1 KiB
Python
import torch
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from .utils import (
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comfyui_images_to_pil_list,
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estimate_total_steps,
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helios_output_to_video,
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make_progress_callback,
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parse_pyramid_steps,
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)
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class RunningHubHeliosV2V:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"helios_pipe": ("HELIOS_PIPE",),
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"video_frames": ("IMAGE",),
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"prompt": ("STRING", {"default": "", "multiline": True}),
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"width": ("INT", {"default": 640, "min": 128, "max": 1920, "step": 16}),
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"height": ("INT", {"default": 384, "min": 128, "max": 1088, "step": 16}),
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"num_frames": ("INT", {"default": 99, "min": 1, "max": 480, "step": 1}),
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"num_inference_steps": ("INT", {"default": 50, "min": 1, "max": 200, "step": 1}),
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"guidance_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 20.0, "step": 0.1}),
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"seed": ("INT", {"default": 42, "min": 0, "max": 0xFFFFFFFF}),
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"is_enable_stage2": ("BOOLEAN", {"default": True}),
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"pyramid_steps": ("STRING", {"default": "2,2,2"}),
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"is_amplify_first_chunk": ("BOOLEAN", {"default": True}),
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},
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"optional": {
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"negative_prompt": ("STRING", {"default": "", "multiline": True}),
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},
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}
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RETURN_TYPES = ("VIDEO",)
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RETURN_NAMES = ("video",)
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FUNCTION = "generate"
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CATEGORY = "RunningHub/Helios"
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def generate(self, helios_pipe, video_frames, prompt, width, height, num_frames,
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num_inference_steps, guidance_scale, seed,
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is_enable_stage2, pyramid_steps, is_amplify_first_chunk,
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negative_prompt=""):
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pipe = helios_pipe
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pyramid_list = parse_pyramid_steps(pyramid_steps)
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total_steps = estimate_total_steps(
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num_frames, num_inference_steps, is_enable_stage2,
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pyramid_list, is_amplify_first_chunk,
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)
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progress_callback = make_progress_callback(total_steps)
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pil_frames = comfyui_images_to_pil_list(video_frames)
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with torch.no_grad():
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output = pipe(
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prompt=prompt,
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negative_prompt=negative_prompt if negative_prompt else None,
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height=height,
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width=width,
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num_frames=num_frames,
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num_inference_steps=num_inference_steps,
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guidance_scale=guidance_scale,
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generator=torch.Generator(device="cuda").manual_seed(seed),
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history_sizes=[16, 2, 1],
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num_latent_frames_per_chunk=9,
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keep_first_frame=True,
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is_enable_stage2=is_enable_stage2,
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pyramid_num_inference_steps_list=pyramid_list,
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is_skip_first_chunk=False,
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is_amplify_first_chunk=is_amplify_first_chunk,
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use_zero_init=False,
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zero_steps=1,
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image=None,
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video=pil_frames,
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callback_on_step_end=progress_callback,
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)
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video = helios_output_to_video(output)
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return (video,)
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