removed neural ontology manager

examples/neural_reasoner_retrieval.py

@@ -41,7 +41,6 @@
 
 """
 from owlapy.owl_neural_reasoners.owl_neural_reasoner import OWLNeuralReasoner
-from owlapy.owl_neural_reasoners.neural_ontology_manager import NeuralOntologyManager
 from owlapy.owl_reasoner import StructuralReasoner
 from owlapy.owl_ontology_manager import OntologyManager
 from owlapy.utils import concept_reducer, concept_reducer_properties, jaccard_similarity, f1_set_similarity
@@ -78,13 +77,9 @@ def execute(args):
     symbolic_kb = StructuralReasoner(ontology=OntologyManager().load_ontology(path=args.path_kg))
     # (2) Initialize Neural OWL Reasoner.
     if args.path_kge_model:
-        neural_manager = NeuralOntologyManager()
-        neural_manager.load_neural_embedding(path=args.path_kge_model)
-        neural_owl_reasoner = OWLNeuralReasoner(ontology=neural_manager, gamma=args.gamma)
+        neural_owl_reasoner = OWLNeuralReasoner(path_neural_embedding=args.path_kge_model, gamma=args.gamma)
     else:
-        neural_manager = NeuralOntologyManager()
-        neural_manager.load_ontology(path=args.path_kg)
-        neural_owl_reasoner = OWLNeuralReasoner(ontology=neural_manager, gamma=args.gamma)
+        neural_owl_reasoner = OWLNeuralReasoner(path_of_kb=args.path_kg, gamma=args.gamma)
     # Fix the random seed.
     random.seed(args.seed)
     ###################################################################

owlapy/owl_neural_reasoners/abstract.py

@@ -1,13 +1,11 @@
 from abc import ABC, abstractmethod
-from typing import List, Tuple, Generator, Union
+from typing import List, Tuple, Generator
 from owlapy.class_expression import OWLClassExpression
-from owlapy.owl_neural_reasoners.neural_ontology_manager import NeuralOntologyManager
-from owlapy.owl_ontology import AbstractOWLOntology
 
 class AbstractNeuralReasoner(ABC):
     """Abstract class for Neural Reasoners that operate on OWL Class Expressions using embeddings."""
     @abstractmethod
-    def __init__(self, ontology: Union[NeuralOntologyManager, AbstractOWLOntology], **kwargs):
+    def __init__(self, **kwargs):
         pass 
 
     @abstractmethod

owlapy/owl_neural_reasoners/owl_neural_reasoner.py

@@ -14,18 +14,15 @@
 from collections import Counter, OrderedDict
 from functools import lru_cache
 from owlapy.owl_neural_reasoners.abstract import AbstractNeuralReasoner
-from owlapy.owl_neural_reasoners.neural_ontology_manager import NeuralOntologyManager
 
 # TODO:
 def is_valid_entity(text_input: str):
     return True if "/" in text_input else False
 
 class OWLNeuralReasoner(AbstractNeuralReasoner):
     """ OWL Neural Reasoner uses a neural link predictor to retrieve instances of an OWL Class Expression"""
-    def __init__(self, ontology: NeuralOntologyManager, gamma: float = 0.25, max_cache_size: int = 2**20):
+    def __init__(self, path_of_kb: str = None, path_neural_embedding: str = None, gamma: float = 0.25, max_cache_size: int = 2**20):
         assert gamma is None or 0 <= gamma <= 1, "Confidence threshold (gamma) must be in the range [0, 1]."
-        path_of_kb = ontology.get_path()
-        path_neural_embedding = ontology.get_path_neural_embedding( )
         self.gamma = gamma
         self._prediction_cache = OrderedDict()
         self._max_cache_size = max_cache_size