model:
  base_learning_rate: 1.0e-04
  target: ldm.models.diffusion.ddpm.ImageEmbeddingConditionedLatentDiffusion
  params:
    embedding_dropout: 0.25
    parameterization: "v"
    linear_start: 0.00085
    linear_end: 0.0120
    log_every_t: 200
    timesteps: 1000
    first_stage_key: "jpg"
    cond_stage_key: "txt"
    image_size: 96
    channels: 4
    cond_stage_trainable: false
    conditioning_key: crossattn-adm
    scale_factor: 0.18215
    monitor: val/loss_simple_ema
    use_ema: False

    embedder_config:
      target: ldm.modules.encoders.modules.ClipImageEmbedder
      params:
        model: "ViT-L/14"

    unet_config:
      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        num_classes: "sequential"
        adm_in_channels: 768
        use_checkpoint: True
        image_size: 32 # unused
        in_channels: 4
        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 # need to fix for flash-attn
        use_spatial_transformer: True
        use_linear_in_transformer: True
        transformer_depth: 1
        context_dim: 1024
        spatial_transformer_attn_type: "softmax-xformers"
        legacy: False

    first_stage_config:
      target: ldm.models.autoencoder.AutoencoderKL
      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

    cond_stage_config:
      target: ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder
      params:
        freeze: True
        layer: "penultimate"