model: target: cldm.cldm.PAIRDiffusion learning_rate: 1.5e-05 sd_locked: True only_mid_control: False init_ckpt: './models/pair_diff_init.ckpt' params: linear_start: 0.00085 linear_end: 0.0120 num_timesteps_cond: 1 log_every_t: 200 timesteps: 1000 first_stage_key: "image" cond_stage_key: "caption" control_key: "hint" image_size: 64 channels: 4 cond_stage_trainable: false conditioning_key: crossattn monitor: val/loss_simple_ema scale_factor: 0.18215 use_ema: False only_mid_control: False appearance_net_locked: True app_net: 'DINO' control_stage_config: target: cldm.controlnet.ControlNetPAIR params: image_size: 32 # unused in_channels: 4 concat_indices: [0,1] concat_channels: 130 hint_channels: [1026, 1026, -1, -1] #(1024 + 2) 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 attn_class: ['maskguided', 'maskguided', 'softmax', 'softmax'] unet_config: target: cldm.cldm.ControlledUnetModel params: 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_heads: 8 use_spatial_transformer: True transformer_depth: 1 context_dim: 768 use_checkpoint: True legacy: 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.FrozenCLIPEmbedder data: target: cldm.data.DataModuleFromConfig params: batch_size: 2 wrap: True num_workers: 4 train: target: dataset.txtseg.COCOTrain params: image_dir: caption_file: panoptic_mask_dir: seg_dir: size: 512 validation: target: dataset.txtseg.COCOValidation params: size: 512 image_dir: caption_file: panoptic_mask_dir: seg_dir: lightning: callbacks: image_logger: target: main.ImageLogger params: batch_frequency: 2000 max_images: 4 increase_log_steps: False log_first_step: True trainer: benchmark: True accumulate_grad_batches: 2