added a ConditionalScalarEstimator which subclasses ConditionalDiscre…

…tePolicyEstimator

src/gfn/modules.py

@@ -148,7 +148,7 @@ def __init__(
         self,
         module: nn.Module,
         n_actions: int,
-        preprocessor: Preprocessor | None,
+        preprocessor: Preprocessor | None = None,
         is_backward: bool = False,
     ):
         """Initializes a estimator for P_F for discrete environments.
@@ -226,7 +226,7 @@ def __init__(
         conditioning_module: nn.Module,
         final_module: nn.Module,
         n_actions: int,
-        preprocessor: Preprocessor | None,
+        preprocessor: Preprocessor | None = None,
         is_backward: bool = False,
     ):
         """Initializes a estimator for P_F for discrete environments.
@@ -252,3 +252,33 @@ def forward(
             self._output_dim_is_checked = True
 
         return out
+
+
+class ConditionalScalarEstimator(ConditionalDiscretePolicyEstimator):
+    def __init__(
+        self,
+        state_module: nn.Module,
+        conditioning_module: nn.Module,
+        final_module: nn.Module,
+        preprocessor: Preprocessor | None = None,
+        is_backward: bool = False,
+    ):
+        super().__init__(
+            state_module,
+            conditioning_module,
+            final_module,
+            n_actions=1,
+            preprocessor=preprocessor,
+            is_backward=is_backward,
+        )
+
+    def expected_output_dim(self) -> int:
+        return 1
+
+    def to_probability_distribution(
+        self,
+        states: States,
+        module_output: TT["batch_shape", "output_dim", float],
+        **policy_kwargs: Optional[dict],
+    ) -> Distribution:
+        raise NotImplementedError