# Experiment setup 
job_key: ''
run_name: 'binnedSpec_experiment'
run_details: ""
project_name: ''
wandb_entity_name: 'mass-spec-ml'
no_wandb: True
seed: 0
debug: False
checkpoint_pth: ""

# Training setup
max_epochs: 1000 
accelerator: 'gpu'
devices: [1]
log_every_n_steps: 250
val_check_interval: 1.0

# Data paths
candidates_pth: ../data/sample/candidates_mass.json
dataset_pth: "../data/sample/data.tsv" 
subformula_dir_pth: ""
split_pth: 
fp_dir_pth: '../data/sample/morganfp_r5_1024.pickle'
cons_spec_dir_pth: "../data/sample/consensus_binnedSpec.pkl"
NL_spec_dir_pth: ""
partial_checkpoint: ""

# General hyperparameters
batch_size: 64
lr: 5.0e-4
weight_decay: 0
contr_temp: 0.05
early_stopping_patience: 300
loss_strategy: 'static' # static, linear, manual
num_workers: 50


############################## Data transforms ##############################
# - Spectra 
spectra_view:  SpecBinnerLog 
max_mz: 1000
bin_width: 1
mask_peak_ratio: 0.00

# 2. SpecFormula
element_list: ['H', 'C',  'O', 'N', 'P', 'S', 'Cl', 'F', 'Br', 'I', 'B', 'As', 'Si', 'Se']
add_intensities: True
mask_precursor: False

# - Molecule
molecule_view: "MolGraph"
atom_feature: 'full'
bond_feature: 'full'


############################## Views ##############################
# contrastive
use_contr: True
contr_wt: 1
contr_wt_update: {} 

# consensus spectra
use_cons_spec: False
cons_spec_wt: 3
cons_spec_wt_update: {} 
cons_loss_type: 'l2' # cosine, l2

# fp prediction/usage
pred_fp: False
use_fp: False
fp_loss_type: 'cosine' #cosine, bce
fp_wt: 3
fp_wt_update: {} 
fp_size: 1024
fp_radius: 5
fp_dropout: 0.4

# candidates
aug_cands: False
aug_cands_wt: 0.1
aug_cands_update: {} 
aug_cands_size: 3

# neutral loss
use_NL: False



############################## Task and model ##############################
task: 'retrieval'
spec_enc: MLP_BIN 
mol_enc: "GNN"
model:  "MultiviewContrastive" 
contr_views: [['spec_enc', 'mol_enc']]
log_only_loss_at_stages: []
df_test_path: ""

# - Spectra encoder
final_embedding_dim: 512
fc_dropout: 0.4

# - Spectra Token encoder
hidden_dims: [64, 128]
peak_dropout: 0.2

# - Formula-based spec encoders
formula_dropout: 0.2
formula_dims: [64, 128, 256]
cross_attn_heads: 2
use_cls: True

# -- GAT params
attn_heads: [12,12,12]

# - Molecule encoder (GNN)
gnn_channels: [64,128,256] 
gnn_type: "gcn"
num_gnn_layers: 3
gnn_hidden_dim: 512
gnn_dropout: 0.3