Upload photo100k Stage 2 v2 condition encoder
Browse files
configs/diffusion_photo100k_b32_stage4_condition_v2.yaml
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project:
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name: diffusion_photo100k_b32_stage4_condition_v2
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output_dir: /home/jwheojjang/scratch/sr-diffusion/runs/diffusion_photo100k_b32_stage4_condition_v2
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logging:
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wandb:
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enabled: true
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project: sr-diffusion
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name: diffusion_photo100k_b32_stage4_condition_v2
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mode: online
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dir: /home/jwheojjang/scratch/sr-diffusion/wandb
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tags: [stage4, diffusion, condition-start, photo100k, degradation-v2, b32, init-stage3-photo100k-v2]
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watch: false
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samples:
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enabled: true
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split: val
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fallback_split: train
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count: 4
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indices: [0, 1, 2, 3]
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init: condition
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seed: 1337
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autoencoder:
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config: configs/autoencoder_photo10k.yaml
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checkpoint: /home/jwheojjang/scratch/sr-diffusion/runs/autoencoder_photo10k_b16_eval_online/checkpoints/best_eval_recon.pt
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condition_encoder:
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config: configs/latent_pretrain_photo100k_v2.yaml
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checkpoint: /home/jwheojjang/scratch/sr-diffusion/runs/latent_pretrain_photo100k_v2_b64/checkpoints/best_eval_latent.pt
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trainable: false
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data:
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manifest: /home/jwheojjang/scratch/sr-diffusion/data/manifest_photo100k.csv
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split: train
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hr_size: 512
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scale: 4
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degradation_preset: photo_v2
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domains:
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photo: 0
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anime: 1
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num_workers: 8
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model:
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type: conditional_unet
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latent_channels: 16
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condition_channels: 16
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out_channels: 16
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base_channels: 128
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channel_multipliers: [1, 2, 3, 4]
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num_res_blocks: 2
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norm_groups: 32
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num_heads: 4
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attention_resolutions: [32, 16]
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base_resolution: 128
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num_domains: 2
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diffusion:
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num_train_timesteps: 1000
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beta_schedule: linear
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beta_start: 0.0001
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beta_end: 0.02
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sample_timestep: 50
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train_min_timestep: 25
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train_max_timestep: 100
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train_init: condition
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sampling:
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init: condition
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start_timestep: 25
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steps: 32
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loss:
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noise_weight: 0.05
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x0_weight: 1.0
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train:
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device: auto
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dtype: bf16
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batch_size: 32
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max_steps: 5000
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lr: 0.00001
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weight_decay: 0.0
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grad_accum_steps: 1
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log_every: 25
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save_every: 1000
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sample_every: 500
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eval:
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enabled: true
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split: val
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limit: 100
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batch_size: 32
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num_workers: 8
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every: 500
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run_at_start: true
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timestep: 50
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init: condition
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best_metric: eval/decoded_mse
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best_mode: min
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best_checkpoint: best_eval_condition_decoded.pt
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