model: base_learning_rate: 5.0e-5 # set to target_lr by starting main.py with '--scale_lr False' target: ldm.models.diffusion.ddpm.LatentDiffusion params: linear_start: 0.0015 linear_end: 0.0155 num_timesteps_cond: 1 log_every_t: 200 timesteps: 1000 loss_type: l1 first_stage_key: "image" cond_stage_key: "image" image_size: 32 channels: 4 cond_stage_trainable: False concat_mode: False scale_by_std: True monitor: 'val/loss_simple_ema' scheduler_config: # 10000 warmup steps target: ldm.lr_scheduler.LambdaLinearScheduler params: warm_up_steps: [10000] cycle_lengths: [10000000000000] f_start: [1.e-6] f_max: [1.] f_min: [ 1.] unet_config: target: ldm.modules.diffusionmodules.openaimodel.UNetModel params: image_size: 32 in_channels: 4 out_channels: 4 model_channels: 192 attention_resolutions: [ 1, 2, 4, 8 ] # 32, 16, 8, 4 num_res_blocks: 2 channel_mult: [ 1,2,2,4,4 ] # 32, 16, 8, 4, 2 num_heads: 8 use_scale_shift_norm: True resblock_updown: True first_stage_config: target: ldm.models.autoencoder.AutoencoderKL params: embed_dim: 4 monitor: "val/rec_loss" ckpt_path: "/export/compvis-nfs/user/ablattma/logs/braket/2021-11-26T11-25-56_lsun_churches-convae-f8-ft_from_oi/checkpoints/step=000180071-fidfrechet_inception_distance=2.335.ckpt" ddconfig: double_z: True z_channels: 4 resolution: 256 in_channels: 3 out_ch: 3 ch: 128 ch_mult: [ 1,2,4,4 ] # num_down = len(ch_mult)-1 num_res_blocks: 2 attn_resolutions: [ ] dropout: 0.0 lossconfig: target: torch.nn.Identity cond_stage_config: "__is_unconditional__" data: target: main.DataModuleFromConfig params: batch_size: 24 # TODO: was 96 in our experiments num_workers: 5 wrap: False train: target: ldm.data.lsun.LSUNChurchesTrain params: size: 256 validation: target: ldm.data.lsun.LSUNChurchesValidation params: size: 256 lightning: callbacks: image_logger: target: main.ImageLogger params: batch_frequency: 1000 # TODO 5000 max_images: 8 increase_log_steps: False metrics_over_trainsteps_checkpoint: target: pytorch_lightning.callbacks.ModelCheckpoint params: every_n_train_steps: 20000 trainer: benchmark: True