FlowProt / model /test_dataset.yaml
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data:
dataset:
seed: 9
max_num_res: 256
cache_num_res: 0
min_num_res: 0
subset: null
samples_per_eval_length: 5
num_eval_lengths: 5
min_eval_length: 500
csv_path: class_preprocessed/metadata.csv
loader:
num_workers: 4
prefetch_factor: 10
sampler:
max_batch_size: 100
max_num_res_squared: 500000
interpolant:
min_t: 1e-2
rots:
train_schedule: linear
sample_schedule: exp
exp_rate: 10
trans:
train_schedule: linear
sample_schedule: linear
sampling:
num_timesteps: 100
self_condition: ${model.edge_features.self_condition}
model:
node_embed_size: 128
edge_embed_size: 128
symmetric: false
node_features:
c_s: ${model.node_embed_size}
c_pos_emb: 128
c_timestep_emb: 128
embed_diffuse_mask: false
max_num_res: 2000
timestep_int: 1000
edge_features:
single_bias_transition_n: 2
c_s: ${model.node_embed_size}
c_p: ${model.edge_embed_size}
relpos_k: 64
use_rbf: true
num_rbf: 32
feat_dim: 64
num_bins: 22
self_condition: true
ipa:
c_s: ${model.node_embed_size}
c_z: ${model.edge_embed_size}
c_hidden: 128
no_heads: 8
no_qk_points: 8
no_v_points: 4
seq_tfmr_num_heads: 4
seq_tfmr_num_layers: 2
num_blocks: 6
experiment:
debug: false
seed: 123
#num_devices: 2
warm_start: null
warm_start_cfg_override: true
use_swa: false
batch_ot:
enabled: true
cost: kabsch
noise_per_sample: 1
permute: false
training:
min_plddt_mask: null
loss: se3_vf_loss
bb_atom_scale: 0.1
trans_scale: 0.1
translation_loss_weight: 2.0
t_normalize_clip: 0.9
rotation_loss_weights: 1.0
aux_loss_weight: 1.0
aux_loss_t_pass: 0.25
wandb:
name: dnmt-test-unconditioned
project: se3-fm
save_code: true
tags: []
optimizer:
lr: 0.0001
trainer:
overfit_batches: 0
min_epochs: 1
max_epochs: 300
accelerator: gpu
log_every_n_steps: 1
deterministic: false
#strategy: ddp
check_val_every_n_epoch: 2
accumulate_grad_batches: 2
num_sanity_val_steps: 0
checkpointer:
dirpath: ckpt/${experiment.wandb.project}/${experiment.wandb.name}/${now:%Y-%m-%d}_${now:%H-%M-%S}
save_last: true
save_top_k: 3
monitor: valid/non_coil_percent
mode: max