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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 |