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
Official implementation for "Low-light Image Enhancement via Breaking Down the Darkness"

Low-light Image Enhancement via Breaking Down the Darkness by Qiming Hu, Xiaojie Guo. 1. Dependencies Python3 PyTorch=1.0 OpenCV-Python, TensorboardX

Qiming Hu 30 Jan 01, 2023
A TensorFlow implementation of Neural Program Synthesis from Diverse Demonstration Videos

ViZDoom http://vizdoom.cs.put.edu.pl ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is pri

Hyeonwoo Noh 1 Aug 19, 2020
Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021)

Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021) Contact 0 Jan 11, 2022

FOSS Digital Asset Distribution Platform built on Frappe.

Digistore FOSS Digital Assets Marketplace. Distribute digital assets, like a pro. Video Demo Here Features Create, attach and list digital assets (PDF

Mohammad Hussain Nagaria 30 Dec 08, 2022
Scikit-learn compatible estimation of general graphical models

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

213 Jan 02, 2023
Voila - Voilà turns Jupyter notebooks into standalone web applications

Rendering of live Jupyter notebooks with interactive widgets. Introduction Voilà turns Jupyter notebooks into standalone web applications. Unlike the

Voilà Dashboards 4.5k Jan 03, 2023
A library that can print Python objects in human readable format

objprint A library that can print Python objects in human readable format Install pip install objprint Usage op Use op() (or objprint()) to print obj

319 Dec 25, 2022
Scalable, event-driven, deep-learning-friendly backtesting library

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

Andrew 922 Dec 27, 2022
View model summaries in PyTorch!

torchinfo (formerly torch-summary) Torchinfo provides information complementary to what is provided by print(your_model) in PyTorch, similar to Tensor

Tyler Yep 1.5k Jan 05, 2023
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption

⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

Lukas Hedegaard 21 Dec 22, 2022
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.

This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their

Liron Bdolah 8 May 22, 2022
PSGAN running with ncnn⚡妆容迁移/仿妆⚡Imitation Makeup/Makeup Transfer⚡

PSGAN running with ncnn⚡妆容迁移/仿妆⚡Imitation Makeup/Makeup Transfer⚡

WuJinxuan 144 Dec 26, 2022
Self-supervised spatio-spectro-temporal represenation learning for EEG analysis

EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation This repository provides a tensorflow implementation of a submitted paper: EEG-Orie

Wonjun Ko 4 Jun 09, 2022
Self-supervised Label Augmentation via Input Transformations (ICML 2020)

Self-supervised Label Augmentation via Input Transformations Authors: Hankook Lee, Sung Ju Hwang, Jinwoo Shin (KAIST) Accepted to ICML 2020 Install de

hankook 96 Dec 29, 2022
Xview3 solution - XView3 challenge, 2nd place solution

Xview3, 2nd place solution https://iuu.xview.us/ test split aggregate score publ

Selim Seferbekov 24 Nov 23, 2022
Users can free try their models on SIDD dataset based on this code

SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p

Yuzhi ZHAO 2 May 20, 2022
Fast Learning of MNL Model From General Partial Rankings with Application to Network Formation Modeling

Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN

Xingjian Zhang 3 Aug 19, 2022
Normalization Calibration (NorCal) for Long-Tailed Object Detection and Instance Segmentation

NorCal Normalization Calibration (NorCal) for Long-Tailed Object Detection and Instance Segmentation On Model Calibration for Long-Tailed Object Detec

Tai-Yu (Daniel) Pan 24 Dec 25, 2022
Ground truth data for the Optical Character Recognition of Historical Classical Commentaries.

OCR Ground Truth for Historical Commentaries The dataset OCR ground truth for historical commentaries (GT4HistComment) was created from the public dom

Ajax Multi-Commentary 3 Sep 08, 2022