GaussianAnything-AIGC3D / sgm /configs /stage1-mv23d-i23dpt-noi23d.yaml
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ldm_configs:
# scheduler_config:
# target: sgm.lr_scheduler.LambdaLinearScheduler
# params:
# warm_up_steps: [10000]
# cycle_lengths: [10000000000000]
# f_start: [1.e-6]
# f_max: [1.]
# f_min: [1.]
# denoiser_config:
# target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
# params:
# num_idx: 1000
# scaling_config:
# target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
# discretization_config:
# target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
conditioner_config:
target: sgm.modules.GeneralConditioner
params:
emb_models:
# - is_trainable: False
# input_key: caption
# ucg_rate: 0.316
# target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
# params:
# always_return_pooled: True
# legacy: False
# arch: 'ViT-L-14'
# version: 'openai'
- is_trainable: True
input_key: 'img-c'
ucg_rate: 0.1
# ucg_rate: 0.316
# ucg_rate: 0.167 # overall 0.1 dropout.
# legacy_ucg_value: None
target: sgm.modules.encoders.modules.FrozenDinov2ImageEmbedderMVPlucker
params:
freeze: False
enable_bf16: True
output_cls: False # return pooling
# arch: vitb
arch: vits
inp_size: 322
n_cond_frames: 6 # first 4 views as cond
modLN: False
aug_c: True
# - is_trainable: False
# input_key: 'img'
# ucg_rate: 0.6
# # legacy_ucg_value: None
# target: sgm.modules.encoders.modules.FrozenDinov2ImageEmbedder
# params:
# freeze: True
# arch: vitl
# inp_size: 518
# output_cls: True
# inp_size: 224
loss_fn_config:
target: sgm.modules.diffusionmodules.loss.FMLoss
params:
transport_config:
target: transport.create_transport
params: # all follow default
snr_type: uniform
path_type: GVP
guider_config:
target: sgm.modules.diffusionmodules.guiders.VanillaCFG
params:
# scale: 1.0
scale: 5.0