Code for the paper "JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design"

Related tags

Deep LearningJANUS
Overview

JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design

This repository contains code for the paper: JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design. By: AkshatKumar Nigam, Robert Pollice, Alán Aspuru-Guzik

Package Requirements:

Using The Code:

The code can be run using:

python ./JANUS.py

Within params_init.py, a user has the option to provide:

  1. A function for calculting property values (see function calc_prop).
  2. Input parameters that are to be used by JANUS (see function generate_params). Initial parameters are provided. These are picked based on prior experience by the authors of the paper.

Output Generation:

All results from running JANUS will be stored here. The following files will be created:

  1. fitness_explore.txt: Fitness values for all molecules from the exploration component of JANUS.
  2. fitness_local_search.txt: Fitness values for all molecules from the exploitation component of JANUS.
  3. generation_all_best.txt: Smiles and fitness value for the best molecule encountered in every generation (iteration).
  4. init_mols.txt: List of molecules used to initialte JANUS.
  5. population_explore.txt: SMILES for all molecules from the exploration component of JANUS.
  6. population_local_search.txt: SMILES for all molecules from the exploitation component of JANUS.

Paper Results/Reproducibility:

Our code and results for each experiment in the paper can be found here:

Questions, problems?

Make a github issue 😄 . Please be as clear and descriptive as possible. Please feel free to reach out in person: (akshat[DOT]nigam[AT]mail[DOT]utoronto[DOT]ca, rob[DOT]pollice[AT]utoronto[DOT]ca)

License

Apache License 2.0

Comments
  • freeze_support runtime error with provided example

    freeze_support runtime error with provided example

    Hello, I'm trying out JANUS and if I just run the example inside the tests as provided I get

      File "/Users/nsofroniew/opt/anaconda3/envs/chem/lib/python3.9/multiprocessing/spawn.py", line 134, in _check_not_importing_main
    raise RuntimeError('''
RuntimeError:
        An attempt has been made to start a new process before the
        current process has finished its bootstrapping phase.

        This probably means that you are not using fork to start your
        child processes and you have forgotten to use the proper idiom
        in the main module:

            if __name__ == '__main__':
                freeze_support()
                ...

        The "freeze_support()" line can be omitted if the program
        is not going to be frozen to produce an executable.

    This can be fixed by wrapping the creation and running of the JANUS agent and inside

    if __name__ == '__main__':
    torch.multiprocessing.freeze_support()

    see for a similar fix https://github.com/pytorch/pytorch/issues/5858#issuecomment-373950687

    I'm happy to submit a PR to fix if you like - it will be very simple

    opened by sofroniewn 4
  • Enquiring on multi-objective fitness function

    Enquiring on multi-objective fitness function

    Hi, I would like to ask if there are multiple objectives which I want the fitness function to fulfil, how would I write out the function because the example on the README.md is only for one objective (logP)?

    Thank you! :D

    opened by yipy0005 3
  • error in numpy/ list multiplication inside mutate_smi_list

    error in numpy/ list multiplication inside mutate_smi_list

    Hello, I am trying to run the provided example, but get the following error

    $ python ./example.py
    Unique and valid fragments generated: 107308
    Unique and valid fragments generated: 107308
On generation 0/200
/Users/nsofroniew/opt/anaconda3/envs/chem/lib/python3.9/site-packages/janus/janus.py:457: RuntimeWarning: overflow encountered in power
  prob_ = 1.0 / (3.0 ** ((F_50_val - fitness) / (F_50_val - F_25_val)) + 1)
    (Explr) Top Fitness: 15.811199999999957
    (Explr) Top Smile: CCCCCCCCCCCCCCCCOP(=O)(O)Oc1ccc(C=Cc2ccc(OP(=O)(O)OCCCCCCCCCCCCCCCC)cc2)cc1
Traceback (most recent call last):
  File "/Users/nsofroniew/Documents/code/chem/janus/tests/./example.py", line 81, in <module>
  File "/Users/nsofroniew/opt/anaconda3/envs/chem/lib/python3.9/site-packages/janus/janus.py", line 317, in run
    mut_smi_loc = self.mutate_smi_list(smiles_local_search, "local")
  File "/Users/nsofroniew/opt/anaconda3/envs/chem/lib/python3.9/site-packages/janus/janus.py", line 137, in mutate_smi_list
    smi_list = smi_list * num_random_samples
numpy.core._exceptions._UFuncNoLoopError: ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U98'), dtype('int64')) -> None

    It looks like smi_list has become a numpy array, which is unintended and it should be a list. This can be fixed by making this line https://github.com/aspuru-guzik-group/JANUS/blob/a52e5994a108063e3fc1d692752cea0ff0240120/src/janus/janus.py#L137 be

        smi_list = list(smi_list) * num_random_samples

    There could be other, more desirable fixes that avoid this problem altogether. I am happy to submit a PR if this fix is desired though.

    opened by sofroniewn 2
  • Unhandled exceptions and KeyError

    Unhandled exceptions and KeyError

    I tried running JANUS.py but got a number of exceptions. In addition, the script terminated with a KeyError.

    Initial population obtained!
Forming Fragments!
    Fragment creation: 0/10000
    Fragment creation: 1000/10000
    Fragment creation: 2000/10000
    Fragment creation: 3000/10000
    Fragment creation: 4000/10000
    Fragment creation: 5000/10000
    Fragment creation: 6000/10000
    Fragment creation: 7000/10000
    Fragment creation: 8000/10000
    Fragment creation: 9000/10000
Process Process-5:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch3_1]'
	SELFIES: [S][C][=N][N][=C][Branch1][Ring1][C][C][C][Branch1][#Branch1][O][C][Branch1][C][C][=O][C][Branch1][C][C][Branch1][C][C][C][N][N][N][Branch3_1][C][C][=C][=C][Branch1][C][N][C][=C][Ring1][#Branch1][C][#Branch1][N]
Process Process-7:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 124, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Expl=Ring3]'
	SELFIES: [C][Expl=Ring3][=C][Branch2][Ring1][=Branch1][C][=C][C][=C][Branch1][#C][C][=C][Ring1][=Branch1][C][=C][C][=C][C][=C][Ring1][=Branch1][Ring1][=C][F][C][Branch1][C][C][C][C][C][N][Branch1][=Branch2][S][Branch1][C][C][=Branch1][C][=O][=O][C][C][Ring1][#Branch2][C][N][Branch1][Branch1][C][C][C][C][C][C][C][C]
Process Process-4:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch1_3]'
	SELFIES: [C][C][=C][Branch1][=Branch1][C][C][=Ring1][=Branch1][Branch1_3][C][C][=C][C][=C][Branch1][C][C][=C][C][=C][Branch1][C][N][C][=N][Ring1][#Branch1][#Branch2][C][N][C][O][C][C][Ring1][=Branch1][C][Branch1][C][O][=C][C][=C][Ring1][=C][O][Ring1][P]
Process Process-6:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch3_2]'
	SELFIES: [C][C][=Branch1][#C][=C][C][=C][C][=Ring1][=Branch1][C][Branch1][C][F][Branch1][C][F][F][C][C][Branch1][C][C][=N][N][C][=Branch1][C][C][C][N][C][C][C][Branch1][C][N][C][C][Ring1][#Branch1][C][O][=C][C][Branch1][O][C][Branch3_2][C][N][C][C][O][C][C][Ring1][=Branch1][=O]
Process Process-8:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch2_1]'
	SELFIES: [C][=Branch1][C][=O][Branch1][C][O][C][N][C][=Branch1][C][=O][C][Branch2][Ring1][=Branch1][N][C][=Branch1][C][=O][C][Branch1][N][C][=C][C][=C][C][Branch2_1][Ring2][=N][Ring1][=Branch1][N][=N][O][C][Ring2][Ring1][C][S][C][C][=Ring2][Ring1][=Branch1][S][C][S][N][=C][Branch1][Ring2][N][=Ring1][Branch1][S][C][C][N]
Process Process-11:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch2_3]'
	SELFIES: [C][C][=C][C][Branch1][=C][C][N][Branch1][C][C][N][C][=Branch1][C][=O][C][S][C][C][C][Ring1][#Branch1][=C][C][=Ring1][O][C][=C][C][=C][C][=C][Ring1][=Branch1][O][C][=C][Branch2_3][Branch1]
Process Process-10:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch3_3]'
	SELFIES: [F][C][=C][C][=C][Branch2][Ring2][O][C][N][C][Branch2][Ring2][Ring2][C][Branch1][#C][C][C][=C][Branch1][=Branch2][C][=C][C][=C][C][=Branch1][C][=O][N][Branch1][C][C][Branch3_3][C][Branch1][C][F][C][=Ring1][#Branch1][F][=N][C][C][Ring1][C][N][C][C][N][C][C][Ring1][=Branch1][=C][=N][C][=Branch1][Branch1][=N][C][=Ring1][=Branch1][N][Branch1][C][C][C][=O][C][=C][Ring2][Ring1][=N]
Process Process-9:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 116, in _derive_mol_from_symbols
    init_state=binit_state, root_atom=prev_atom, rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch3_3]'
	SELFIES: [C][C][Branch1][#Branch2][C][=C][C][=Branch1][Ring2][=C][=Branch1][F][=N][C][=C][Branch2][Ring2][Branch1][N][Branch1][Branch2][C][=N][C][Ring1][=Branch1][=Ring1][=C][N][=C][C][=C][C][=C][Branch1][P][C][=Branch1][Ring2][=C][Ring1][=Branch1][C][Branch3_3][C][N][=C][C][=C][C][=Ring1][=Branch1][O][C][O]
On generation 0/200
    (Explr) Top Fitness: 1.0
    (Explr) Top Smile: C=C1N=CC=C(N=CNc2ccc(N)cc2)N=C(C)[SH]1C
Process Process-27:
Traceback (most recent call last):
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 297, in _bootstrap
    self.run()
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/multiprocessing/process.py", line 99, in run
    self._target(*self._args, **self._kwargs)
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 205, in calc_parr_prop
    props_collect[property_name][smile] = get_prop_material(smile, alphabet=alphabet, num_random_samples=num_random_samples, num_mutations=num_mutations)  # TODO: TESTING
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in get_prop_material
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/software/JANUS/mutate_parr.py", line 129, in 
    mutated_smiles = [decoder(x) for x in mutated_sf]
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 59, in decoder
    rings=rings
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 147, in _derive_mol_from_symbols
    _raise_decoder_error(selfies, symbol)
  File "/home/ubuntu/anaconda3/envs/reinvent.v3.2/lib/python3.7/site-packages/selfies/decoder.py", line 179, in _raise_decoder_error
    raise DecoderError(err_msg)
selfies.exceptions.DecoderError: invalid symbol '[Branch3_2]'
	SELFIES: [C][O][=C][N][C][N][C][=Branch1][C][=O][N][Branch1][=Branch1][N+1][=Branch1][C][=O][O-1][C][Ring1][=Branch2][N][Ring1][N][O][C][=C][C][C][N][C][N][C][N][C][=C][C][=C][Branch1][C][F][C][Branch1][C][F][=C][Ring1][Branch2][=N][C][Branch1][C][C][Branch3_2][Branch1][=Branch1][C][Branch1][C][C][=O][S][Ring1][=Branch2][=C][C][=Ring1][#Branch1][N][C][N][C][C][=C][C][=C][C][=C][Ring1][=Branch1][C][N][=C][Branch1][=C][SH1][Branch1][C][C][C][=C][C][=C][C][=C][Ring1][=Branch1][=Branch1][C][=C][N][=C][C][=Ring1][#Branch2][C]
Traceback (most recent call last):
  File "./JANUS.py", line 308, in 
    mut_smi_dict_local  = mut_smi_dict_local[population[top_idx]]
KeyError: 'C=C1N=CC=C(N=CNc2ccc(N)cc2)N=C(C)[SH]1C'
    opened by PatWalters 2
  • multiprocessing in windows

    multiprocessing in windows

    Hi. I was run the code, but I met errors in all codes that used multiprocessing. As I know these errors came from the difference of OS.

    Since I use Windows, I wonder how to correct the code for Windows.

    Thanks.

    opened by gunwook12 1

  • "aux" folder name should be changed to make the repository compatible with Windows.

    It looks like "aux" is a reserved word in Windows and directory of this name cannot be used. This is causing error, when I try to clone the repository.

    opened by sptiwari 1
  • Question: How sensitive is the model to molecule initialization?

    Question: How sensitive is the model to molecule initialization?

    Hello, great work! I'm excited to try this out for a chemical design project I'm working on. One question that I had after reading the pre-print— how sensitive is the model to molecule initialization?

    I read that you can start JANUS with random molecules or provide it with defined molecules. Did you perform any tests on what happens if the best molecule's scaffold was ablated from the initial bank of molecules? And how much, if at all, does rational initialization improve over random molecular initialization? Does this relate back to being trapped in local minima, and would the choice of initialization help explore more chemical space?

    Thank you!

    question 
    opened by jrhorne 1
Releases(v1)
Owner
Aspuru-Guzik group repo
Aspuru-Guzik group repo
GitHub Repository
AnimationKit: AI Upscaling & Interpolation using Real-ESRGAN+RIFE

ALPHA 2.5: Frostbite Revival (Released 12/23/21) Changelog: [ UI ] Chained design. All steps link to one another! Use the master override toggles to s

87 Nov 16, 2022
Deeplearning project at The Technological University of Denmark (DTU) about Neural ODEs for finding dynamics in ordinary differential equations and real world time series data

Authors Marcus Lenler Garsdal, [email protected] Valdemar Søgaard, Simon Moe Sørensen 6 Sep 05, 2022

Confident Semantic Ranking Loss for Part Parsing

Confident Semantic Ranking Loss for Part Parsing

Jiachen Xu 5 Oct 22, 2022
DIVeR: Deterministic Integration for Volume Rendering

DIVeR: Deterministic Integration for Volume Rendering This repo contains the training and evaluation code for DIVeR. Setup python 3.8 pytorch 1.9.0 py

64 Dec 27, 2022
Open Source Differentiable Computer Vision Library for PyTorch

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer

kornia 7.6k Jan 04, 2023
YOLO-v5 기반 단안 카메라의 영상을 활용해 차간 거리를 일정하게 유지하며 주행하는 Adaptive Cruise Control 기능 구현

자율 주행차의 영상 기반 차간거리 유지 개발 Table of Contents 프로젝트 소개 주요 기능 시스템 구조 디렉토리 구조 결과 실행 방법 참조 팀원 프로젝트 소개 YOLO-v5 기반으로 단안 카메라의 영상을 활용해 차간 거리를 일정하게 유지하며 주행하는 Adap

14 Jun 29, 2022
PyTorch implementation of Deformable Convolution

PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple

Wei Ouyang 893 Dec 18, 2022
ESP32 python application to read data from a Tilt™ Hydrometer for homebrewing

TitlESP32 ESP32 MicroPython application to read and log data from a Tilt™ Hydrometer. Requirements A board with an ESP32 chip USB cable - USB A / micr

IoBeer 5 Dec 01, 2022
library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization

NLopt is a library for nonlinear local and global optimization, for functions with and without gradient information. It is designed as a simple, unifi

Steven G. Johnson 1.4k Dec 25, 2022
This repository contains the code for "Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP".

Self-Diagnosis and Self-Debiasing This repository contains the source code for Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based

Timo Schick 62 Dec 12, 2022
End-to-End Object Detection with Fully Convolutional Network

This project provides an implementation for "End-to-End Object Detection with Fully Convolutional Network" on PyTorch.

472 Dec 22, 2022
Scenarios, tutorials and demos for Autonomous Driving

The Autonomous Driving Cookbook (Preview) NOTE: This project is developed and being maintained by Project Road Runner at Microsoft Garage. This is cur

Microsoft 2.1k Jan 02, 2023
Collection of TensorFlow2 implementations of Generative Adversarial Network varieties presented in research papers.

TensorFlow2-GAN Collection of tf2.0 implementations of Generative Adversarial Network varieties presented in research papers. Model architectures will

41 Apr 28, 2022
TAP: Text-Aware Pre-training for Text-VQA and Text-Caption, CVPR 2021 (Oral)

TAP: Text-Aware Pre-training TAP: Text-Aware Pre-training for Text-VQA and Text-Caption by Zhengyuan Yang, Yijuan Lu, Jianfeng Wang, Xi Yin, Dinei Flo

Microsoft 61 Nov 14, 2022
The Empirical Investigation of Representation Learning for Imitation (EIRLI)

The Empirical Investigation of Representation Learning for Imitation (EIRLI)

Center for Human-Compatible AI 31 Nov 06, 2022
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).

GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation [OpenReview] [arXiv] [Code] The official implementation of GeoDiff: A Geome

Minkai Xu 155 Dec 26, 2022
Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js

Start-to-finish tutorial for interactive music co-creation in PyTorch and Tensorflow.js

Chris Donahue 98 Dec 14, 2022
A Pytorch loader for MVTecAD dataset.

MVTecAD A Pytorch loader for MVTecAD dataset. It strictly follows the code style of common Pytorch datasets, such as torchvision.datasets.CIFAR10. The

Jiyuan 1 Dec 27, 2021
Article Reranking by Memory-enhanced Key Sentence Matching for Detecting Previously Fact-checked Claims.

MTM This is the official repository of the paper: Article Reranking by Memory-enhanced Key Sentence Matching for Detecting Previously Fact-checked Cla

ICTMCG 13 Sep 17, 2022
Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3

Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are

Paul Zivich 120 Nov 17, 2022