gt4sd.algorithms.registry module¶

Collection of available methods.

Summary¶

Classes:

`AlgorithmApplication`	Collect all needed to run an application.
`AnnotationTuple`
`ApplicationsRegistry`	Registry to collect "applications" and make them accessible.
`ConfigurationTuple`	Attributes to uniquely describe an AlgorithmConfiguration.
`RegistryDict`	Dict that raises when reassigning an existing key.

Reference¶

class ConfigurationTuple(algorithm_type: str, domain: str, algorithm_name: str, algorithm_application: str)[source]¶

Bases: NamedTuple

Attributes to uniquely describe an AlgorithmConfiguration.

algorithm_type: str¶: Alias for field number 0

domain: str¶: Alias for field number 1

algorithm_name: str¶: Alias for field number 2

algorithm_application: str¶: Alias for field number 3

__annotations__ = {'algorithm_application': <class 'str'>, 'algorithm_name': <class 'str'>, 'algorithm_type': <class 'str'>, 'domain': <class 'str'>}¶

__doc__ = 'Attributes to uniquely describe an AlgorithmConfiguration.'¶

__getnewargs__()¶: Return self as a plain tuple. Used by copy and pickle.

__match_args__ = ('algorithm_type', 'domain', 'algorithm_name', 'algorithm_application')¶

__module__ = 'gt4sd.algorithms.registry'¶

__orig_bases__ = (<function NamedTuple>,)¶

__repr__()¶: Return a nicely formatted representation string

__slots__ = ()¶

_asdict()¶: Return a new dict which maps field names to their values.

_field_defaults = {}¶

_fields = ('algorithm_type', 'domain', 'algorithm_name', 'algorithm_application')¶

classmethod _make(iterable)¶: Make a new ConfigurationTuple object from a sequence or iterable

_replace(**kwds)¶: Return a new ConfigurationTuple object replacing specified fields with new values

class AnnotationTuple(annotation, default_value)[source]¶

Bases: NamedTuple

annotation: type¶: Alias for field number 0

default_value: Any¶: Alias for field number 1

__annotations__ = {'annotation': <class 'type'>, 'default_value': typing.Any}¶

__doc__ = 'AnnotationTuple(annotation, default_value)'¶

__getnewargs__()¶: Return self as a plain tuple. Used by copy and pickle.

__match_args__ = ('annotation', 'default_value')¶

__module__ = 'gt4sd.algorithms.registry'¶

__orig_bases__ = (<function NamedTuple>,)¶

__repr__()¶: Return a nicely formatted representation string

__slots__ = ()¶

_asdict()¶: Return a new dict which maps field names to their values.

_field_defaults = {}¶

_fields = ('annotation', 'default_value')¶

classmethod _make(iterable)¶: Make a new AnnotationTuple object from a sequence or iterable

_replace(**kwds)¶: Return a new AnnotationTuple object replacing specified fields with new values

class AlgorithmApplication(algorithm_class, configuration_class, parameters_dict=<factory>)[source]¶

Bases: object

Collect all needed to run an application.

algorithm_class: Type[GeneratorAlgorithm]¶

configuration_class: Type[AlgorithmConfiguration]¶

parameters_dict: Dict[str, AnnotationTuple]¶

__annotations__ = {'algorithm_class': typing.Type[gt4sd.algorithms.core.GeneratorAlgorithm], 'configuration_class': typing.Type[gt4sd.algorithms.core.AlgorithmConfiguration], 'parameters_dict': typing.Dict[str, gt4sd.algorithms.registry.AnnotationTuple]}¶

__dataclass_fields__ = {'algorithm_class': Field(name='algorithm_class',type=typing.Type[gt4sd.algorithms.core.GeneratorAlgorithm],default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'configuration_class': Field(name='configuration_class',type=typing.Type[gt4sd.algorithms.core.AlgorithmConfiguration],default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'parameters_dict': Field(name='parameters_dict',type=typing.Dict[str, gt4sd.algorithms.registry.AnnotationTuple],default=<dataclasses._MISSING_TYPE object>,default_factory=<class 'dict'>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD)}¶

__dataclass_params__ = _DataclassParams(init=True,repr=True,eq=True,order=False,unsafe_hash=False,frozen=False)¶

__dict__ = mappingproxy({'__module__': 'gt4sd.algorithms.registry', '__annotations__': {'algorithm_class': typing.Type[gt4sd.algorithms.core.GeneratorAlgorithm], 'configuration_class': typing.Type[gt4sd.algorithms.core.AlgorithmConfiguration], 'parameters_dict': typing.Dict[str, gt4sd.algorithms.registry.AnnotationTuple]}, '__doc__': 'Collect all needed to run an application.', '__dict__': <attribute '__dict__' of 'AlgorithmApplication' objects>, '__weakref__': <attribute '__weakref__' of 'AlgorithmApplication' objects>, '__dataclass_params__': _DataclassParams(init=True,repr=True,eq=True,order=False,unsafe_hash=False,frozen=False), '__dataclass_fields__': {'algorithm_class': Field(name='algorithm_class',type=typing.Type[gt4sd.algorithms.core.GeneratorAlgorithm],default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'configuration_class': Field(name='configuration_class',type=typing.Type[gt4sd.algorithms.core.AlgorithmConfiguration],default=<dataclasses._MISSING_TYPE object>,default_factory=<dataclasses._MISSING_TYPE object>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD), 'parameters_dict': Field(name='parameters_dict',type=typing.Dict[str, gt4sd.algorithms.registry.AnnotationTuple],default=<dataclasses._MISSING_TYPE object>,default_factory=<class 'dict'>,init=True,repr=True,hash=None,compare=True,metadata=mappingproxy({}),kw_only=False,_field_type=_FIELD)}, '__init__': <function AlgorithmApplication.__init__>, '__repr__': <function AlgorithmApplication.__repr__>, '__eq__': <function AlgorithmApplication.__eq__>, '__hash__': None, '__match_args__': ('algorithm_class', 'configuration_class', 'parameters_dict')})¶

__doc__ = 'Collect all needed to run an application.'¶

__eq__(other)¶: Return self==value.

__hash__ = None¶

__init__(algorithm_class, configuration_class, parameters_dict=<factory>)¶

__match_args__ = ('algorithm_class', 'configuration_class', 'parameters_dict')¶

__module__ = 'gt4sd.algorithms.registry'¶

__repr__()¶: Return repr(self).

__weakref__¶: list of weak references to the object (if defined)

class RegistryDict[source]¶

Bases: Dict[ConfigurationTuple, AlgorithmApplication]

Dict that raises when reassigning an existing key.

__setitem__(key, value)[source]¶: Set self[key] to value.

__annotations__ = {}¶

__dict__ = mappingproxy({'__module__': 'gt4sd.algorithms.registry', '__doc__': 'Dict that raises when reassigning an existing key.', '__setitem__': <function RegistryDict.__setitem__>, '__orig_bases__': (typing.Dict[gt4sd.algorithms.registry.ConfigurationTuple, gt4sd.algorithms.registry.AlgorithmApplication],), '__dict__': <attribute '__dict__' of 'RegistryDict' objects>, '__weakref__': <attribute '__weakref__' of 'RegistryDict' objects>, '__parameters__': (), '__annotations__': {}})¶

__doc__ = 'Dict that raises when reassigning an existing key.'¶

__module__ = 'gt4sd.algorithms.registry'¶

__orig_bases__ = (typing.Dict[gt4sd.algorithms.registry.ConfigurationTuple, gt4sd.algorithms.registry.AlgorithmApplication],)¶

__parameters__ = ()¶

__weakref__¶: list of weak references to the object (if defined)

class ApplicationsRegistry[source]¶

Bases: object

Registry to collect “applications” and make them accessible.

An application denotes the combination of an AlgorithmConfiguration and a GeneratorAlgorithm.

applications: RegistryDict = {ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='GraphGAGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GraphGAGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='GraphMCTSGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GraphMCTSGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='SMILESGAGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.SMILESGAGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='SMILESLSTMHCGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.SMILESLSTMHCGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='SMILESLSTMPPOGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.SMILESLSTMPPOGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MolGX', algorithm_application='MolGXQM9Generator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.molgx.core.MolGX'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.molgx.core.MolGXQM9Generator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MosesGenerator', algorithm_application='AaeGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.MosesGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.AaeGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MosesGenerator', algorithm_application='OrganGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.MosesGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.OrganGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MosesGenerator', algorithm_application='VaeGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.MosesGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.VaeGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='PaccMannRL', algorithm_application='PaccMannRLOmicBasedGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRL'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRLOmicBasedGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='PaccMannRL', algorithm_application='PaccMannRLProteinBasedGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRL'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRLProteinBasedGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='RegressionTransformer', algorithm_application='RegressionTransformerMolecules'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformer'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformerMolecules'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='RegressionTransformer', algorithm_application='RegressionTransformerProteins'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformer'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformerProteins'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='Reinvent', algorithm_application='ReinventGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.reinvent.core.Reinvent'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.reinvent.core.ReinventGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='Template', algorithm_application='TemplateGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.template.core.Template'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.template.core.TemplateGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='nlp', algorithm_name='KeywordBERTGenerationAlgorithm', algorithm_application='KeyBERTGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.key_bert.core.KeywordBERTGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.key_bert.core.KeyBERTGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='controlled_sampling', domain='materials', algorithm_name='AdvancedManufacturing', algorithm_application='CatalystGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.controlled_sampling.advanced_manufacturing.core.AdvancedManufacturing'>, configuration_class=<class 'gt4sd.algorithms.controlled_sampling.advanced_manufacturing.core.CatalystGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='controlled_sampling', domain='materials', algorithm_name='PaccMannGP', algorithm_application='PaccMannGPGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.controlled_sampling.paccmann_gp.core.PaccMannGP'>, configuration_class=<class 'gt4sd.algorithms.controlled_sampling.paccmann_gp.core.PaccMannGPGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='MoLeR', algorithm_application='MoLeRDefaultGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.moler.core.MoLeR'>, configuration_class=<class 'gt4sd.algorithms.generation.moler.core.MoLeRDefaultGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='PaccMannVAE', algorithm_application='PaccMannVAEGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.paccmann_vae.core.PaccMannVAE'>, configuration_class=<class 'gt4sd.algorithms.generation.paccmann_vae.core.PaccMannVAEGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='PolymerBlocks', algorithm_application='PolymerBlocksGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.polymer_blocks.core.PolymerBlocks'>, configuration_class=<class 'gt4sd.algorithms.generation.polymer_blocks.core.PolymerBlocksGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='TorchDrugGenerator', algorithm_application='TorchDrugGCPN'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGenerator'>, configuration_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGCPN'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='TorchDrugGenerator', algorithm_application='TorchDrugGraphAF'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGenerator'>, configuration_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGraphAF'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceCTRLGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceCTRLGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceConfiguration'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceConfiguration'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceGPT2Generator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGPT2Generator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceOpenAIGPTGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceOpenAIGPTGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceSeq2SeqGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceSeq2SeqGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceTransfoXLGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceTransfoXLGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceXLMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceXLMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceXLNetGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceXLNetGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTAlgorithmConfiguration'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTAlgorithmConfiguration'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTCoherenceChecker'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTCoherenceChecker'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTEditor'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTEditor'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='DDIMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.DDIMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='DDPMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.DDPMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='DiffusersConfiguration'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersConfiguration'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='GeoDiffGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.GeoDiffGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='LDMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.LDMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='LDMTextToImageGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.LDMTextToImageGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='ScoreSdeGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.ScoreSdeGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='StableDiffusionGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.StableDiffusionGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='prediction', domain='materials', algorithm_name='PaccMann', algorithm_application='AffinityPredictor'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.prediction.paccmann.core.PaccMann'>, configuration_class=<class 'gt4sd.algorithms.prediction.paccmann.core.AffinityPredictor'>, parameters_dict={}), ConfigurationTuple(algorithm_type='prediction', domain='nlp', algorithm_name='TopicsZeroShot', algorithm_application='TopicsPredictor'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.prediction.topics_zero_shot.core.TopicsZeroShot'>, configuration_class=<class 'gt4sd.algorithms.prediction.topics_zero_shot.core.TopicsPredictor'>, parameters_dict={})}¶

classmethod _register_application(algorithm_class, algorithm_configuration_class)[source]¶

classmethod register_algorithm_application(algorithm_class, as_algorithm_application=None)[source]¶

Complete and register a configuration via decoration.

Parameters

algorithm_class (Type[GeneratorAlgorithm]) – The algorithm that uses the configuration.
as_algorithm_application (Optional[str, None]) – Optional application name to use instead of the configurations class name.

Return type

Callable[[Type[AlgorithmConfiguration]], Type[AlgorithmConfiguration]]

Returns

A function to complete the configuration class’ attributes to reflect the matching GeneratorAlgorithm and application. The final class is registered and returned.

Example

as decorator:

from gt4sd.algorithms.registry import ApplicationsRegistry


@ApplicationsRegistry.register_algorithm_application(SomeAlgorithm)
class SomeApplication(AlgorithmConfiguration):
    algorithm_type: ClassVar[str] = 'conditional_generation'
    domain: ClassVar[str] = 'materials'
    algorithm_version: str = 'v0'

    some_more_serializable_arguments_with_defaults: int = 42

Example

directly, here for an additional algorithm application with the same algorithm:

AnotherApplication = ApplicationsRegistry.register_algorithm_application(
    SomeAlgorithm, 'AnotherApplication'
)(SomeApplication)

static configuration_class_as_tuple(algorithm_configuration_class)[source]¶

Get a hashable identifier per application.

Return type: ConfigurationTuple

classmethod get_application(algorithm_type, domain, algorithm_name, algorithm_application)[source]¶

Return type: AlgorithmApplication

classmethod get_matching_configuration_defaults(algorithm_type, domain, algorithm_name, algorithm_application)[source]¶

Return type: Dict[str, AnnotationTuple]

classmethod get_matching_configuration_schema(algorithm_type, domain, algorithm_name, algorithm_application)[source]¶

Return type: Dict[str, Any]

classmethod get_configuration_instance(algorithm_type, domain, algorithm_name, algorithm_application, *args, **kwargs)[source]¶

Create an instance of the matching AlgorithmConfiguration from the ApplicationsRegistry.

Parameters

algorithm_type (str) – general type of generative algorithm.
domain (str) – general application domain. Hints at input/output types.
algorithm_name (str) – name of the algorithm to use with this configuration.
algorithm_application (str) – unique name for the application that is the use of this configuration together with a specific algorithm.
algorithm_version – to differentiate between different versions of an application.
*args – additional positional arguments passed to the configuration.
**kwargs – additional keyword arguments passed to the configuration.

Return type

AlgorithmConfiguration

Returns

an instance of the configuration.

classmethod get_application_instance(algorithm_type, domain, algorithm_name, algorithm_application, target=None, **kwargs)[source]¶

Instantiate an algorithm via a matching application from the ApplicationsRegistry.

Additional arguments are passed to the configuration and override any arguments in the ApplicationsRegistry.

Parameters

algorithm_type (str) – general type of generative algorithm.
domain (str) – general application domain. Hints at input/output types.
algorithm_name (str) – name of the algorithm to use with this configuration.
algorithm_application (str) – unique name for the application that is the use of this configuration together with a specific algorithm.
algorithm_version – to differentiate between different versions of an application.
target (Optional[Any, None]) – optional context or condition for the generation.
**kwargs – additional keyword arguments passed to the configuration.

Return type

GeneratorAlgorithm

Returns

an instance of a generative algorithm ready to sample from.

classmethod list_available()[source]¶

Return type: List[Dict[str, str]]

__annotations__ = {'applications': <class 'gt4sd.algorithms.registry.RegistryDict'>}¶

__dict__ = mappingproxy({'__module__': 'gt4sd.algorithms.registry', '__annotations__': {'applications': <class 'gt4sd.algorithms.registry.RegistryDict'>}, '__doc__': 'Registry to collect "applications" and make them accessible.\n\n An application denotes the combination of an\n :class:`AlgorithmConfiguration<gt4sd.algorithms.core.AlgorithmConfiguration>` and a\n :class:`GeneratorAlgorithm<gt4sd.algorithms.core.GeneratorAlgorithm>`.\n ', 'applications': {ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='SMILESGAGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.SMILESGAGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='GraphGAGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GraphGAGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='GraphMCTSGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GraphMCTSGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='SMILESLSTMHCGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.SMILESLSTMHCGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='GuacaMolGenerator', algorithm_application='SMILESLSTMPPOGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.GuacaMolGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.SMILESLSTMPPOGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MosesGenerator', algorithm_application='AaeGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.MosesGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.AaeGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MosesGenerator', algorithm_application='VaeGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.MosesGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.VaeGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MosesGenerator', algorithm_application='OrganGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.MosesGenerator'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.guacamol.core.OrganGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='nlp', algorithm_name='KeywordBERTGenerationAlgorithm', algorithm_application='KeyBERTGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.key_bert.core.KeywordBERTGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.key_bert.core.KeyBERTGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='MolGX', algorithm_application='MolGXQM9Generator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.molgx.core.MolGX'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.molgx.core.MolGXQM9Generator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='PaccMannRL', algorithm_application='PaccMannRLProteinBasedGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRL'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRLProteinBasedGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='PaccMannRL', algorithm_application='PaccMannRLOmicBasedGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRL'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.paccmann_rl.core.PaccMannRLOmicBasedGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='RegressionTransformer', algorithm_application='RegressionTransformerMolecules'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformer'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformerMolecules'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='RegressionTransformer', algorithm_application='RegressionTransformerProteins'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformer'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.regression_transformer.core.RegressionTransformerProteins'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='Reinvent', algorithm_application='ReinventGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.reinvent.core.Reinvent'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.reinvent.core.ReinventGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='conditional_generation', domain='materials', algorithm_name='Template', algorithm_application='TemplateGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.conditional_generation.template.core.Template'>, configuration_class=<class 'gt4sd.algorithms.conditional_generation.template.core.TemplateGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='controlled_sampling', domain='materials', algorithm_name='AdvancedManufacturing', algorithm_application='CatalystGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.controlled_sampling.advanced_manufacturing.core.AdvancedManufacturing'>, configuration_class=<class 'gt4sd.algorithms.controlled_sampling.advanced_manufacturing.core.CatalystGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='controlled_sampling', domain='materials', algorithm_name='PaccMannGP', algorithm_application='PaccMannGPGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.controlled_sampling.paccmann_gp.core.PaccMannGP'>, configuration_class=<class 'gt4sd.algorithms.controlled_sampling.paccmann_gp.core.PaccMannGPGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='DiffusersConfiguration'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersConfiguration'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='DDPMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.DDPMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='DDIMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.DDIMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='LDMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.LDMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='ScoreSdeGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.ScoreSdeGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='LDMTextToImageGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.LDMTextToImageGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='StableDiffusionGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.StableDiffusionGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='vision', algorithm_name='DiffusersGenerationAlgorithm', algorithm_application='GeoDiffGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.diffusion.core.DiffusersGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.diffusion.core.GeoDiffGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceConfiguration'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceConfiguration'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceXLMGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceXLMGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceCTRLGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceCTRLGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceGPT2Generator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGPT2Generator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceOpenAIGPTGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceOpenAIGPTGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceXLNetGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceXLNetGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceTransfoXLGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceTransfoXLGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='HuggingFaceGenerationAlgorithm', algorithm_application='HuggingFaceSeq2SeqGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceGenerationAlgorithm'>, configuration_class=<class 'gt4sd.algorithms.generation.hugging_face.core.HuggingFaceSeq2SeqGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='MoLeR', algorithm_application='MoLeRDefaultGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.moler.core.MoLeR'>, configuration_class=<class 'gt4sd.algorithms.generation.moler.core.MoLeRDefaultGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTAlgorithmConfiguration'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTAlgorithmConfiguration'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTEditor'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTEditor'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='nlp', algorithm_name='PGT', algorithm_application='PGTCoherenceChecker'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.pgt.core.PGT'>, configuration_class=<class 'gt4sd.algorithms.generation.pgt.core.PGTCoherenceChecker'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='PolymerBlocks', algorithm_application='PolymerBlocksGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.polymer_blocks.core.PolymerBlocks'>, configuration_class=<class 'gt4sd.algorithms.generation.polymer_blocks.core.PolymerBlocksGenerator'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='TorchDrugGenerator', algorithm_application='TorchDrugGCPN'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGenerator'>, configuration_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGCPN'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='TorchDrugGenerator', algorithm_application='TorchDrugGraphAF'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGenerator'>, configuration_class=<class 'gt4sd.algorithms.generation.torchdrug.core.TorchDrugGraphAF'>, parameters_dict={}), ConfigurationTuple(algorithm_type='prediction', domain='materials', algorithm_name='PaccMann', algorithm_application='AffinityPredictor'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.prediction.paccmann.core.PaccMann'>, configuration_class=<class 'gt4sd.algorithms.prediction.paccmann.core.AffinityPredictor'>, parameters_dict={}), ConfigurationTuple(algorithm_type='prediction', domain='nlp', algorithm_name='TopicsZeroShot', algorithm_application='TopicsPredictor'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.prediction.topics_zero_shot.core.TopicsZeroShot'>, configuration_class=<class 'gt4sd.algorithms.prediction.topics_zero_shot.core.TopicsPredictor'>, parameters_dict={}), ConfigurationTuple(algorithm_type='generation', domain='materials', algorithm_name='PaccMannVAE', algorithm_application='PaccMannVAEGenerator'): AlgorithmApplication(algorithm_class=<class 'gt4sd.algorithms.generation.paccmann_vae.core.PaccMannVAE'>, configuration_class=<class 'gt4sd.algorithms.generation.paccmann_vae.core.PaccMannVAEGenerator'>, parameters_dict={})}, '_register_application': <classmethod(<function ApplicationsRegistry._register_application>)>, 'register_algorithm_application': <classmethod(<function ApplicationsRegistry.register_algorithm_application>)>, 'configuration_class_as_tuple': <staticmethod(<function ApplicationsRegistry.configuration_class_as_tuple>)>, 'get_application': <classmethod(<function ApplicationsRegistry.get_application>)>, 'get_matching_configuration_defaults': <classmethod(<function ApplicationsRegistry.get_matching_configuration_defaults>)>, 'get_matching_configuration_schema': <classmethod(<function ApplicationsRegistry.get_matching_configuration_schema>)>, 'get_configuration_instance': <classmethod(<function ApplicationsRegistry.get_configuration_instance>)>, 'get_application_instance': <classmethod(<function ApplicationsRegistry.get_application_instance>)>, 'list_available': <classmethod(<function ApplicationsRegistry.list_available>)>, '__dict__': <attribute '__dict__' of 'ApplicationsRegistry' objects>, '__weakref__': <attribute '__weakref__' of 'ApplicationsRegistry' objects>})¶

__doc__ = 'Registry to collect "applications" and make them accessible.\n\n An application denotes the combination of an\n :class:`AlgorithmConfiguration<gt4sd.algorithms.core.AlgorithmConfiguration>` and a\n :class:`GeneratorAlgorithm<gt4sd.algorithms.core.GeneratorAlgorithm>`.\n '¶

__module__ = 'gt4sd.algorithms.registry'¶

__weakref__¶: list of weak references to the object (if defined)