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# Copyright (c) 2022 GT4SD team
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"""MoLeR Algorithm.
MoLeR generation algorithm.
"""
import logging
from dataclasses import field
from typing import Any, ClassVar, Dict, Optional, TypeVar
from ....domains.materials import SMILES, MoleculeFormat, validate_molecules
from ....exceptions import InvalidItem
from ...core import AlgorithmConfiguration, GeneratorAlgorithm, Untargeted
from ...registry import ApplicationsRegistry
from .implementation import MoLeRGenerator
logger = logging.getLogger(__name__)
logger.addHandler(logging.NullHandler())
T = type(None)
S = TypeVar("S", bound=SMILES)
[docs]class MoLeR(GeneratorAlgorithm[S, T]):
"""MoLeR Algorithm."""
[docs] def __init__(
self,
configuration: AlgorithmConfiguration[S, T],
target: Optional[T] = None,
):
"""Instantiate MoLeR ready to generate items.
Args:
configuration: domain and application
specification defining parameters, types and validations.
target: a target for which to generate items.
Example:
An example for generating small molecules (SMILES) with the default configuration:
configuration = MoLeRDefaultGenerator()
MoLeR = MoLeR(configuration=configuration, target=target)
items = list(MoLeR.sample(10))
print(items)
"""
configuration = self.validate_configuration(configuration)
# TODO there might also be a validation/check on the target input
super().__init__(
configuration=configuration, # type:ignore
target=target, # type:ignore
)
[docs] def get_generator(
self,
configuration: AlgorithmConfiguration[S, T],
target: Optional[T],
) -> Untargeted:
"""Get the function to sample batches via the MoLeRGenerator.
Args:
configuration: helps to set up the application.
target: context or condition for the generation. Unused in the algorithm.
Returns:
callable generating a batch of items.
"""
logger.info("ensure artifacts for the application are present.")
self.local_artifacts = configuration.ensure_artifacts()
implementation: MoLeRGenerator = configuration.get_conditional_generator( # type: ignore
self.local_artifacts
)
return implementation.generate
[docs] def validate_configuration(
self, configuration: AlgorithmConfiguration[S, T]
) -> AlgorithmConfiguration[S, T]:
# TODO raise InvalidAlgorithmConfiguration
assert isinstance(configuration, AlgorithmConfiguration)
return configuration
[docs]@ApplicationsRegistry.register_algorithm_application(MoLeR)
class MoLeRDefaultGenerator(AlgorithmConfiguration[SMILES, Any]):
"""Configuration to generate compounds using default parameters of MoLeR."""
algorithm_type: ClassVar[str] = "generation"
domain: ClassVar[str] = "materials"
algorithm_version: str = "v0"
scaffolds: str = field(
default="",
metadata=dict(
description="Scaffolds as '.'-separated SMILES. If empty, no scaffolds are used."
),
)
num_samples: int = field(
default=32,
metadata=dict(description="Number of molecules to sample per call."),
)
beam_size: int = field(
default=1,
metadata=dict(description="Beam size to use during decoding."),
)
seed: int = field(
default=0,
metadata=dict(description="Seed used for random number generation."),
)
num_workers: int = field(
default=6,
metadata=dict(description="Number of workers used for generation."),
)
seed_smiles: str = field(
default="",
metadata=dict(
description="Dot-separated SMILES used to initialize the encoder. If empty, random codes are used."
),
)
sigma: float = field(
default=0.0,
metadata=dict(
description="Variance of Gaussian noise being added to latent code."
),
)
[docs] def get_target_description(self) -> Optional[Dict[str, str]]:
"""Get description of the target for generation.
Returns:
target description, returns None in case no target is used.
"""
return None
[docs] def get_conditional_generator(self, resources_path: str) -> MoLeRGenerator:
"""Instantiate the actual generator implementation.
Args:
resources_path: local path to model files.
Returns:
instance with :meth:`generate<gt4sd.algorithms.generation.MoLeR.implementation.MoLeRGenerator.generate>` for generation.
"""
return MoLeRGenerator(
resources_path=resources_path,
scaffolds=self.scaffolds,
num_samples=self.num_samples,
beam_size=self.beam_size,
seed=self.seed,
num_workers=self.num_workers,
seed_smiles=self.seed_smiles,
sigma=self.sigma,
)
[docs] def validate_item(self, item: str) -> SMILES:
"""Check that item is a valid SMILES.
Args:
item: a generated item that is possibly not valid.
Raises:
InvalidItem: in case the item can not be validated.
Returns:
the validated SMILES.
"""
(
molecules,
_,
) = validate_molecules([item], MoleculeFormat.smiles)
if molecules[0] is None:
raise InvalidItem(
title="InvalidSMILES",
detail=f'rdkit.Chem.MolFromSmiles returned None for "{item}"',
)
return SMILES(item)