sgm/configs/img23d-clipl-compat-fm-lognorm-480-uniform.yaml

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: 'img'
          ucg_rate: 0.316
          # legacy_ucg_value: None
          target: sgm.modules.encoders.modules.FrozenOpenCLIPImageEmbedder
          params:
              arch: 'ViT-L-14'
              version: 'openai'
              # version: 'laion2b_s32b_b82k'
              freeze: True
              output_tokens: True
              # inp_size: 448
              inp_size: 224

        - is_trainable: False
          input_key: 'img'
          ucg_rate: 0.316
          # legacy_ucg_value: None
          target: sgm.modules.encoders.modules.FrozenDinov2ImageEmbedder
          params:
              freeze: True
              arch: vitl
              # inp_size: 448
              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: lognorm # too noisy?
          snr_type: uniform
          # path_type: Linear
          path_type: GVP

  guider_config:
    target: sgm.modules.diffusionmodules.guiders.VanillaCFG
    params:
      # scale: 1.0
      scale: 5.0