finish ask part of the algorithm;

use jax.lax.while_loop in graph algorithms and forward function;
fix "enabled not care" bug in forward

configs/activations.py

@@ -1,32 +0,0 @@
-from neat.genome.activations import *
-
-ACT_TOTAL_LIST = [sigmoid_act, tanh_act, sin_act, gauss_act, relu_act, elu_act, lelu_act, selu_act, softplus_act,
-                  identity_act, clamped_act, inv_act, log_act, exp_act, abs_act, hat_act, square_act, cube_act]
-
-act_name2key = {
-    'sigmoid': 0,
-    'tanh': 1,
-    'sin': 2,
-    'gauss': 3,
-    'relu': 4,
-    'elu': 5,
-    'lelu': 6,
-    'selu': 7,
-    'softplus': 8,
-    'identity': 9,
-    'clamped': 10,
-    'inv': 11,
-    'log': 12,
-    'exp': 13,
-    'abs': 14,
-    'hat': 15,
-    'square': 16,
-    'cube': 17,
-}
-
-
-def refactor_act(config):
-    config['activation_default'] = act_name2key[config['activation_default']]
-    config['activation_options'] = [
-        act_name2key[act_name] for act_name in config['activation_options']
-    ]

configs/aggregations.py

@@ -1,20 +0,0 @@
-from neat.genome.aggregations import *
-
-AGG_TOTAL_LIST = [sum_agg, product_agg, max_agg, min_agg, maxabs_agg, median_agg, mean_agg]
-
-agg_name2key = {
-    'sum': 0,
-    'product': 1,
-    'max': 2,
-    'min': 3,
-    'maxabs': 4,
-    'median': 5,
-    'mean': 6,
-}
-
-
-def refactor_agg(config):
-    config['aggregation_default'] = agg_name2key[config['aggregation_default']]
-    config['aggregation_options'] = [
-        agg_name2key[act_name] for act_name in config['aggregation_options']
-    ]

configs/configer.py

@@ -4,8 +4,8 @@ import configparser
 
 import numpy as np
 
-from .activations import refactor_act
-from .aggregations import refactor_agg
+from neat.genome.activations import act_name2func
+from neat.genome.aggregations import agg_name2func
 
 # Configuration used in jit-able functions. The change of values will not cause the re-compilation of JAX.
 jit_config_keys = [
@@ -20,12 +20,12 @@ jit_config_keys = [
     "node_delete_prob",
     "compatibility_threshold",
     "bias_init_mean",
-    "bias_init_stdev",
+    "bias_init_std",
     "bias_mutate_power",
     "bias_mutate_rate",
     "bias_replace_rate",
     "response_init_mean",
-    "response_init_stdev",
+    "response_init_std",
     "response_mutate_power",
     "response_mutate_rate",
     "response_replace_rate",
@@ -36,7 +36,7 @@ jit_config_keys = [
     "aggregation_options",
     "aggregation_replace_rate",
     "weight_init_mean",
-    "weight_init_stdev",
+    "weight_init_std",
     "weight_mutate_power",
     "weight_mutate_rate",
     "weight_replace_rate",
@@ -90,14 +90,26 @@ class Configer:
         cls.__check_redundant_config(default_config, config)
         cls.__complete_config(default_config, config)
 
-        refactor_act(config)
-        refactor_agg(config)
-        input_idx = np.arange(config['num_inputs'])
-        output_idx = np.arange(config['num_inputs'], config['num_inputs'] + config['num_outputs'])
-        config['input_idx'] = input_idx
-        config['output_idx'] = output_idx
+        cls.refactor_activation(config)
+        cls.refactor_aggregation(config)
+
+        config['input_idx'] = np.arange(config['num_inputs'])
+        config['output_idx'] = np.arange(config['num_inputs'], config['num_inputs'] + config['num_outputs'])
+
         return config
 
+    @classmethod
+    def refactor_activation(cls, config):
+        config['activation_default'] = 0
+        config['activation_options'] = np.arange(len(config['activation_option_names']))
+        config['activation_funcs'] = [act_name2func[name] for name in config['activation_option_names']]
+
+    @classmethod
+    def refactor_aggregation(cls, config):
+        config['aggregation_default'] = 0
+        config['aggregation_options'] = np.arange(len(config['aggregation_option_names']))
+        config['aggregation_funcs'] = [agg_name2func[name] for name in config['aggregation_option_names']]
+
     @classmethod
     def create_jit_config(cls, config):
         jit_config = {k: config[k] for k in jit_config_keys}

configs/default_config.ini

@@ -5,7 +5,8 @@ init_maximum_nodes = 20
 init_maximum_connections = 20
 init_maximum_species = 10
 expands_coe = 2.0
-forward_way = "pop_batch"
+forward_way = "pop"
+batch_size = 4
 
 [population]
 fitness_threshold = 100000
@@ -46,12 +47,12 @@ response_replace_rate = 0.0
 
 [gene-activation]
 activation_default = "sigmoid"
-activation_options = ["sigmoid"]
+activation_option_names = ["sigmoid"]
 activation_replace_rate = 0.0
 
 [gene-aggregation]
 aggregation_default = "sum"
-aggregation_options = ["sum"]
+aggregation_option_names = ["sum"]
 aggregation_replace_rate = 0.0
 
 [gene-weight]