add args record_episode in rl tasks, with related test "test_record_episode.ipynb";

add args return_data in func_fit tasks.

tensorneat/problem/func_fit/func_fit.py

@@ -8,11 +8,12 @@ from .. import BaseProblem
 class FuncFit(BaseProblem):
     jitable = True
 
-    def __init__(self, error_method: str = "mse"):
+    def __init__(self, error_method: str = "mse", return_data: bool = False):
         super().__init__()
 
         assert error_method in {"mse", "rmse", "mae", "mape"}
         self.error_method = error_method
+        self.return_data = return_data
 
     def setup(self, state: State = State()):
         return state
@@ -38,7 +39,10 @@ class FuncFit(BaseProblem):
         else:
             raise NotImplementedError
 
-        return -loss
+        if self.return_data:
+            return -loss, self.inputs
+        else:
+            return -loss
 
     def show(self, state, randkey, act_func, params, *args, **kwargs):
         predict = jax.vmap(act_func, in_axes=(None, 0, None))(

tensorneat/problem/func_fit/xor.py

@@ -4,8 +4,6 @@ from .func_fit import FuncFit
 
 
 class XOR(FuncFit):
-    def __init__(self, error_method: str = "mse"):
-        super().__init__(error_method)
 
     @property
     def inputs(self):

tensorneat/problem/func_fit/xor3d.py

@@ -4,9 +4,6 @@ from .func_fit import FuncFit
 
 
 class XOR3d(FuncFit):
-    def __init__(self, error_method: str = "mse"):
-        super().__init__(error_method)
-
     @property
     def inputs(self):
         return np.array(