model: base_learning_rate: 5.0e-07 target: ldm.models.diffusion.ddpm.LatentDepth2ImageDiffusion params: linear_start: 0.00085 linear_end: 0.0120 num_timesteps_cond: 1 log_every_t: 200 timesteps: 1000 first_stage_key: "jpg" cond_stage_key: "txt" image_size: 64 channels: 4 cond_stage_trainable: false conditioning_key: hybrid scale_factor: 0.18215 monitor: val/loss_simple_ema finetune_keys: null use_ema: False depth_stage_config: target: ldm.modules.midas.api.MiDaSInference params: model_type: "dpt_hybrid" unet_config: target: ldm.modules.diffusionmodules.openaimodel.UNetModel params: use_checkpoint: True image_size: 32 # unused in_channels: 5 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 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"