| ckpt_path: null |
| ddpm: |
| cond_drop_threshold: 0.1 |
| prediction_type: v_prediction |
| exp_name: cond_model_emready |
| inference: |
| batch_size: 16 |
| patch_overlap: 0 |
| is_debug: false |
| keep_last_k: null |
| mode: train |
| model: |
| act_fn: silu |
| attention_head_dim: 8 |
| attn_norm_num_groups: null |
| block_out_channels: !!python/tuple |
| - 64 |
| - 128 |
| - 256 |
| - 512 |
| class_embed_type: null |
| down_block_types: !!python/tuple |
| - DownBlock3D |
| - DownBlock3D |
| - AttnDownBlock3D |
| - AttnDownBlock3D |
| downsample_padding: 1 |
| downsample_type: conv |
| dropout: 0.0 |
| flip_sin_to_cos: true |
| freq_shift: 0 |
| in_channels: 3 |
| layers_per_block: 2 |
| mid_block_scale_factor: 1 |
| norm_eps: 1.0e-05 |
| norm_num_groups: 32 |
| num_class_embeds: 5 |
| out_channels: 1 |
| resnet_time_scale_shift: scale_shift |
| sample_size: 64 |
| time_embedding_dim: null |
| time_embedding_type: positional |
| up_block_types: !!python/tuple |
| - AttnUpBlock3D |
| - AttnUpBlock3D |
| - UpBlock3D |
| - UpBlock3D |
| upsample_type: conv |
| model_type: unet |
| num_val_samples: 3 |
| optimizer: |
| lr: 0.0001 |
| warmup: 2000 |
| patch_size: 64 |
| process: fm |
| resume_path: null |
| seed: 42 |
| selective_datasets: emready |
| timestep_sampling: uniform |
| work_dir: work_dirs/cond_model_emready |
| z_crop: null |
| z_scale: |
| mean: null |
| std: null |
|
|
