又搞到3点，还是没有找到问题在哪，不过已经排除了是forward的问题

algorithms/neat/genome/numpy/__init__.py

@@ -1,4 +1,4 @@
-from .genome import create_initialize_function, expand, expand_single, analysis
+from .genome import create_initialize_function, expand, expand_single, analysis, pop_analysis
 from .distance import distance
 from .mutate import create_mutate_function
 from .forward import create_forward_function

algorithms/neat/genome/numpy/aggregations.py

@@ -69,7 +69,6 @@ agg_name2key = {
 
 def agg(idx, z):
     idx = np.asarray(idx, dtype=np.int32)
-
     if np.all(z == 0.):
         return 0
     else:

algorithms/neat/genome/numpy/forward.py

@@ -76,7 +76,6 @@ def forward_single(inputs: NDArray, N: int, input_idx: NDArray, output_idx: NDAr
         # for some nodes (inputs nodes), the output z will be nan, thus we do not update the vals
         ini_vals[i] = z
 
-
     return ini_vals[output_idx]
 
 

algorithms/neat/genome/numpy/genome.py

@@ -198,8 +198,13 @@ def analysis(nodes: NDArray, connections: NDArray, input_keys, output_keys) -> \
 
 def pop_analysis(pop_nodes, pop_connections, input_keys, output_keys):
     res = []
+    total_nodes, total_connections = 0, 0
     for nodes, connections in zip(pop_nodes, pop_connections):
-        res.append(analysis(nodes, connections, input_keys, output_keys))
+        nodes, connections = analysis(nodes, connections, input_keys, output_keys)
+        res.append((nodes, connections))
+        total_nodes += len(nodes)
+        total_connections += len(connections)
+    print(total_nodes - 200, total_connections)
     return res
 
 

algorithms/neat/genome/numpy/mutate.py

@@ -9,6 +9,8 @@ from .utils import fetch_random, fetch_first, I_INT
 from .genome import add_node, add_connection_by_idx, delete_node_by_idx, delete_connection_by_idx
 from .graph import check_cycles
 
+add_node_cnt, delete_node_cnt, add_connection_cnt, delete_connection_cnt = 0, 0, 0, 0
+
 
 def create_mutate_function(config, input_keys, output_keys, batch: bool):
     """
@@ -79,11 +81,15 @@ def create_mutate_function(config, input_keys, output_keys, batch: bool):
         return mutate_func
     else:
         def batch_mutate_func(pop_nodes, pop_connections, new_node_keys):
+            global add_node_cnt, delete_node_cnt, add_connection_cnt, delete_connection_cnt
+            add_node_cnt, delete_node_cnt, add_connection_cnt, delete_connection_cnt = 0, 0, 0, 0
             res_nodes, res_connections = [], []
             for nodes, connections, new_node_key in zip(pop_nodes, pop_connections, new_node_keys):
                 nodes, connections = mutate_func(nodes, connections, new_node_key)
                 res_nodes.append(nodes)
                 res_connections.append(connections)
+            # print(f"add_node_cnt: {add_node_cnt}, delete_node_cnt: {delete_node_cnt}, "
+            #       f"add_connection_cnt: {add_connection_cnt}, delete_connection_cnt: {delete_connection_cnt}")
             return np.stack(res_nodes, axis=0), np.stack(res_connections, axis=0)
 
         return batch_mutate_func
@@ -161,6 +167,8 @@ def mutate(nodes: NDArray,
     :return:
     """
 
+    global add_node_cnt, delete_node_cnt, add_connection_cnt, delete_connection_cnt
+
     # mutate_structure
     def nothing(n, c):
         return n, c
@@ -200,18 +208,22 @@ def mutate(nodes: NDArray,
         # mutate add node
         if rand() < add_node_rate:
             nodes, connections = m_add_node(nodes, connections)
+            add_node_cnt += 1
 
         # mutate delete node
         if rand() < delete_node_rate:
             nodes, connections = m_delete_node(nodes, connections)
+            delete_node_cnt += 1
 
         # mutate add connection
         if rand() < add_connection_rate:
             nodes, connections = m_add_connection(nodes, connections)
+            add_connection_cnt += 1
 
         # mutate delete connection
         if rand() < delete_connection_rate:
             nodes, connections = m_delete_connection(nodes, connections)
+            delete_connection_cnt += 1
 
     nodes, connections = mutate_values(nodes, connections, bias_mean, bias_std, bias_mutate_strength,
                                        bias_mutate_rate, bias_replace_rate, response_mean, response_std,
@@ -220,6 +232,8 @@ def mutate(nodes: NDArray,
                                        weight_mutate_rate, weight_replace_rate, act_range, act_replace_rate, agg_range,
                                        agg_replace_rate, enabled_reverse_rate)
 
+    # print(add_node_cnt, delete_node_cnt, add_connection_cnt, delete_connection_cnt)
+
     return nodes, connections
 
 
@@ -321,9 +335,9 @@ def mutate_float_values(old_vals: NDArray, mean: float, std: float,
     replace = np.random.normal(size=old_vals.shape) * std + mean
     r = rand(*old_vals.shape)
     new_vals = old_vals
-    new_vals = np.where(r < mutate_rate, new_vals + noise, new_vals)
+    new_vals = np.where(r <= mutate_rate, new_vals + noise, new_vals)
     new_vals = np.where(
-        np.logical_and(mutate_rate < r, r < mutate_rate + replace_rate),
+        (mutate_rate < r) & (r <= mutate_rate + replace_rate),
         replace,
         new_vals
     )
@@ -413,7 +427,7 @@ def mutate_delete_node(nodes: NDArray, connections: NDArray,
     node_key, node_idx = choice_node_key(nodes, input_keys, output_keys,
                                          allow_input_keys=False, allow_output_keys=False)
 
-    if np.isnan(node_key):
+    if node_idx == I_INT:
         return nodes, connections
 
     # delete the node