finish jit-able speciate function

next time i'll create a new branch

examples/function_tests.py

@@ -23,8 +23,6 @@ if __name__ == '__main__':
         new_node_idx += len(pop_nodes)
         pop_nodes, pop_connections = mutate_func(mutate_keys, pop_nodes, pop_connections, new_nodes)
         pop_nodes, pop_connections = jax.device_get([pop_nodes, pop_connections])
-        # for i in range(len(pop_nodes)):
-        #     check_array_valid(pop_nodes[i], pop_connections[i], input_idx, output_idx)
         idx1 = np.random.permutation(len(pop_nodes))
         idx2 = np.random.permutation(len(pop_nodes))
 
@@ -32,13 +30,6 @@ if __name__ == '__main__':
         n2, c2 = pop_nodes[idx2], pop_connections[idx2]
         crossover_keys = jax.random.split(subkey, len(pop_nodes))
 
-        # for idx, (zn1, zc1, zn2, zc2) in enumerate(zip(n1, c1, n2, c2)):
-        #     n, c = crossover(crossover_keys[idx], zn1, zc1, zn2, zc2)
-        #     try:
-        #         check_array_valid(n, c, input_idx, output_idx)
-        #     except AssertionError as e:
-        #         crossover(crossover_keys[idx], zn1, zc1, zn2, zc2)
-
         pop_nodes, pop_connections = crossover_func(crossover_keys, n1, c1, n2, c2)
 
         for i in range(len(pop_nodes)):

examples/jax_playground.py

@@ -3,56 +3,45 @@ import jax.numpy as jnp
 from jax import jit, vmap
 from time_utils import using_cprofile
 from time import time
-
+#
 @jit
 def fx(x, y):
     return x + y
-
-
+#
+#
+# # @jit
+# def fy(z):
+#     z1, z2 = z, z + 1
+#     vmap_fx = vmap(fx)
+#     return vmap_fx(z1, z2)
+#
 # @jit
-def fy(z):
-    z1, z2 = z, z + 1
-    vmap_fx = vmap(fx)
-    return vmap_fx(z1, z2)
-
-@jit
-def test_while(num, init_val):
-    def cond_fun(carry):
-        i, cumsum = carry
-        return i < num
-
-    def body_fun(carry):
-        i, cumsum = carry
-        cumsum += i
-        return i + 1, cumsum
-
-    return jax.lax.while_loop(cond_fun, body_fun, (0, init_val))
+# def test_while(num, init_val):
+#     def cond_fun(carry):
+#         i, cumsum = carry
+#         return i < num
+#
+#     def body_fun(carry):
+#         i, cumsum = carry
+#         cumsum += i
+#         return i + 1, cumsum
+#
+#     return jax.lax.while_loop(cond_fun, body_fun, (0, init_val))
 
 
 
-@using_cprofile
+
+# @using_cprofile
 def main():
-    z = jnp.zeros((100000, ))
+    vmap_f = vmap(fx, in_axes=(None, 0))
+    vmap_vmap_f = vmap(vmap_f, in_axes=(0, None))
+    a = jnp.array([20,10,30])
+    b = jnp.array([6, 5, 4])
+    res = vmap_vmap_f(a, b)
+    print(res)
+    print(jnp.argmin(res, axis=1))
 
-    num = 100
 
-    nums = jnp.arange(num) * 10
-
-    f = jit(vmap(test_while, in_axes=(0, None))).lower(nums, z).compile()
-    def test_time(*args):
-        return f(*args)
-
-    print(test_time(nums, z))
-
-    #
-    #
-    # for i in range(10):
-    #     num = 10 ** i
-    #     st = time()
-    #     res = test_time(num, z)
-    #     print(res)
-    #     t = time() - st
-    #     print(f"num: {num}, time: {t}")
 
 if __name__ == '__main__':
     main()

examples/jitable_speciate_t.py

@@ -0,0 +1,67 @@
+import jax
+import jax.numpy as jnp
+import numpy as np
+from algorithms.neat.function_factory import FunctionFactory
+from algorithms.neat.genome.debug.tools import check_array_valid
+from utils import Configer
+from algorithms.neat.jitable_speciate import jitable_speciate
+from algorithms.neat.genome.crossover import crossover
+from algorithms.neat.genome.utils import I_INT
+from time import time
+
+if __name__ == '__main__':
+    config = Configer.load_config()
+    function_factory = FunctionFactory(config, debug=True)
+    initialize_func = function_factory.create_initialize()
+
+    pop_nodes, pop_connections, input_idx, output_idx = initialize_func()
+    mutate_func = function_factory.create_mutate(pop_nodes.shape[1], pop_connections.shape[1])
+    crossover_func = function_factory.create_crossover(pop_nodes.shape[1], pop_connections.shape[1])
+
+    N, C, species_size = function_factory.init_N, function_factory.init_C, 20
+    spe_center_nodes = np.full((species_size, N, 5), np.nan)
+    spe_center_connections = np.full((species_size, C, 4), np.nan)
+    spe_center_nodes[0] = pop_nodes[0]
+    spe_center_connections[0] = pop_connections[0]
+
+    key = jax.random.PRNGKey(0)
+    new_node_idx = 100
+
+    while True:
+        start_time = time()
+        key, subkey = jax.random.split(key)
+        mutate_keys = jax.random.split(subkey, len(pop_nodes))
+        new_nodes = np.arange(new_node_idx, new_node_idx + len(pop_nodes))
+        new_node_idx += len(pop_nodes)
+        pop_nodes, pop_connections = mutate_func(mutate_keys, pop_nodes, pop_connections, new_nodes)
+        pop_nodes, pop_connections = jax.device_get([pop_nodes, pop_connections])
+        # for i in range(len(pop_nodes)):
+        #     check_array_valid(pop_nodes[i], pop_connections[i], input_idx, output_idx)
+        idx1 = np.random.permutation(len(pop_nodes))
+        idx2 = np.random.permutation(len(pop_nodes))
+
+        n1, c1 = pop_nodes[idx1], pop_connections[idx1]
+        n2, c2 = pop_nodes[idx2], pop_connections[idx2]
+        crossover_keys = jax.random.split(subkey, len(pop_nodes))
+
+        # for i in range(len(pop_nodes)):
+        #     check_array_valid(pop_nodes[i], pop_connections[i], input_idx, output_idx)
+
+        #speciate next generation
+
+        idx2specie, spe_center_nodes, spe_center_cons = jitable_speciate(pop_nodes, pop_connections, spe_center_nodes, spe_center_connections,
+                               compatibility_threshold=2.5)
+
+        idx2specie = np.array(idx2specie)
+        spe_dict = {}
+        for i in range(len(idx2specie)):
+            spe_idx = idx2specie[i]
+            if spe_idx not in spe_dict:
+                spe_dict[spe_idx] = 1
+            else:
+                spe_dict[spe_idx] += 1
+
+        print(spe_dict)
+        assert np.all(idx2specie != I_INT)
+        print(time() - start_time)
+        # print(idx2specie)