update data dtype

lululxvi · Jan 3, 2025 · 165e5ab · 165e5ab
1 parent 9b9fb5e
commit 165e5ab
Showing 1 changed file with 18 additions and 13 deletions.
diff --git a/deepxde/data/mf.py b/deepxde/data/mf.py
@@ -38,22 +38,24 @@ def train_next_batch(self, batch_size=None):
                     self.geom.uniform_points(self.num_lo, True),
                     self.geom.uniform_points(self.num_hi, True),
                 )
-            )
+            ).astype(config.real(np))
         else:
             self.X_train = np.vstack(
                 (
                     self.geom.random_points(self.num_lo, random=self.dist_train),
                     self.geom.random_points(self.num_hi, random=self.dist_train),
                 )
-            )
+            ).astype(config.real(np))
         y_lo_train = self.func_lo(self.X_train)
         y_hi_train = self.func_hi(self.X_train)
         self.y_train = [y_lo_train, y_hi_train]
         return self.X_train, self.y_train
 
     @run_if_any_none("X_test", "y_test")
     def test(self):
-        self.X_test = self.geom.uniform_points(self.num_test, True)
+        self.X_test = self.geom.uniform_points(self.num_test, True).astype(
+            config.real(np)
+        )
         y_lo_test = self.func_lo(self.X_test)
         y_hi_test = self.func_hi(self.X_test)
         self.y_test = [y_lo_test, y_hi_test]
@@ -84,20 +86,20 @@ def __init__(
         standardize=False,
     ):
         if X_lo_train is not None:
-            self.X_lo_train = X_lo_train
-            self.X_hi_train = X_hi_train
-            self.y_lo_train = y_lo_train
-            self.y_hi_train = y_hi_train
-            self.X_hi_test = X_hi_test
-            self.y_hi_test = y_hi_test
+            self.X_lo_train = X_lo_train.astype(config.real(np))
+            self.X_hi_train = X_hi_train.astype(config.real(np))
+            self.y_lo_train = y_lo_train.astype(config.real(np))
+            self.y_hi_train = y_hi_train.astype(config.real(np))
+            self.X_hi_test = X_hi_test.astype(config.real(np))
+            self.y_hi_test = y_hi_test.astype(config.real(np))
         elif fname_lo_train is not None:
-            data = np.loadtxt(fname_lo_train)
+            data = np.loadtxt(fname_lo_train).astype(config.real(np))
             self.X_lo_train = data[:, col_x]
             self.y_lo_train = data[:, col_y]
-            data = np.loadtxt(fname_hi_train)
+            data = np.loadtxt(fname_hi_train).astype(config.real(np))
             self.X_hi_train = data[:, col_x]
             self.y_hi_train = data[:, col_y]
-            data = np.loadtxt(fname_hi_test)
+            data = np.loadtxt(fname_hi_test).astype(config.real(np))
             self.X_hi_test = data[:, col_x]
             self.y_hi_test = data[:, col_y]
         else:
@@ -117,7 +119,10 @@ def losses_train(self, targets, outputs, loss_fn, inputs, model, aux=None):
         return [loss_lo, loss_hi]
 
     def losses_test(self, targets, outputs, loss_fn, inputs, model, aux=None):
-        return [bkd.as_tensor(0, dtype=config.real(bkd.lib)), loss_fn(targets[1], outputs[1])]
+        return [
+            bkd.as_tensor(0, dtype=config.real(bkd.lib)),
+            loss_fn(targets[1], outputs[1]),
+        ]
 
     @run_if_any_none("X_train", "y_train")
     def train_next_batch(self, batch_size=None):