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bpt yaml

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model:
target: hy3dgen.shapegen.bpt.miche.michelangelo.models.tsal.asl_pl_module.AlignedShapeAsLatentPLModule
params:
shape_module_cfg:
target: hy3dgen.shapegen.bpt.miche.michelangelo.models.tsal.sal_perceiver.AlignedShapeLatentPerceiver
params:
num_latents: 256
embed_dim: 64
point_feats: 3 # normal
num_freqs: 8
include_pi: false
heads: 12
width: 768
num_encoder_layers: 8
num_decoder_layers: 16
use_ln_post: true
init_scale: 0.25
qkv_bias: false
use_checkpoint: true
aligned_module_cfg:
target: hy3dgen.shapegen.bpt.miche.michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
params:
clip_model_version: "./checkpoints/clip/clip-vit-large-patch14"
loss_cfg:
target: hy3dgen.shapegen.bpt.miche.michelangelo.models.tsal.loss.ContrastKLNearFar
params:
contrast_weight: 0.1
near_weight: 0.1
kl_weight: 0.001
optimizer_cfg:
optimizer:
target: torch.optim.AdamW
params:
betas: [0.9, 0.99]
eps: 1.e-6
weight_decay: 1.e-2
scheduler:
target: hy3dgen.shapegen.bpt.miche.michelangelo.utils.trainings.lr_scheduler.LambdaWarmUpCosineFactorScheduler
params:
warm_up_steps: 5000
f_start: 1.e-6
f_min: 1.e-3
f_max: 1.0