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