Fix dtype of dummy conditions if inference variables are available

Author: han-ol

bayesflow/networks/point_inference_network.py

@@ -132,7 +132,9 @@ def call(
         if xz is None and not self.built:
             raise ValueError("Cannot build inference network without inference variables.")
         if conditions is None:  # unconditional estimation uses a fixed input vector
-            conditions = keras.ops.convert_to_tensor([[1.0]])
+            conditions = keras.ops.convert_to_tensor(
+                [[1.0]], dtype=keras.ops.dtype(xz) if xz is not None else "float32"
+            )
 
         # pass conditions to the shared subnet
         output = self.subnet(conditions, training=training)