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Merge pull request #411 from glide-the/diffuser_params

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Add new command line arguments for LoRA weights and prompt
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Yuxuan.Zhang 2024-10-14 20:11:49 +08:00 committed by GitHub
commit 6a16207321
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1 changed files with 23 additions and 5 deletions
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28
tools/load_cogvideox_lora.py
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@ -57,6 +57,23 @@ def get_args():
The formula for lora_scale is: lora_r / alpha.
""",
)
parser.add_argument(
"--lora_alpha",
type=int,
default=1,
help="""LoRA weights have a rank parameter, with the default for 2B trans set at 128 and 5B trans set at 256.
This part is used to calculate the value for lora_scale, which is by default divided by the alpha value,
used for stable learning and to prevent underflow. In the SAT training framework,
alpha is set to 1 by default. The higher the rank, the better the expressive capability,
but it requires more memory and training time. Increasing this number blindly isn't always better.
The formula for lora_scale is: lora_r / alpha.
""",
)
parser.add_argument(
"--prompt",
type=str,
help="prompt",
)
parser.add_argument(
"--output_dir",
type=str,
@ -69,17 +86,18 @@ def get_args():
if __name__ == "__main__":
args = get_args()
pipe = CogVideoXPipeline.from_pretrained(args.pretrained_model_name_or_path, torch_dtype=torch.bfloat16).to(device)
pipe.load_lora_weights(args.lora_weights_path, weight_name="pytorch_lora_weights.safetensors", adapter_name="test_1")
pipe.fuse_lora(lora_scale=1/128)
pipe.load_lora_weights(args.lora_weights_path, weight_name="pytorch_lora_weights.safetensors", adapter_name="cogvideox-lora")
# pipe.fuse_lora(lora_scale=args.lora_alpha/args.lora_r, ['transformer'])
lora_scaling=args.lora_alpha/args.lora_r
pipe.set_adapters(["cogvideox-lora"], [lora_scaling])
pipe.scheduler = CogVideoXDPMScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
os.makedirs(args.output_dir, exist_ok=True)
prompt="""In the heart of a bustling city, a young woman with long, flowing brown hair and a radiant smile stands out. She's donned in a cozy white beanie adorned with playful animal ears, adding a touch of whimsy to her appearance. Her eyes sparkle with joy as she looks directly into the camera, her expression inviting and warm. The background is a blur of activity, with indistinct figures moving about, suggesting a lively public space. The lighting is soft and diffused, casting a gentle glow on her face and highlighting her features. The overall mood is cheerful and vibrant, capturing a moment of happiness in the midst of urban life.
"""
latents = pipe(
prompt=prompt,
prompt=args.prompt,
num_videos_per_prompt=1,
num_inference_steps=50,
num_frames=49,