odify genome for the official release

examples/brax/half_cheetah.py

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+import jax
+
+from pipeline import Pipeline
+from algorithm.neat import *
+
+from problem.rl_env import BraxEnv
+from tensorneat.common import Act
+
+
+def sample_policy(randkey, obs):
+    return jax.random.uniform(randkey, (6,), minval=-1, maxval=1)
+
+
+if __name__ == "__main__":
+    pipeline = Pipeline(
+        algorithm=NEAT(
+            species=DefaultSpecies(
+                genome=DefaultGenome(
+                    num_inputs=17,
+                    num_outputs=6,
+                    max_nodes=50,
+                    max_conns=100,
+                    node_gene=DefaultNodeGene(
+                        activation_options=(Act.tanh,),
+                        activation_default=Act.tanh,
+                    ),
+                    output_transform=Act.tanh,
+                ),
+                pop_size=1000,
+                species_size=10,
+            ),
+        ),
+        problem=BraxEnv(
+            env_name="halfcheetah",
+            max_step=1000,
+            obs_normalization=True,
+            sample_episodes=1000,
+            sample_policy=sample_policy,
+        ),
+        generation_limit=10000,
+        fitness_target=5000,
+    )
+
+    # initialize state
+    state = pipeline.setup()
+    # print(state)
+    # run until terminate
+    state, best = pipeline.auto_run(state)