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Running
on
T4
| CUDA_VISIBLE_DEVICES=0 python -m diffusion.train_diffusion \ | |
| trainer.evaluate=true \ | |
| trainer.batch_size=1000 \ | |
| trainer.gpu=1 \ | |
| trainer.test_output_dir=./outputs/unconditional/ \ | |
| trainer.resume_from_checkpoint=./ckpt/Diffusion_uncond_1100k.ckpt \ | |
| trainer.num_worker=2 \ | |
| trainer.accelerator="32-true" \ | |
| trainer.exp_name=test \ | |
| dataset.name=Dummy_dataset \ | |
| dataset.length=5000 \ | |
| dataset.num_max_faces=30 \ | |
| dataset.condition=None \ | |
| model.name=Diffusion_condition \ | |
| model.autoencoder_weights=./ckpt/AE_deepcad_1100k.ckpt \ | |
| model.autoencoder=AutoEncoder_1119_light \ | |
| model.with_intersection=true \ | |
| model.in_channels=6 \ | |
| model.dim_shape=768 \ | |
| model.dim_latent=8 \ | |
| model.gaussian_weights=1e-6 \ | |
| model.pad_method=random \ | |
| model.diffusion_latent=768 \ | |
| model.diffusion_type=epsilon \ | |
| model.gaussian_weights=1e-6 \ | |
| model.condition=None \ | |
| model.num_max_faces=30 \ | |
| model.beta_schedule=linear \ | |
| model.addition_tag=false \ | |
| model.name=Diffusion_condition | |
| python -m construct_brep \ | |
| --data_root ./outputs/unconditional \ | |
| --out_root ./outputs/unconditional_post \ | |
| --use_ray \ | |
| --num_cpus 24 \ | |
| --drop_num 3 \ | |
| --from_scratch |