initial commit in branch developing

examples/xor.py

@@ -6,35 +6,14 @@ from time_utils import using_cprofile
 from problems import Sin, Xor, DIY
 
 
-# xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
-# xor_outputs = np.array([[0], [1], [1], [0]])
-#
-#
-# def evaluate(forward_func: Callable) -> List[float]:
-#     """
-#     :param forward_func: (4: batch, 2: input size) -> (pop_size, 4: batch, 1: output size)
-#     :return:
-#     """
-#     outs = forward_func(xor_inputs)
-#     outs = jax.device_get(outs)
-#     fitnesses = 4 - np.sum((outs - xor_outputs) ** 2, axis=(1, 2))
-#     return fitnesses.tolist()  # returns a list
-
-
 # @using_cprofile
 @partial(using_cprofile, root_abs_path='/mnt/e/neat-jax/', replace_pattern="/mnt/e/neat-jax/")
 def main():
     config = Configer.load_config()
-    # config.neat.population.pop_size = 50
     problem = Xor()
-    # problem = Sin()
-    # problem = DIY(func=lambda x: (np.sin(x) + np.exp(x) - x ** 2) / (np.cos(x) + np.sqrt(x)) - np.log(x + 1))
     problem.refactor_config(config)
     pipeline = Pipeline(config, seed=0)
-    best_nodes, best_connections = pipeline.auto_run(problem.evaluate)
-    # print(best_nodes, best_connections)
-    # func = pipeline.function_factory.ask_batch_forward(best_nodes, best_connections)
-    # problem.print(func)
+    pipeline.auto_run(problem.evaluate)
 
 
 if __name__ == '__main__':