odify genome for the official release

examples/gymnax/cartpole.py

@@ -0,0 +1,41 @@
+import jax.numpy as jnp
+
+from pipeline import Pipeline
+from algorithm.neat import *
+
+from problem.rl_env import GymNaxEnv
+
+
+def action_policy(randkey, forward_func, obs):
+    return jnp.argmax(forward_func(obs))
+
+
+if __name__ == "__main__":
+    pipeline = Pipeline(
+        algorithm=NEAT(
+            species=DefaultSpecies(
+                genome=DefaultGenome(
+                    num_inputs=4,
+                    num_outputs=2,
+                    max_nodes=50,
+                    max_conns=100,
+                    # output_transform=lambda out: jnp.argmax(
+                    #     out
+                    # ),  # the action of cartpole is {0, 1}
+                ),
+                pop_size=10000,
+                species_size=10,
+            ),
+        ),
+        problem=GymNaxEnv(
+            env_name="CartPole-v1", repeat_times=5, action_policy=action_policy
+        ),
+        generation_limit=10000,
+        fitness_target=500,
+    )
+
+    # initialize state
+    state = pipeline.setup()
+    # print(state)
+    # run until terminate
+    state, best = pipeline.auto_run(state)