wip experimenting with structural inference taking one theorem at a time

opennars · Feb 14, 2024 · ff761d0 · ff761d0
1 parent c0db1c7
commit ff761d0
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Showing 4 changed files with 52 additions and 11 deletions.
diff --git a/Tests/test_NAL/test_NAL4.py b/Tests/test_NAL/test_NAL4.py
@@ -301,6 +301,29 @@ def test_structural_transformation_10(self):
         )
         pass
 
+    def test_other_stuff(self):
+        # tasks_derived = []
+        # # tasks_derived = process_two_premises(
+        # #     '<<(*, $a, $b) --> is> <=> <$a --> $b>>.',
+        # #     None
+        # # )
+        # tasks_derived.extend(process_two_premises(
+        #     '<(*,cat,animal)-->is>.',
+        #     '<cat-->animal>.'
+        # ))
+        # tasks_derived.extend(process_two_premises(
+        #     '<(*,dog,animal)-->is>.',
+        #     '<dog-->animal>?',
+        #     600
+        # ))
+        # # for t in tasks_derived: print(t)
+        # self.assertTrue(
+        #     output_contains(tasks_derived, '<dog --> animal>. %1.00;0.29%')
+        #     or
+        #     output_contains(tasks_derived, '<dog --> animal>. %1.00;0.40%')
+        # )
+        pass
+
 if __name__ == '__main__':
 
     test_classes_to_run = [

diff --git a/Tests/utils_for_test.py b/Tests/utils_for_test.py
@@ -17,8 +17,8 @@
 nars = Reasoner(100, 100)
 engine: GeneralEngine = nars.inference
 
-NUM_CYCLES_MULTIPLIER = 4
-def process_two_premises(premise1: str, premise2: str, n_cycle: int) -> List[Task]:
+NUM_CYCLES_MULTIPLIER = 10
+def process_two_premises(premise1: str, premise2: str, n_cycle: int = 0) -> List[Task]:
     ''''''
     tasks_all_cycles = []
 

diff --git a/pynars/NARS/Control/Reasoner.py b/pynars/NARS/Control/Reasoner.py
@@ -26,8 +26,9 @@
 from ..InferenceEngine.KanrenEngine import util
 
 class Reasoner:
-    # avg_inference = 0
-    # num_runs = 0
+    avg_inference = 0
+    num_runs = 0
+
     all_theorems = Bag(100, 100, take_in_order=False)
 
     def __init__(self, n_memory, capacity, config='./config.json', nal_rules={1, 2, 3, 4, 5, 6, 7, 8, 9}) -> None:
@@ -147,7 +148,7 @@ def consider(self, tasks_derived: List[Task]):
             # t0 = time()
             tasks_inference_derived = self.inference_step(concept)
             tasks_derived.extend(tasks_inference_derived)
-            # t1 = time() - t0
+            # t1 = time() - t0 + 1e-6 # add epsilon to avoid division by 0
             # self.avg_inference += (t1 - self.avg_inference) / self.num_runs
             # print("inference:", 1 // self.avg_inference, "per second", f"({1//t1})")
 
@@ -329,7 +330,10 @@ def inference_step(self, concept: Concept):
 
             results = []
 
-            results.extend(self.inference.inference_immediate(task.sentence))
+            res, cached = self.inference.inference_immediate(task.sentence)
+
+            if not cached:
+                results.extend(res)
 
             for term, truth in results:
                 # TODO: how to properly handle stamp for immediate rules?
@@ -363,7 +367,7 @@ def inference_step(self, concept: Concept):
 
             # t0 = time()
             theorems = []
-            for _ in range(min(5, len(self.all_theorems))):
+            for _ in range(min(1, len(self.all_theorems))):
                 theorem = self.all_theorems.take(remove=True)
                 theorems.append(theorem)
 
@@ -467,8 +471,13 @@ def inference_step(self, concept: Concept):
                     # beleif_eternalized = belief # TODO: should it be added into the `tasks_derived`?
 
             # t0 = time()
-
-            results, cached = self.inference.inference(task.sentence, belief.sentence)
+
+            results = []
+
+            res, cached = self.inference.inference(task.sentence, belief.sentence)
+
+            if not cached: 
+                results.extend(res)
 
             # t1 = time() - t0
 
@@ -478,7 +487,10 @@ def inference_step(self, concept: Concept):
 
             # print("avg:", 1 // self._inference_time_avg, "per second")
 
-            results.extend(self.inference.inference_compositional(task.sentence, belief.sentence))
+            res, cached = self.inference.inference_compositional(task.sentence, belief.sentence)
+
+            if not cached:
+                results.extend(res)
 
             # print(">>>", results)
 

diff --git a/pynars/NARS/InferenceEngine/KanrenEngine/KanrenEngine.py b/pynars/NARS/InferenceEngine/KanrenEngine/KanrenEngine.py
@@ -61,6 +61,7 @@ def __init__(self):
     # INFERENCE (SYLLOGISTIC)
     @cache_notify
     def inference(self, t1: Sentence, t2: Sentence) -> list:
+        # print(f'Inference syllogistic\n{t1}\n{t2}')
         results = []
 
         t1e = variable_elimination(t2.term, t1.term)
@@ -142,8 +143,10 @@ def apply(self, rule, l1, l2):
     #############
     # IMMEDIATE #
     #############
-
+
+    @cache_notify
     def inference_immediate(self, t: Sentence):
+        # print(f'Inference immediate\n{t}')
         results = []
 
         l = logic(t.term)
@@ -165,6 +168,7 @@ def inference_immediate(self, t: Sentence):
 
     @cache_notify
     def inference_structural(self, t: Sentence, theorems = None):
+        # print(f'Inference structural\n{t}')
         results = []
 
         if not theorems:
@@ -191,7 +195,9 @@ def inference_structural(self, t: Sentence, theorems = None):
     # COMPOSITIONAL #
     #################
 
+    @cache_notify
     def inference_compositional(self, t1: Sentence, t2: Sentence):
+        # print(f'Inference compositional\n{t1}\n{t2}')
         results = []
 
         common = set(t1.term.sub_terms).intersection(t2.term.sub_terms)