Make powf broadcastable (#2398)

crates/burn-ndarray/src/ops/base.rs

@@ -480,12 +480,13 @@ where
         rhs: NdArrayTensor<OtherE>,
         var_name: impl FnMut(&E, &OtherE) -> E,
     ) -> NdArrayTensor<E> {
-        NdArrayTensor::new(
-            Zip::from(lhs.array.view())
-                .and(rhs.array.view())
-                .map_collect(var_name)
-                .into_shared(),
-        )
+        let lhs = lhs
+            .array
+            .broadcast(rhs.array.dim())
+            .unwrap_or(lhs.array.view());
+        let rhs = rhs.array.broadcast(lhs.dim()).unwrap_or(rhs.array.view());
+
+        NdArrayTensor::new(Zip::from(lhs).and(rhs).map_collect(var_name).into_shared())
     }
 
     pub(crate) fn elementwise_op_scalar(

crates/burn-tensor/src/tests/ops/powf.rs

@@ -54,4 +54,21 @@ mod tests {
 
         output.into_data().assert_approx_eq(&expected, 3);
     }
+
+    #[test]
+    fn should_support_powf_broadcasted() {
+        let device = Default::default();
+        let tensor_1 = Tensor::<TestBackend, 1>::from_floats([2.0, 3.0, 4.0], &device);
+        let tensor_2 = Tensor::from_floats([1.0], &device);
+
+        // Broadcast rhs
+        let output = tensor_1.clone().powf(tensor_2.clone());
+        output.into_data().assert_approx_eq(&tensor_1.to_data(), 3);
+
+        // Broadcast lhs
+        let output = tensor_2.powf(tensor_1);
+        output
+            .into_data()
+            .assert_approx_eq(&TensorData::from([1.0, 1.0, 1.0]), 3);
+    }
 }