TargetDiff / configs /training.yml
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data:
name: pl
path: ${ONESCIENCE_DATASETS_DIR}/targetdiff/data/crossdocked_v1.1_rmsd1.0_pocket10
split: ${ONESCIENCE_DATASETS_DIR}/targetdiff/data/crossdocked_pocket10_pose_split.pt
transform:
ligand_atom_mode: add_aromatic
random_rot: False
model:
model_mean_type: C0 # ['noise', 'C0']
beta_schedule: sigmoid
beta_start: 1.e-7
beta_end: 2.e-3
v_beta_schedule: cosine
v_beta_s: 0.01
num_diffusion_timesteps: 1000
loss_v_weight: 100.
sample_time_method: symmetric # ['importance', 'symmetric']
time_emb_dim: 0
time_emb_mode: simple
center_pos_mode: protein
node_indicator: True
model_type: uni_o2
num_blocks: 1
num_layers: 9
hidden_dim: 128
n_heads: 16
edge_feat_dim: 4 # edge type feat
num_r_gaussian: 20
knn: 32 # !
num_node_types: 8
act_fn: relu
norm: True
cutoff_mode: knn # [radius, none]
ew_net_type: global # [r, m, none]
num_x2h: 1
num_h2x: 1
r_max: 10.
x2h_out_fc: False
sync_twoup: False
train:
seed: 2021
batch_size: 4
num_workers: 4
n_acc_batch: 1
max_iters: 10000000
val_freq: 100
pos_noise_std: 0.1
max_grad_norm: 8.0
bond_loss_weight: 1.0
optimizer:
type: adam
lr: 5.e-4
weight_decay: 0
beta1: 0.95
beta2: 0.999
scheduler:
type: plateau
factor: 0.6
patience: 10
min_lr: 1.e-6