add package problems

examples/xor.py

@@ -1,34 +1,35 @@
-from typing import Callable, List
 from functools import partial
 
-import jax
-import numpy as np
-
 from utils import Configer
 from algorithms.neat import Pipeline
 from time_utils import using_cprofile
-
-xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
-xor_outputs = np.array([[0], [1], [1], [0]])
+from problems import Sin, Xor
 
 
-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
+# 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()
+    # problem = Xor()
+    problem = Sin()
+    problem.refactor_config(config)
     pipeline = Pipeline(config, seed=11454)
-    pipeline.auto_run(evaluate)
+    pipeline.auto_run(problem.evaluate)
 
 
 if __name__ == '__main__':