DrugFlow / configs /training /flexflow.yml
mority's picture
Upload 53 files
6e7d4ba verified
run_name: flexflow
pocket_representation: CA+
virtual_nodes: [0, 10]
flexible: True
flexible_bb: False
train_params:
logdir: ./runs # symlink to any location you like
datadir: ./processed_crossdocked # symlink to the dataset location
enable_progress_bar: False
num_sanity_val_steps: 0
batch_size: 64
accumulate_grad_batches: 2
lr: 5.0e-4
lr_step_size: null
lr_gamma: null
n_epochs: 700
num_workers: 4
gpus: 1
clip_grad: True
gnina: gnina # add Gnina location to path
sample_from_clusters: False
sharded_dataset: False
wandb_params:
mode: online # disabled, offline, online
entity:
group: crossdocked
loss_params:
discrete_loss: VLB # VLB or CE
reduce: sum # 'mean' or 'sum'
lambda_x: 0.015
lambda_h: 2.5
lambda_e: 0.25
lambda_chi: 0.002
lambda_trans: null
lambda_rot: null
lambda_clash: null
regularize_uncertainty: null
timestep_weights: null
simulation_params:
n_steps: 5000
prior_h: marginal # uniform, marginal
prior_e: uniform # uniform, marginal
predict_final: False
predict_confidence: False
scheduler_chi:
type: polynomial
k: 3 # constant for exponential scheduler kappa(t)=(1-t)^k
eval_params:
eval_epochs: 100
n_loss_per_sample: 100
n_eval_samples: 4
n_sampling_steps: 500
eval_batch_size: 16
visualize_sample_epoch: 1
n_visualize_samples: 100
visualize_chain_epoch: 1
keep_frames: 100
sample_with_ground_truth_size: True
predictor_params:
heterogeneous_graph: True
backbone: gvp
num_rbf_time: 16
edge_cutoff_ligand: null
edge_cutoff_pocket: 10.0
edge_cutoff_interaction: 10.0
cycle_counts: True
spectral_feat: False
reflection_equivariant: False
num_rbf: 16
d_max: 15.0
self_conditioning: True
augment_residue_sc: False
augment_ligand_sc: False
normal_modes: False
add_chi_as_feature: False
angle_act_fn: null
add_all_atom_diff: True
gvp_params:
n_layers: 5
node_h_dim: [ 128, 32 ] # (s, V)
edge_h_dim: [ 128, 32 ]
dropout: 0.0
vector_gate: True