144 lines
4.0 KiB
YAML
144 lines
4.0 KiB
YAML
name: michelangelo-image-to-shape-diffusion/clip-mvrgb-modln-l256-e64-ne8-nd16-nl6-170k
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description: ''
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tag: michelangelo-aligned-autoencoder+n4096+noise0.0+pfeat3+zeroemb0.0+normembFalse+lr5e-05+qkvbiasFalse+nfreq8+ln_postTrue
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seed: 0
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use_timestamp: true
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timestamp: ''
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exp_root_dir: outputs
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exp_dir: outputs/michelangelo-image-to-shape-diffusion/clip-mvrgb-modln-l256-e64-ne8-nd16-nl6-170k
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trial_name: michelangelo-aligned-autoencoder+n4096+noise0.0+pfeat3+zeroemb0.0+normembFalse+lr5e-05+qkvbiasFalse+nfreq8+ln_postTrue
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trial_dir: outputs/michelangelo-image-to-shape-diffusion/clip-mvrgb-modln-l256-e64-ne8-nd16-nl6-170k/michelangelo-aligned-autoencoder+n4096+noise0.0+pfeat3+zeroemb0.0+normembFalse+lr5e-05+qkvbiasFalse+nfreq8+ln_postTrue
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n_gpus: 8
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resume: ./ckpts/3DNativeGeneration/michelangelo-image-to-shape-diffusion/clip-mvrgb-modln-l256-e64-ne8-nd16-nl6-170k.ckpt
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data_type: objaverse-datamodule
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data:
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root_dir: data/objaverse_clean/cap3d_high_quality_170k_images
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data_type: occupancy
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n_samples: 4096
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noise_sigma: 0.0
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load_supervision: false
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supervision_type: occupancy
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n_supervision: 10000
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load_image: true
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image_data_path: data/objaverse_clean/raw_data/images/cap3d_high_quality_170k
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image_type: mvrgb
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idx:
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- 0
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- 4
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- 8
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- 12
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- 16
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n_views: 4
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load_caption: false
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rotate_points: false
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batch_size: 32
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num_workers: 16
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system_type: shape-diffusion-system
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system:
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val_samples_json: val_data/mv_images/val_samples_rgb_mvimage.json
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z_scale_factor: 1.0
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guidance_scale: 7.5
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num_inference_steps: 50
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eta: 0.0
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shape_model_type: michelangelo-aligned-autoencoder
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shape_model:
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num_latents: 256
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embed_dim: 64
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point_feats: 3
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out_dim: 1
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num_freqs: 8
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include_pi: false
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heads: 12
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width: 768
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num_encoder_layers: 8
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num_decoder_layers: 16
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use_ln_post: true
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init_scale: 0.25
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qkv_bias: false
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use_flash: true
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use_checkpoint: true
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condition_model_type: clip-embedder
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condition_model:
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pretrained_model_name_or_path: openai/clip-vit-large-patch14
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encode_camera: true
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camera_embeds_dim: 32
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n_views: 4
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empty_embeds_ratio: 0.1
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normalize_embeds: false
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zero_uncond_embeds: true
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denoiser_model_type: simple-denoiser
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denoiser_model:
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input_channels: 64
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output_channels: 64
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n_ctx: 256
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width: 768
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layers: 6
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heads: 12
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context_dim: 1024
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init_scale: 1.0
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skip_ln: true
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use_checkpoint: true
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noise_scheduler_type: diffusers.schedulers.DDPMScheduler
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noise_scheduler:
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num_train_timesteps: 1000
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beta_start: 0.00085
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beta_end: 0.012
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beta_schedule: scaled_linear
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variance_type: fixed_small
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clip_sample: false
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denoise_scheduler_type: diffusers.schedulers.DDIMScheduler
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denoise_scheduler:
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num_train_timesteps: 1000
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beta_start: 0.00085
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beta_end: 0.012
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beta_schedule: scaled_linear
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clip_sample: false
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set_alpha_to_one: false
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steps_offset: 1
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loggers:
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wandb:
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enable: false
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project: JiangXin
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name: text-to-shape-diffusion+michelangelo-image-to-shape-diffusion/clip-mvrgb-modln-l256-e64-ne8-nd16-nl6-170k+michelangelo-aligned-autoencoder+n4096+noise0.0+pfeat3+zeroemb0.0+normembFalse+lr5e-05+qkvbiasFalse+nfreq8+ln_postTrue
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loss:
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loss_type: mse
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lambda_diffusion: 1.0
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optimizer:
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name: AdamW
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args:
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lr: 5.0e-05
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betas:
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- 0.9
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- 0.99
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eps: 1.0e-06
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scheduler:
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name: SequentialLR
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interval: step
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schedulers:
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- name: LinearLR
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interval: step
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args:
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start_factor: 1.0e-06
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end_factor: 1.0
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total_iters: 5000
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- name: CosineAnnealingLR
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interval: step
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args:
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T_max: 5000
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eta_min: 0.0
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milestones:
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- 5000
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trainer:
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num_nodes: 2
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max_epochs: 100000
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log_every_n_steps: 5
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num_sanity_val_steps: 1
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check_val_every_n_epoch: 3
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enable_progress_bar: true
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precision: 16-mixed
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strategy: ddp_find_unused_parameters_true
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checkpoint:
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save_last: true
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save_top_k: -1
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every_n_train_steps: 5000
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