modify NEAT package; successfully run xor example

examples/func_fit/xor.py

@@ -1,43 +1,38 @@
-from pipeline import Pipeline
-from algorithm.neat import *
-
-from problem.func_fit import XOR3d
-from tensorneat.common import ACT_ALL, AGG_ALL, Act, Agg
+from tensorneat.pipeline import Pipeline
+from tensorneat.algorithm.neat import NEAT
+from tensorneat.genome import DefaultGenome, DefaultNodeGene, DefaultMutation
+from tensorneat.problem.func_fit import XOR3d
+from tensorneat.common import Act, Agg
 
 if __name__ == "__main__":
     pipeline = Pipeline(
         algorithm=NEAT(
-            species=DefaultSpecies(
-                genome=DenseInitialize(
-                    num_inputs=3,
-                    num_outputs=1,
-                    max_nodes=50,
-                    max_conns=100,
-                    node_gene=DefaultNodeGene(
-                        activation_default=Act.tanh,
-                        # activation_options=(Act.tanh,),
-                        activation_options=ACT_ALL,
-                        aggregation_default=Agg.sum,
-                        # aggregation_options=(Agg.sum,),
-                        aggregation_options=AGG_ALL,
-                    ),
-                    output_transform=Act.standard_sigmoid,  # the activation function for output node
-                    mutation=DefaultMutation(
-                        node_add=0.1,
-                        conn_add=0.1,
-                        node_delete=0,
-                        conn_delete=0,
-                    ),
+            pop_size=10000,
+            species_size=20,
+            compatibility_threshold=2,
+            survival_threshold=0.01,
+            genome=DefaultGenome(
+                num_inputs=3,
+                num_outputs=1,
+                init_hidden_layers=(),
+                node_gene=DefaultNodeGene(
+                    activation_default=Act.tanh,
+                    activation_options=Act.tanh,
+                    aggregation_default=Agg.sum,
+                    aggregation_options=Agg.sum,
+                ),
+                output_transform=Act.standard_sigmoid,  # the activation function for output node
+                mutation=DefaultMutation(
+                    node_add=0.1,
+                    conn_add=0.1,
+                    node_delete=0,
+                    conn_delete=0,
                 ),
-                pop_size=10000,
-                species_size=20,
-                compatibility_threshold=2,
-                survival_threshold=0.01,  # magic
             ),
         ),
         problem=XOR3d(),
-        generation_limit=10000,
-        fitness_target=-1e-3,
+        generation_limit=500,
+        fitness_target=-1e-8,
     )
 
     # initialize state
@@ -47,4 +42,3 @@ if __name__ == "__main__":
     state, best = pipeline.auto_run(state)
     # show result
     pipeline.show(state, best)
-    pipeline.save(state=state)