configs/inference.yaml

model:
  target: PrimeDepth_inference.ldm.models.diffusion.ddpm.PrimeDepth
  params:
    linear_start: 0.00085
    linear_end: 0.012
    num_timesteps_cond: 1
    timesteps: 1000
    first_stage_key: image
    cond_stage_key: caption
    parameterization: x0
    image_size: 64
    channels: 4
    cond_stage_trainable: false
    conditioning_key: crossattn
    monitor: val/loss
    scale_factor: 0.18215
    use_ema: false
    ckpt_path: ./checkpoints/PrimeDepth.ckpt
    label_mode:
    - segmentation
    - depth
    label_stage_config:
      target: PrimeDepth_inference.ldm.modules.diffusionmodules.labeller.PrimeDepthLabeller
      params:
        image_size: 32
        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
        use_spatial_transformer: true
        use_linear_in_transformer: true
        transformer_depth: 1
        context_dim: 1024
        use_checkpoint: false
        legacy: false
        infusion2refiner: cat
        refiner_model_ratio: 0.5
        use_self_attn_maps: true
        use_cross_attn_maps: true
        use_feature_maps: true
        n_ca_maps: 77
        n_sa_maps: 64
        channels2predictor: 512
        label_mode:
          depth: 3
          segmentation: 150
        zero_convs: false
        scale_input_features_with_model: true
        label_decoder_config:
          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
    unet_config:
      target: PrimeDepth_inference.ldm.modules.diffusionmodules.openaimodel.UNetModel
      params:
        use_checkpoint: true
        image_size: 32
        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
        use_spatial_transformer: true
        use_linear_in_transformer: true
        transformer_depth: 1
        context_dim: 1024
        legacy: false
    first_stage_config:
      target: PrimeDepth_inference.ldm.models.autoencoder.AutoencoderKL
      params:
        embed_dim: 4
        monitor: val/rec_loss
        ddconfig:
          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: PrimeDepth_inference.ldm.modules.encoders.modules.FrozenOpenCLIPEmbedder