Allow estimation of univariate MVN

Author: han-ol

bayesflow/networks/point_inference_network.py

@@ -132,7 +132,7 @@ 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]], dtype=keras.ops.dtype(xz))
+            conditions = keras.ops.convert_to_tensor([[1.0]])
 
         # pass conditions to the shared subnet
         output = self.subnet(conditions, training=training)

bayesflow/scores/multivariate_normal_score.py

@@ -101,6 +101,8 @@ def sample(self, batch_shape: Shape, mean: Tensor, covariance: Tensor) -> Tensor
         Tensor
             A tensor of shape (batch_size, num_samples, D) containing the generated samples.
         """
+        if len(batch_shape) == 1:
+            batch_shape = (1,) + batch_shape
         batch_size, num_samples = batch_shape
         dim = keras.ops.shape(mean)[-1]
         if keras.ops.shape(mean) != (batch_size, dim):