sampling.toml

# REINVENT4 TOML input example for sampling
#


run_type = "sampling"
device = "cuda:0"  # set torch device e.g. "cpu"
json_out_config = "_sampling.json"  # write this TOML to JSON


[parameters]

# Uncomment one of the comment blocks below.  Each generator needs a model
# file and possibly a SMILES file with seed structures.

## Reinvent: de novo sampling
#model_file = "priors/reinvent.prior"

## LibInvent: find R-groups for the given scaffolds
#model_file = "priors/libinvent.prior"
#smiles_file = "scaffolds.smi"  # 1 scaffold per line with attachment points

## LinkInvent: find a linker/scaffold to link two fragments
#model_file = "priors/linkinvent.prior"
#smiles_file = "warheads.smi"  # 2 warheads per line separated with '|'

## Mol2Mol: find molecules similar to the provided molecules
model_file = "priors/mol2mol_medium_similarity.prior"
smiles_file = "C:\\Users\\Rohan KumarMishra\\Desktop\\hide\\chat_pharma\\src\\smiles\\f2.smi"
sample_strategy = "beamsearch"  # multinomial or beamsearch (deterministic)
temperature = 1.0 # temperature in multinomial sampling
tb_logdir = "tb_logs"  # name of the TensorBoard logging directory

output_file = 'sampling.csv'  # sampled SMILES and NLL in CSV format

num_smiles = 157  # number of SMILES to be sampled, 1 per input SMILES
unique_molecules = true  # if true remove all duplicatesd canonicalize smiles
randomize_smiles = true # if true shuffle atoms in SMILES randomly