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| model: | |
| base_learning_rate: 1.0e-04 | |
| target: 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: 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: 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: 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: 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 | |