Fix/set mean reversion target to D0(4)

Supersedes and closes #123

src/fsrs_optimizer/fsrs_optimizer.py

@@ -95,9 +95,13 @@ def stability_short_term(self, state: Tensor, rating: Tensor) -> Tensor:
         new_s = state[:, 0] * torch.exp(self.w[17] * (rating - 3 + self.w[18]))
         return new_s
 
+    def init_d(self, rating: Tensor) -> Tensor:
+        new_d = self.w[4] - torch.exp(self.w[5] * (X[:, 1] - 1)) + 1
+        return new_d
+
     def next_d(self, state: Tensor, rating: Tensor) -> Tensor:
         new_d = state[:, 1] - self.w[6] * (rating - 3)
-        new_d = self.mean_reversion(self.w[4], new_d)
+        new_d = self.mean_reversion(init_d(4), new_d)
         return new_d
 
     def step(self, X: Tensor, state: Tensor) -> Tensor:
@@ -113,7 +117,7 @@ def step(self, X: Tensor, state: Tensor) -> Tensor:
             # first learn, init memory states
             new_s = torch.ones_like(state[:, 0])
             new_s[index[0]] = self.w[index[1]]
-            new_d = self.w[4] - torch.exp(self.w[5] * (X[:, 1] - 1)) + 1
+            new_d = init_d(X[:, 1])
             new_d = new_d.clamp(1, 10)
         else:
             r = power_forgetting_curve(X[:, 0], state[:, 0])