model:
  target: sgm.models.diffusion.DiffusionEngine
  params:
    scale_factor: 0.18215
    disable_first_stage_autocast: True

    denoiser_config:
      target: sgm.modules.diffusionmodules.denoiser.Denoiser
      params:
        scaling_config:
          target: sgm.modules.diffusionmodules.denoiser_scaling.VScalingWithEDMcNoise

    network_config:
      target: sgm.modules.diffusionmodules.video_model.VideoUNet
      params:
        adm_in_channels: 256
        num_classes: sequential
        use_checkpoint: True
        in_channels: 8
        out_channels: 4
        model_channels: 320
        attention_resolutions: [4, 2, 1]
        num_res_blocks: 2
        channel_mult: [1, 2, 4, 4]
        num_head_channels: 64
        use_linear_in_transformer: True
        transformer_depth: 1
        context_dim: 1024
        spatial_transformer_attn_type: softmax-xformers
        extra_ff_mix_layer: True
        use_spatial_context: True
        merge_strategy: learned_with_images
        video_kernel_size: [3, 1, 1]

    conditioner_config:
      target: sgm.modules.GeneralConditioner
      params:
        emb_models:
        - input_key: cond_frames_without_noise
          is_trainable: False
          target: sgm.modules.encoders.modules.FrozenOpenCLIPImagePredictionEmbedder
          params:
            n_cond_frames: 1
            n_copies: 1
            open_clip_embedding_config:
              target: sgm.modules.encoders.modules.FrozenOpenCLIPImageEmbedder
              params:
                freeze: True

        - input_key: cond_frames
          is_trainable: False
          target: sgm.modules.encoders.modules.VideoPredictionEmbedderWithEncoder
          params:
            disable_encoder_autocast: True
            n_cond_frames: 1
            n_copies: 1
            is_ae: True
            encoder_config:
              target: sgm.models.autoencoder.AutoencoderKLModeOnly
              params:
                embed_dim: 4
                monitor: val/rec_loss
                ddconfig:
                  attn_type: vanilla-xformers
                  double_z: True
                  z_channels: 4
                  resolution: 256
                  in_channels: 3
                  out_ch: 3
                  ch: 128
                  ch_mult: [1, 2, 4, 4]
                  num_res_blocks: 2
                  attn_resolutions: []
                  dropout: 0.0
                lossconfig:
                  target: torch.nn.Identity

        - input_key: cond_aug
          is_trainable: False
          target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
          params:
            outdim: 256

    first_stage_config:
      target: sgm.models.autoencoder.AutoencodingEngine
      params:
        loss_config:
          target: torch.nn.Identity
        regularizer_config:
          target: sgm.modules.autoencoding.regularizers.DiagonalGaussianRegularizer
        encoder_config:
          target: torch.nn.Identity
        decoder_config:
          target: sgm.modules.diffusionmodules.model.Decoder
          params:
            attn_type: vanilla-xformers
            double_z: True
            z_channels: 4
            resolution: 256
            in_channels: 3
            out_ch: 3
            ch: 128
            ch_mult: [ 1, 2, 4, 4 ]
            num_res_blocks: 2
            attn_resolutions: [ ]
            dropout: 0.0