Davids048andClaude Opus 5.5
f571621ae7
Every example calls VideoGenerator.generate with a nested request instead of generate_video keywords, and passes settings outside the from_pretrained convenience keywords through VideoGenerator.from_config at their typed paths. Each request and generator config equals what the keyword call built. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
88 lines
2.9 KiB
Python
88 lines
2.9 KiB
Python
from fastvideo import VideoGenerator
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from fastvideo.models.dits.matrixgame2.utils import create_action_presets
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import torch
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# Available variants: "base_distilled_model", "gta_distilled_model", "templerun_distilled_model"
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# Each variant has different keyboard_dim:
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# - base_distilled_model: keyboard_dim=4
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# - gta_distilled_model: keyboard_dim=2
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# - templerun_distilled_model: keyboard_dim=7 (keyboard only, no mouse)
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MODEL_VARIANT = "base_distilled_model"
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# Variant-specific settings
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VARIANT_CONFIG = {
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"base_distilled_model": {
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"model_path":
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"FastVideo/Matrix-Game-2.0-Base-Distilled-Diffusers",
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"keyboard_dim":
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4,
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"image_url":
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"https://raw.githubusercontent.com/SkyworkAI/Matrix-Game/main/Matrix-Game-2/demo_images/universal/0000.png",
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},
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"gta_distilled_model": {
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"model_path":
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"FastVideo/Matrix-Game-2.0-GTA-Distilled-Diffusers",
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"keyboard_dim":
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2,
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"image_url":
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"https://raw.githubusercontent.com/SkyworkAI/Matrix-Game/main/Matrix-Game-2/demo_images/gta_drive/0000.png",
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},
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"templerun_distilled_model": {
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"model_path":
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"FastVideo/Matrix-Game-2.0-TempleRun-Distilled-Diffusers",
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"keyboard_dim":
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7,
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"image_url":
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"https://raw.githubusercontent.com/SkyworkAI/Matrix-Game/main/Matrix-Game-2/demo_images/temple_run/0000.png",
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},
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}
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OUTPUT_PATH = "video_samples_matrixgame2"
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def main():
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# FastVideo will automatically use the optimal default arguments for the
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# model.
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# If a local path is provided, FastVideo will make a best effort
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# attempt to identify the optimal arguments.
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config = VARIANT_CONFIG[MODEL_VARIANT]
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generator = VideoGenerator.from_pretrained(
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config["model_path"],
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# FastVideo will automatically handle distributed setup
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num_gpus=1,
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use_fsdp_inference=False, # set to True if GPU is out of memory
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dit_cpu_offload=True, # DiT need to be offloaded for MoE
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vae_cpu_offload=False,
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text_encoder_cpu_offload=True,
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# Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
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pin_cpu_memory=True,
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# image_encoder_cpu_offload=False,
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)
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num_frames = 597
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actions = create_action_presets(num_frames, keyboard_dim=config["keyboard_dim"])
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grid_sizes = torch.tensor([150, 44, 80])
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generator.generate({
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"prompt": "",
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"inputs": {
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"image_path": config["image_url"],
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"mouse_cond": actions["mouse"].unsqueeze(0),
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"keyboard_cond": actions["keyboard"].unsqueeze(0),
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"grid_sizes": grid_sizes,
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},
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"sampling": {
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"num_frames": num_frames,
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"height": 352,
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"width": 640,
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"num_inference_steps": 50,
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},
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"output": {"output_path": OUTPUT_PATH, "save_video": True},
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})
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if __name__ == "__main__":
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main()
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