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clean code
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Wuziyi616 committed Oct 3, 2022
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1 change: 1 addition & 0 deletions .gitignore
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data/
example_data/
checkpoint/
wandb/
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5 changes: 5 additions & 0 deletions README.md
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Expand Up @@ -37,6 +37,11 @@ You can train, test and visualize the results using our provided config files, o
We explain our code design in [tutorial.md](docs/tutorial.md).
Please read it before modifying the codebase or implementing your new algorithms.

## Benchmark

We benchmark the baselines and report them in [model.md](docs/model.md).
We also present detailed instructions on how to reproduce our results.

## License

This project is released under the [MIT license](LICENSE).
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2 changes: 1 addition & 1 deletion configs/_base_/datasets/breaking_bad/artifact.py
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_C = CN()
_C.dataset = 'geometry'
_C.data_dir = '/scratch/ssd004/scratch/ziyiwu/data/assembly'
_C.data_dir = './data/breaking_bad'
_C.data_fn = 'artifact.{}.txt'
_C.data_keys = ('part_ids', )
_C.category = '' # empty means all categories
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2 changes: 1 addition & 1 deletion configs/_base_/datasets/breaking_bad/everyday.py
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_C = CN()
_C.dataset = 'geometry'
_C.data_dir = '/scratch/ssd004/scratch/ziyiwu/data/assembly'
_C.data_dir = './data/breaking_bad'
_C.data_fn = 'everyday.{}.txt'
_C.data_keys = ('part_ids', )
_C.category = '' # empty means all categories
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2 changes: 1 addition & 1 deletion configs/_base_/datasets/breaking_bad/other.py
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_C = CN()
_C.dataset = 'geometry'
_C.data_dir = '/scratch/ssd004/scratch/ziyiwu/data/assembly'
_C.data_dir = './data/breaking_bad'
_C.data_fn = 'other.{}.txt'
_C.data_keys = ('part_ids', )
_C.category = '' # empty means all categories
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2 changes: 1 addition & 1 deletion configs/_base_/datasets/partnet/partnet_chair.py
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_C = CN()
_C.dataset = 'partnet'
_C.data_dir = '../Generative-3D-Part-Assembly/prepare_data'
_C.data_dir = './data/partnet'
_C.data_fn = 'Chair.{}.npy'
_C.category = 'Chair' # actually useless
_C.data_keys = ('part_ids', 'match_ids', 'contact_points')
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2 changes: 1 addition & 1 deletion configs/_base_/datasets/partnet/partnet_lamp.py
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_C = CN()
_C.dataset = 'partnet'
_C.data_dir = '../Generative-3D-Part-Assembly/prepare_data'
_C.data_dir = './data/partnet'
_C.data_fn = 'Lamp.{}.npy'
_C.category = 'Lamp' # actually useless
_C.data_keys = ('part_ids', 'match_ids', 'contact_points')
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2 changes: 1 addition & 1 deletion configs/_base_/datasets/partnet/partnet_table.py
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_C = CN()
_C.dataset = 'partnet'
_C.data_dir = '../Generative-3D-Part-Assembly/prepare_data'
_C.data_dir = './data/partnet'
_C.data_fn = 'Table.{}.npy'
_C.category = 'Table' # actually useless
_C.data_keys = ('part_ids', 'match_ids', 'contact_points')
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1 change: 0 additions & 1 deletion configs/_base_/models/loss/geometric_loss.py
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# also note that there is almost no symmetry in this dataset
_C = CN()
_C.noise_dim = 0 # no stochastic
_C.num_rot = 1 # rotate GT to match the predictions

_C.trans_loss_w = 1.
_C.rot_pt_cd_loss_w = 10.
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23 changes: 0 additions & 23 deletions configs/_base_/models/pn_transformer/pn_transformer_gan.py

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17 changes: 0 additions & 17 deletions configs/_base_/models/pn_transformer/vn_pn_transformer.py

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18 changes: 0 additions & 18 deletions configs/_base_/models/pn_transformer/vn_pn_transformer_v2.py

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2 changes: 1 addition & 1 deletion configs/dgl/dgl-32x1-cosine_200e-artifact.py
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_C.exp.val_every = 5 # DGL training is very slow

_C.data = CN()
_C.data.data_keys = ('part_ids', 'instance_label', 'valid_matrix')
_C.data.data_keys = ('part_ids', 'valid_matrix')


def get_cfg_defaults():
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2 changes: 1 addition & 1 deletion configs/rgl_net/rgl_net-32x1-cosine_200e-artifact.py
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_C.exp.val_every = 5 # to be the same as DGL

_C.data = CN()
_C.data.data_keys = ('part_ids', 'instance_label', 'valid_matrix')
_C.data.data_keys = ('part_ids', 'valid_matrix')


def get_cfg_defaults():
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2 changes: 2 additions & 0 deletions docs/install.md
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conda activate assembly
# pytorch
conda install pytorch=1.10 torchvision torchaudio cudatoolkit=11.3 -c pytorch
# pytorch-lightning
conda install pytorch-lightning=1.6.2
# pytorch3d
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install pytorch3d -c pytorch3d
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