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pretrain.yaml
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pretrain.yaml
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optimizer: { type: AdamW, kwargs: { lr: 0.0001, weight_decay: 0.05 } }
scheduler: { type: CosLR, kwargs: { epochs: 300, initial_epochs: 10 } }
dataset:
{
train:
{
_base_: cfgs/dataset_configs/UnlabeledHybrid.yaml,
others: { subset: "train", npoints: 1024 },
},
val:
{
_base_: cfgs/dataset_configs/UnlabeledHybrid.yaml,
others: { subset: "test", npoints: 1024 },
},
test:
{
_base_: cfgs/dataset_configs/UnlabeledHybrid.yaml,
others: { subset: "test", npoints: 1024 },
},
}
model:
{
NAME: PointGPT,
cls_dim: 40,
group_size: 32,
num_group: 64,
loss: cdl12,
weight_center: 1,
transformer_config:
{
mask_ratio: 0.7,
mask_type: "rand",
trans_dim: 768,
encoder_dims: 768,
depth: 12,
drop_path_rate: 0.1,
num_heads: 12,
decoder_depth: 4,
decoder_num_heads: 12,
},
}
npoints: 1024
total_bs: 128
step_per_update: 1
max_epoch: 300