model: base_learning_rate: 1.0e-04 target: src.ldm.models.diffusion.ddpm.LatentDiffusion params: linear_start: 0.00085 linear_end: 0.0120 num_timesteps_cond: 1 log_every_t: 200 timesteps: 1000 first_stage_key: "image_target" cond_stage_key: "image_cond" image_size: 32 channels: 4 cond_stage_trainable: false # Note: different from the one we trained before conditioning_key: hybrid monitor: val/loss_simple_ema scale_factor: 0.18215 scheduler_config: # 10000 warmup steps target: src.ldm.lr_scheduler.LambdaLinearScheduler params: warm_up_steps: [ 100 ] cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases f_start: [ 1.e-6 ] f_max: [ 1. ] f_min: [ 1. ] unet_config: target: src.ldm.modules.diffusionmodules.openaimodel.UNetModel params: image_size: 32 # unused in_channels: 8 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: src.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: src.ldm.modules.encoders.modules.FrozenCLIPImageEmbedder params: clip_root: 'ckpts/' data: target: src.ldm.data.simple.ObjaverseDataModuleFromConfig params: root_dir: 'views_whole_sphere' batch_size: 192 num_workers: 16 total_view: 4 train: validation: False image_transforms: size: 256 validation: validation: True image_transforms: size: 256 lightning: find_unused_parameters: false metrics_over_trainsteps_checkpoint: True modelcheckpoint: params: every_n_train_steps: 5000 callbacks: image_logger: target: main.ImageLogger params: batch_frequency: 500 max_images: 32 increase_log_steps: False log_first_step: True log_images_kwargs: use_ema_scope: False inpaint: False plot_progressive_rows: False plot_diffusion_rows: False N: 32 unconditional_guidance_scale: 3.0 unconditional_guidance_label: [""] trainer: benchmark: True val_check_interval: 5000000 # really sorry num_sanity_val_steps: 0 accumulate_grad_batches: 1