make fully stateful in module ga.

tensorneat/algorithm/neat/ga/crossover/base.py

@@ -1,3 +1,10 @@
+from utils import State
+
+
 class BaseCrossover:
-    def __call__(self, randkey, genome, nodes1, nodes2, conns1, conns2):
+
+    def setup(self, state=State()):
+        return state
+
+    def __call__(self, state, key, genome, nodes1, nodes2, conns1, conns2):
         raise NotImplementedError

tensorneat/algorithm/neat/ga/crossover/default.py

@@ -5,12 +5,12 @@ from .base import BaseCrossover
 
 class DefaultCrossover(BaseCrossover):
 
-    def __call__(self, randkey, genome, nodes1, conns1, nodes2, conns2):
+    def __call__(self, state, key, genome, nodes1, conns1, nodes2, conns2):
         """
         use genome1 and genome2 to generate a new genome
         notice that genome1 should have higher fitness than genome2 (genome1 is winner!)
         """
-        randkey_1, randkey_2, key = jax.random.split(randkey, 3)
+        randkey_1, randkey_2, key = jax.random.split(key, 3)
 
         # crossover nodes
         keys1, keys2 = nodes1[:, 0], nodes2[:, 0]

tensorneat/algorithm/neat/ga/mutation/base.py

@@ -1,3 +1,10 @@
+from utils import State
+
+
 class BaseMutation:
-    def __call__(self, key, genome, nodes, conns, new_node_key):
-        raise NotImplementedError
+
+    def setup(self, state=State()):
+        return state
+
+    def __call__(self, state, key, genome, nodes, conns, new_node_key):
+        raise NotImplementedError

tensorneat/algorithm/neat/ga/mutation/default.py

@@ -17,7 +17,7 @@ class DefaultMutation(BaseMutation):
         self.node_add = node_add
         self.node_delete = node_delete
 
-    def __call__(self, randkey, genome, nodes, conns, new_node_key):
+    def __call__(self, state, randkey, genome, nodes, conns, new_node_key):
         k1, k2 = jax.random.split(randkey)
 
         nodes, conns = self.mutate_structure(k1, genome, nodes, conns, new_node_key)