finish all refactoring

examples/gymnax/mountain_car_continuous.py

@@ -1,38 +1,36 @@
-import jax.numpy as jnp
-
-from config import *
 from pipeline import Pipeline
-from algorithm import NEAT
-from algorithm.neat.gene import NormalGene, NormalGeneConfig
-from problem.rl_env import GymNaxConfig, GymNaxEnv
-
-
-def example_conf():
-    return Config(
-        basic=BasicConfig(
-            seed=42,
-            fitness_target=100,
-            pop_size=10000
-        ),
-        neat=NeatConfig(
-            inputs=2,
-            outputs=1,
-        ),
-        gene=NormalGeneConfig(
-            activation_default=Act.tanh,
-            activation_options=(Act.tanh,),
-        ),
-        problem=GymNaxConfig(
-            env_name='MountainCarContinuous-v0'
-        )
-    )
+from algorithm.neat import *
 
+from problem.rl_env import GymNaxEnv
+from utils import Act
 
 if __name__ == '__main__':
-    conf = example_conf()
+    pipeline = Pipeline(
+        algorithm=NEAT(
+            species=DefaultSpecies(
+                genome=DefaultGenome(
+                    num_inputs=2,
+                    num_outputs=1,
+                    max_nodes=50,
+                    max_conns=100,
+                    node_gene=DefaultNodeGene(
+                        activation_options=(Act.tanh, ),
+                        activation_default=Act.tanh,
+                    )
+                ),
+                pop_size=10000,
+                species_size=10,
+            ),
+        ),
+        problem=GymNaxEnv(
+            env_name='MountainCarContinuous-v0',
+        ),
+        generation_limit=10000,
+        fitness_target=500
+    )
 
-    algorithm = NEAT(conf, NormalGene)
-    pipeline = Pipeline(conf, algorithm, GymNaxEnv)
+    # initialize state
     state = pipeline.setup()
-    pipeline.pre_compile(state)
-    state, best = pipeline.auto_run(state)
+    # print(state)
+    # run until terminate
+    state, best = pipeline.auto_run(state)