The whole NEAT algorithm is written into functional programming.

examples/evox_test.py

@@ -1,26 +0,0 @@
-import jax
-from jax import numpy as jnp
-
-from evox import algorithms, problems, pipelines
-from evox.monitors import StdSOMonitor
-
-monitor = StdSOMonitor()
-
-pso = algorithms.PSO(
-    lb=jnp.full(shape=(2,), fill_value=-32),
-    ub=jnp.full(shape=(2,), fill_value=32),
-    pop_size=100,
-)
-
-ackley = problems.classic.Ackley()
-
-pipeline = pipelines.StdPipeline(pso, ackley, fitness_transform=monitor.record_fit)
-
-key = jax.random.PRNGKey(42)
-state = pipeline.init(key)
-
-# run the pipeline for 100 steps
-for i in range(100):
-    state = pipeline.step(state)
-
-print(monitor.get_min_fitness())

examples/jit_xor.py

@@ -1,28 +0,0 @@
-import numpy as np
-
-from configs import Configer
-from jit_pipeline import Pipeline
-
-xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
-xor_outputs = np.array([[0], [1], [1], [0]], dtype=np.float32)
-
-
-def evaluate(forward_func):
-    """
-    :param forward_func: (4: batch, 2: input size) -> (pop_size, 4: batch, 1: output size)
-    :return:
-    """
-    outs = forward_func(xor_inputs)
-    fitnesses = 4 - np.sum((outs - xor_outputs) ** 2, axis=(1, 2))
-    return np.array(fitnesses)  # returns a list
-
-
-def main():
-    config = Configer.load_config("xor.ini")
-    pipeline = Pipeline(config, seed=6)
-    nodes, cons = pipeline.auto_run(evaluate)
-    print(nodes, cons)
-
-
-if __name__ == '__main__':
-    main()

examples/xor.py

@@ -1,7 +1,8 @@
 import numpy as np
 
 from configs import Configer
-from pipeline import Pipeline
+from algorithms.neat.pipeline import Pipeline
+
 
 xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
 xor_outputs = np.array([[0], [1], [1], [0]], dtype=np.float32)
@@ -21,7 +22,8 @@ def main():
     config = Configer.load_config("xor.ini")
     pipeline = Pipeline(config, seed=6)
     nodes, cons = pipeline.auto_run(evaluate)
-    print(nodes, cons)
+    print(nodes)
+    print(cons)
 
 
 if __name__ == '__main__':