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skills/diffdock/assets/custom_inference_config.yaml
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skills/diffdock/assets/custom_inference_config.yaml
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# DiffDock Custom Inference Configuration Template
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# Copy and modify this file to customize inference parameters
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# Model paths (usually don't need to change these)
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model_dir: ./workdir/v1.1/score_model
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confidence_model_dir: ./workdir/v1.1/confidence_model
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ckpt: best_ema_inference_epoch_model.pt
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confidence_ckpt: best_model_epoch75.pt
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# Model version flags
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old_score_model: false # Set to true to use original DiffDock instead of DiffDock-L
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old_filtering_model: true
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# Inference steps
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inference_steps: 20 # Increase for potentially better accuracy (e.g., 25-30)
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actual_steps: 19
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no_final_step_noise: true
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# Sampling parameters
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samples_per_complex: 10 # Increase for difficult cases (e.g., 20-40)
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sigma_schedule: expbeta
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initial_noise_std_proportion: 1.46
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# Temperature controls - Adjust these to balance exploration vs accuracy
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# Higher values = more diverse predictions, lower values = more focused predictions
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# Sampling temperatures
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temp_sampling_tr: 1.17 # Translation sampling temperature
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temp_sampling_rot: 2.06 # Rotation sampling temperature
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temp_sampling_tor: 7.04 # Torsion sampling temperature (increase for flexible ligands)
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# Psi angle temperatures
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temp_psi_tr: 0.73
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temp_psi_rot: 0.90
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temp_psi_tor: 0.59
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# Sigma data temperatures
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temp_sigma_data_tr: 0.93
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temp_sigma_data_rot: 0.75
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temp_sigma_data_tor: 0.69
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# Feature flags
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no_model: false
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no_random: false
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ode: false # Set to true to use ODE solver instead of SDE
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different_schedules: false
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limit_failures: 5
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# Output settings
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# save_visualisation: true # Uncomment to save SDF files
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# ============================================================================
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# Configuration Presets for Common Use Cases
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# ============================================================================
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# PRESET 1: High Accuracy (slower, more thorough)
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# samples_per_complex: 30
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# inference_steps: 25
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# temp_sampling_tr: 1.0
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# temp_sampling_rot: 1.8
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# temp_sampling_tor: 6.5
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# PRESET 2: Fast Screening (faster, less thorough)
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# samples_per_complex: 5
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# inference_steps: 15
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# temp_sampling_tr: 1.3
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# temp_sampling_rot: 2.2
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# temp_sampling_tor: 7.5
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# PRESET 3: Flexible Ligands (more conformational diversity)
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# samples_per_complex: 20
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# inference_steps: 20
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# temp_sampling_tr: 1.2
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# temp_sampling_rot: 2.1
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# temp_sampling_tor: 8.5 # Increased torsion temperature
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# PRESET 4: Rigid Ligands (more focused predictions)
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# samples_per_complex: 10
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# inference_steps: 20
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# temp_sampling_tr: 1.1
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# temp_sampling_rot: 2.0
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# temp_sampling_tor: 6.0 # Decreased torsion temperature
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# ============================================================================
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# Usage Example
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# ============================================================================
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# python -m inference \
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# --config custom_inference_config.yaml \
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# --protein_ligand_csv input.csv \
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# --out_dir results/
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