model: base_learning_rate: 3e-05 target: ldm.models.diffusion.control.ControlLDM params: linear_start: 0.00085 linear_end: 0.0120 log_every_t: 200 timesteps: 1000 image_size: 64 channels: 4 u_cond_percent: 0.2 scale_factor: 0.18215 use_ema: False control_stage_config: target: ldm.models.diffusion.control.ControlNet params: use_checkpoint: True in_channels: 9 hint_channels: 5 model_channels: 320 attention_resolutions: [ 4, 2, 1 ] num_res_blocks: 2 channel_mult: [ 1, 2, 4, 4 ] num_head_channels: 64 transformer_depth: 1 context_dim: 768 unet_config: target: ldm.models.diffusion.control.ControlledUnetModel params: image_size: 32 # unused in_channels: 9 out_channels: 4 model_channels: 320 attention_resolutions: [ 4, 2, 1 ] num_res_blocks: 2 channel_mult: [ 1, 2, 4, 4 ] num_heads: 8 use_spatial_transformer: True transformer_depth: 1 context_dim: 768 use_checkpoint: True legacy: False add_conv_in_front_of_unet: False first_stage_config: target: 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: ldm.modules.encoders.modules.FrozenCLIPImageEmbedder data: target: test.DataModuleFromConfig params: batch_size: 1 wrap: False test: target: ldm.data.image_dresscode.OpenImageDataset params: state: test dataset_dir: datasets/dresscode type: unpaired lightning: trainer: num_nodes: 1 profiler: "simple" accelerator: 'ddp' gpus: "0,1"