change str in config (act, agg) from str to callable

examples/func_fit/xor_hyperneat.py

@@ -3,6 +3,7 @@ from pipeline import Pipeline
 from algorithm.neat import NormalGene, NormalGeneConfig
 from algorithm.hyperneat import HyperNEAT, NormalSubstrate, NormalSubstrateConfig
 from problem.func_fit import XOR3d, FuncFitConfig
+from utils import Act
 
 
 if __name__ == '__main__':
@@ -27,8 +28,8 @@ if __name__ == '__main__':
             input_coors=((-1, -1), (-0.5, -1), (0.5, -1), (1, -1)),
         ),
         gene=NormalGeneConfig(
-            activation_default='tanh',
-            activation_options=('tanh', ),
+            activation_default=Act.tanh,
+            activation_options=(Act.tanh, ),
         ),
         problem=FuncFitConfig()
     )

examples/func_fit/xor_recurrent.py

@@ -36,5 +36,6 @@ if __name__ == '__main__':
     algorithm = NEAT(config, RecurrentGene)
     pipeline = Pipeline(config, algorithm, XOR3d)
     state = pipeline.setup()
+    pipeline.pre_compile(state)
     state, best = pipeline.auto_run(state)
     pipeline.show(state, best)

examples/gymnax/cartpole.py

@@ -19,8 +19,8 @@ def example_conf1():
             outputs=1,
         ),
         gene=NormalGeneConfig(
-            activation_default='sigmoid',
-            activation_options=('sigmoid',),
+            activation_default=Act.sigmoid,
+            activation_options=(Act.sigmoid,),
         ),
         problem=GymNaxConfig(
             env_name='CartPole-v1',
@@ -41,8 +41,8 @@ def example_conf2():
             outputs=1,
         ),
         gene=NormalGeneConfig(
-            activation_default='tanh',
-            activation_options=('tanh',),
+            activation_default=Act.tanh,
+            activation_options=(Act.tanh,),
         ),
         problem=GymNaxConfig(
             env_name='CartPole-v1',
@@ -63,8 +63,8 @@ def example_conf3():
             outputs=2,
         ),
         gene=NormalGeneConfig(
-            activation_default='tanh',
-            activation_options=('tanh',),
+            activation_default=Act.tanh,
+            activation_options=(Act.tanh,),
         ),
         problem=GymNaxConfig(
             env_name='CartPole-v1',
@@ -80,5 +80,5 @@ if __name__ == '__main__':
     algorithm = NEAT(conf, NormalGene)
     pipeline = Pipeline(conf, algorithm, GymNaxEnv)
     state = pipeline.setup()
+    pipeline.pre_compile(state)
     state, best = pipeline.auto_run(state)
-    pipeline.show(state, best)