[607087]: / configs / crossdock_ca_cond.yml

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run_name: 'SE3-cond-CA'
logdir: '/path/to/logdir'
wandb_params:
mode: 'online' # disabled, offline, online
entity: 'my_username'
dataset: 'crossdock'
datadir: '/path/to/processed_crossdock_noH_ca_only'
enable_progress_bar: True
num_sanity_val_steps: 0
mode: 'pocket_conditioning' # joint, pocket_conditioning
pocket_representation: 'CA' # CA, full-atom
batch_size: 96
lr: 1.0e-3
noise_factor: 1.0
n_epochs: 1000
num_workers: 0
gpus: 4
clip_grad: True
augment_rotation: False
augment_noise: 0
accumulate_grad_batches: 1
auxiliary_loss: False
loss_params:
max_weight: 0.001
schedule: 'linear'
clamp_lj: 3.0
egnn_params:
device: 'cuda'
edge_cutoff_ligand: null
edge_cutoff_pocket: 5.0
edge_cutoff_interaction: 5.0
reflection_equivariant: False
joint_nf: 128
hidden_nf: 256
n_layers: 6
attention: True
tanh: True
norm_constant: 1
inv_sublayers: 1
sin_embedding: False
aggregation_method: 'sum'
normalization_factor: 100 #1 # used if aggregation_method='sum'
diffusion_params:
diffusion_steps: 500
diffusion_noise_schedule: 'polynomial_2' # learned, cosine
diffusion_noise_precision: 5.0e-4
diffusion_loss_type: 'l2' # vlb, l2
normalize_factors: [1, 1] #[10, 4] # [x, h]
eval_epochs: 50
visualize_sample_epoch: 50
visualize_chain_epoch: 50
eval_params:
n_eval_samples: 100
eval_batch_size: 100
smiles_file: '/path/to/train_smiles.npy'
n_visualize_samples: 5
keep_frames: 100